{"meta":{"query_hash":"d8c4b8c8c302","filters":{"topic":"Gene Regulatory Network Analysis"},"cohort_total":965,"direct_labels_cover":1,"predictions_cover":965,"exported":965,"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/d8c4b8c8c302","api":"https://metacan.xera.ac/api/v1/cohort?topic=Gene+Regulatory+Network+Analysis"},"results":[{"id":"W1033913700","doi":"10.1051/mmnp/201510312","title":"An Invariant-Manifold Approach to Lumping","year":2015,"lang":"en","type":"article","venue":"Mathematical Modelling of Natural Phenomena","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"University of Lethbridge","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Invariant manifold; Attractor; Invariant (physics); Lyapunov function; Mathematics; Manifold (fluid mechanics); Applied mathematics; Nonlinear system; Equilibrium point; Dimension (graph theory); Mathematical analysis; LTI system theory; Dimensionality reduction; Fixed point; Differential equation; Linear system; Pure mathematics; Computer science; Physics; Mathematical physics","score_opus":0.04605011869390923,"score_gpt":0.2552761186040819,"score_spread":0.20922599991017266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1033913700","genre_codex":"methods","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":[0.42966,0.0003135789,0.56685805,0.00003598584,0.00003699866,0.000156055,0.0000020543382,0.000017184857,0.0029200916],"genre_scores_gemma":[0.9268754,0.000004509273,0.07247825,0.000102525715,0.00024260605,0.000010983164,0.000037852664,0.000029050014,0.00021880852],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99866325,0.000058715203,0.0003383081,0.00038175008,0.00027574168,0.00028225323],"domain_scores_gemma":[0.9989286,0.000011250847,0.00008729941,0.0005454818,0.0001448234,0.0002825441],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042241282,0.00018270324,0.00030093567,0.00007238952,0.000040091974,0.000027466713,0.0003534618,0.00008876514,0.0000039523516],"category_scores_gemma":[0.00003510412,0.00015848193,0.000105365485,0.00018507452,0.000036923448,0.000008197746,0.00008480415,0.00009838069,0.000017367682],"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":[0.00010122773,0.00041340513,0.000025115341,0.0001101388,0.00017206305,0.0000010973235,0.0006921395,0.91520673,0.067274764,0.0149775455,0.00042003585,0.00060573884],"study_design_scores_gemma":[0.0003364685,0.00021093176,0.000009432484,0.000026645539,0.00006837095,0.000008874109,0.00019288747,0.9697833,0.012532621,0.016226415,0.00027103632,0.00033302806],"about_ca_topic_score_codex":0.000004514581,"about_ca_topic_score_gemma":6.1784186e-7,"teacher_disagreement_score":0.49721542,"about_ca_system_score_codex":0.000020929836,"about_ca_system_score_gemma":0.000038184065,"threshold_uncertainty_score":0.6462705},"labels":[],"label_agreement":null},{"id":"W1046806","doi":"10.1007/978-3-642-19621-8_5","title":"Stochastic Gene Expression and the Processing and Propagation of Noisy Signals in Genetic Networks","year":2011,"lang":"en","type":"book-chapter","venue":"Intelligent systems reference library","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ottawa Hospital; University of Ottawa","funders":"","keywords":"Inference; Bayes' theorem; Fidelity; Population; Expression (computer science); Computer science; Noise (video); Gene; Biology; Computational biology; Artificial intelligence; Genetics; Bayesian probability","score_opus":0.019045300501899797,"score_gpt":0.21180402228304493,"score_spread":0.19275872178114514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1046806","genre_codex":"review","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":[0.20575269,0.59102696,0.16180296,0.0000915582,0.00058702147,0.005883564,0.00008715112,0.0000946709,0.034673423],"genre_scores_gemma":[0.97938055,0.005035922,0.00016532546,0.000020703383,0.00022621427,0.000058035177,0.00012120767,0.00006477177,0.014927272],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9982735,0.00012920157,0.0006860044,0.00053152407,0.0001814973,0.00019827468],"domain_scores_gemma":[0.9988583,0.000033821118,0.00055036304,0.0004134057,0.00006334025,0.00008078027],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020336067,0.00033776852,0.0005201628,0.0001337319,0.000056461027,0.00005482005,0.00024237983,0.0004645826,0.000023344544],"category_scores_gemma":[0.000010916836,0.00023728625,0.0000769946,0.00004947812,0.00029045792,0.000014387564,0.00025650935,0.00021045144,0.0000018930557],"study_design_candidate":"simulation_or_modeling","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":[0.008581247,0.0005460505,0.015009512,0.011072857,0.0037724902,0.0001489332,0.0048597623,0.36268464,0.26612857,0.035972368,0.004331245,0.28689232],"study_design_scores_gemma":[0.012312162,0.0044350997,0.007905719,0.04976097,0.004633316,0.0012950966,0.0015017202,0.38418338,0.406091,0.053232368,0.060722567,0.01392658],"about_ca_topic_score_codex":0.000015657324,"about_ca_topic_score_gemma":0.0000051456514,"teacher_disagreement_score":0.7736279,"about_ca_system_score_codex":0.000008079608,"about_ca_system_score_gemma":0.000082515675,"threshold_uncertainty_score":0.96762526},"labels":[],"label_agreement":null},{"id":"W1080308004","doi":"10.1016/j.jmb.2015.07.021","title":"Studying Cellular Signal Transduction with OMIC Technologies","year":2015,"lang":"en","type":"review","venue":"Journal of Molecular Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; Breast Cancer Alliance; National Cancer Institute, Cairo University; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; National Cancer Institute; Richard and Susan Smith Family Foundation","keywords":"Systems biology; Signal transduction; Computational biology; Computer science; Biology; SIGNAL (programming language); Cell biology","score_opus":0.023565863788359117,"score_gpt":0.2910461617834173,"score_spread":0.2674802979950582,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1080308004","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027168216,0.9776275,0.019056711,0.00004333149,0.00019939432,0.00028395298,0.0000098394985,0.000017329156,0.000045089208],"genre_scores_gemma":[0.005506017,0.9913974,0.0023792759,0.00001926066,0.00040965274,0.000017728646,0.00012591697,0.000088585184,0.000056175875],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99742603,0.0005001961,0.0009348842,0.0004943733,0.00025523384,0.00038928437],"domain_scores_gemma":[0.99762785,0.000015514426,0.0012825283,0.00056353665,0.00039551142,0.000115058625],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007889712,0.0005370467,0.0017961924,0.00044536486,0.000057799327,0.000024730083,0.0007153101,0.00093192037,0.000014011308],"category_scores_gemma":[0.000044021446,0.00037535673,0.0008885016,0.00039499046,0.00024553013,0.0000045619527,0.00013191106,0.0005510397,0.000006327106],"study_design_candidate":"not_applicable","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":[0.00010930776,0.000142061,0.000029288187,0.0009044828,0.0037916696,0.00022929668,0.00001549926,0.00032888245,0.051571816,0.000041380743,0.00075130654,0.942085],"study_design_scores_gemma":[0.00049261755,0.0015665796,2.8189612e-7,0.0006847165,0.002541741,0.0011541802,0.00008028571,0.0000033919157,0.010633734,0.00012536907,0.9822392,0.0004778984],"about_ca_topic_score_codex":0.0000013825188,"about_ca_topic_score_gemma":0.0000025107997,"teacher_disagreement_score":0.9814879,"about_ca_system_score_codex":0.000090025875,"about_ca_system_score_gemma":0.0006740058,"threshold_uncertainty_score":0.9998698},"labels":[],"label_agreement":null},{"id":"W121268079","doi":"10.1007/3-540-35888-9_13","title":"Exactly Reduced Chemical Master Equations","year":2006,"lang":"en","type":"book-chapter","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Master equation; Generalization; Mathematics; Differential equation; Hierarchy; Applied mathematics; Population; Stochastic differential equation; Limit (mathematics); Probability distribution; Statistic; Statistical physics; Mathematical analysis; Statistics; Physics","score_opus":0.017461593716517208,"score_gpt":0.22206129944309322,"score_spread":0.20459970572657601,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W121268079","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002554345,0.00092903763,0.003660169,0.00014315477,0.000111875626,0.00017534262,0.000025491614,0.00003169223,0.9923689],"genre_scores_gemma":[0.11936351,0.000044586202,0.0006491449,0.00017504589,0.0009951399,0.000009954028,0.0015438845,0.000080520804,0.8771382],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99866974,0.000011429461,0.00032818064,0.00055830705,0.00019953132,0.00023281178],"domain_scores_gemma":[0.9989554,0.000008979365,0.00014097623,0.0006970644,0.00010331843,0.00009424254],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00007018313,0.00033087915,0.00028045275,0.000071274604,0.000042963304,0.000024954215,0.00021861098,0.0006340538,0.000917702],"category_scores_gemma":[0.000010375443,0.00032501234,0.00036275332,0.000022470758,0.00008397488,0.0000011130132,0.00014368801,0.00014228378,0.00020186415],"study_design_candidate":"not_applicable","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":[0.000035357814,0.00004711311,0.000026837353,0.000027921033,0.0008041657,0.000010436734,0.0000051357574,0.000494279,0.65872014,0.011350439,0.32444313,0.0040350663],"study_design_scores_gemma":[0.00031629635,0.00006520601,0.000019195497,0.000028658927,0.00037995048,0.000013585701,0.000002521957,0.00021526407,0.102961116,0.0018189719,0.8933221,0.000857114],"about_ca_topic_score_codex":0.0000055939827,"about_ca_topic_score_gemma":0.000018688985,"teacher_disagreement_score":0.568879,"about_ca_system_score_codex":0.000029034418,"about_ca_system_score_gemma":0.00008545776,"threshold_uncertainty_score":0.9999956},"labels":[],"label_agreement":null},{"id":"W123725489","doi":"10.1016/b978-0-12-381270-4.00010-x","title":"Probing the Input–Output Behavior of Biochemical and Genetic Systems","year":2010,"lang":"en","type":"review","venue":"Methods in enzymology on CD-ROM/Methods in enzymology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of Toronto","funders":"","keywords":"Computer science; Identification (biology); Cascade; Range (aeronautics); System identification; Control engineering; Measure (data warehouse); Engineering; Data mining; Biology","score_opus":0.05336830734720213,"score_gpt":0.4060034001672452,"score_spread":0.352635092820043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W123725489","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028550975,0.95658964,0.010568933,0.000040014922,0.0018670823,0.00212657,0.000038400736,0.000031516018,0.0001868874],"genre_scores_gemma":[0.0011541931,0.57750493,0.4188232,0.0001094734,0.0005053905,0.0013201777,0.00010859421,0.00020817923,0.00026580715],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9739728,0.019079791,0.002937518,0.0023681624,0.000294042,0.0013476956],"domain_scores_gemma":[0.9925153,0.0029016435,0.0015592722,0.0026240228,0.00017097194,0.00022877002],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":["metaepi_narrow","research_integrity"],"category_scores_codex":[0.008670304,0.0013694462,0.0046980227,0.0012048944,0.00013977004,0.0000381182,0.0017900683,0.004736232,0.000030356277],"category_scores_gemma":[0.0021290192,0.0010891199,0.00085218035,0.0012236113,0.0019287795,0.0000070715814,0.00095258385,0.0028394111,0.0000066585076],"study_design_candidate":"not_applicable","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":[0.00009923698,0.0004657165,0.00075919577,0.002407013,0.00052440277,0.00018633106,0.00014154053,0.00020782618,0.08041608,0.00043196965,0.000266453,0.9140942],"study_design_scores_gemma":[0.0021926195,0.0020904518,0.0048139743,0.0029233573,0.003860627,0.0067820377,0.00019266874,0.0001719803,0.010791257,0.001205247,0.96170795,0.0032678023],"about_ca_topic_score_codex":0.00011722162,"about_ca_topic_score_gemma":0.00018700691,"teacher_disagreement_score":0.9614415,"about_ca_system_score_codex":0.0001557417,"about_ca_system_score_gemma":0.00047091025,"threshold_uncertainty_score":0.99990565},"labels":[],"label_agreement":null},{"id":"W130097263","doi":"10.1007/978-1-4614-3567-9_8","title":"Evolution In Silico: From Network Structure to Bifurcation Theory","year":2012,"lang":"en","type":"article","venue":"Advances in experimental medicine and biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"In silico; Multistability; Computer science; Evolutionary computation; Artificial intelligence; Theoretical computer science; Biology; Physics","score_opus":0.00832615912136602,"score_gpt":0.3039549641456054,"score_spread":0.2956288050242394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W130097263","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":[0.8890854,0.10970631,0.0005655209,0.00008038828,0.00029198642,0.0001072225,0.0000028780632,0.000003697406,0.00015658494],"genre_scores_gemma":[0.9971989,0.0006177854,0.00054396334,0.00046557735,0.000993612,0.000020824138,0.0001387627,0.00000748331,0.000013122726],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99914783,0.0001269033,0.00018414028,0.0002522015,0.00003750764,0.0002514155],"domain_scores_gemma":[0.99969625,0.00002647589,0.00004602499,0.0001509572,0.00000969297,0.00007061524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016322552,0.00011881854,0.00017281128,0.00006550743,0.00002681229,0.0000014307764,0.00007587142,0.00011667116,0.0000408829],"category_scores_gemma":[0.0000345798,0.00009451391,0.000017111654,0.00016810562,0.00011673201,0.000009623672,0.00006913093,0.000056980192,0.0000015246427],"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":[0.00011026694,0.00003104919,0.33288327,0.0000019863235,0.000011233201,2.6474194e-7,0.00027997087,0.000466406,0.659771,0.0010455364,0.000073687064,0.0053253057],"study_design_scores_gemma":[0.0038346334,0.0022033586,0.52404433,0.00017382982,0.000065107655,0.000024994373,0.007426694,0.00028444172,0.36708307,0.018418934,0.07541415,0.0010264091],"about_ca_topic_score_codex":0.000060938622,"about_ca_topic_score_gemma":0.00022187228,"teacher_disagreement_score":0.29268795,"about_ca_system_score_codex":0.000032781674,"about_ca_system_score_gemma":0.000007519041,"threshold_uncertainty_score":0.38541654},"labels":[],"label_agreement":null},{"id":"W1479933963","doi":"10.1007/978-3-642-20389-3_4","title":"Applying Linear Models to Learn Regulation Programs in a Transcription Regulatory Module Network","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science","score_opus":0.03003878729256653,"score_gpt":0.22820197286470192,"score_spread":0.1981631855721354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1479933963","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":[0.014620624,0.0009095149,0.98258007,0.00004738268,0.0003060225,0.0009256765,0.0000014794417,0.000031880514,0.0005773453],"genre_scores_gemma":[0.9127792,0.000059075537,0.08496934,0.00031899274,0.0009914644,0.00008596218,0.00007272057,0.00006608209,0.0006571503],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971899,0.000048389942,0.00047051586,0.0012598912,0.00045463903,0.0005766638],"domain_scores_gemma":[0.99864584,0.000011809333,0.0001701395,0.0008744187,0.00015012916,0.00014768571],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007378005,0.0004114829,0.00040839438,0.00036882292,0.000120482946,0.000061054896,0.00064714556,0.0005164075,0.0000101338],"category_scores_gemma":[0.000007580288,0.00042947926,0.00016957156,0.00046618702,0.00024817468,0.000020386284,0.00026361132,0.00034014328,0.000008458007],"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":[0.0000296323,0.000017255992,0.00015681527,0.000015464373,0.000015101242,0.000003350885,0.00016138586,0.75355226,0.004265026,0.0003074083,0.000012425209,0.24146388],"study_design_scores_gemma":[0.0005662589,0.0005223584,0.00094437355,0.00066867034,0.000063075255,0.000027379494,9.2556405e-7,0.89162976,0.0074313544,0.089110725,0.0075713675,0.0014637521],"about_ca_topic_score_codex":0.000029658158,"about_ca_topic_score_gemma":0.00056242425,"teacher_disagreement_score":0.8981586,"about_ca_system_score_codex":0.0001332385,"about_ca_system_score_gemma":0.00018245225,"threshold_uncertainty_score":0.9998157},"labels":[],"label_agreement":null},{"id":"W1484835433","doi":"10.1017/cbo9780511609077.013","title":"Biology and Value Theory","year":2010,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"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 Guelph","funders":"","keywords":"Statement (logic); Value (mathematics); Epistemology; Naturalism; Value theory; Psychology; Sociology; Computer science; Philosophy","score_opus":0.007864122186034344,"score_gpt":0.19329829585847133,"score_spread":0.18543417367243697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1484835433","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006734105,0.0011560784,0.00096034043,0.000008665798,0.00015786036,0.00017989059,0.00012023235,0.000027531547,0.9906553],"genre_scores_gemma":[0.014281255,0.0004139262,0.00021956694,0.000075236734,0.0003212946,4.639618e-7,0.00019474821,0.00004625551,0.98444724],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99894094,0.00006421889,0.00012195134,0.0005804657,0.00007392708,0.0002184853],"domain_scores_gemma":[0.998985,0.0000187131,0.00014253242,0.00062371313,0.000085007276,0.00014504016],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001350602,0.00030568484,0.00029507506,0.0000903476,0.00013725665,0.000014920717,0.00031030807,0.0008323359,0.000004929279],"category_scores_gemma":[0.000009146991,0.00034653628,0.00019831728,0.0000041079256,0.00047812582,0.0000015456249,0.0004891466,0.0003109408,0.0000041832604],"study_design_candidate":"not_applicable","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":[0.00009428018,0.0000050107724,0.000019172752,0.000024030403,0.0004779039,0.000026833342,0.0000062208696,0.0000031130296,0.038996194,0.95468616,0.003817777,0.0018433002],"study_design_scores_gemma":[0.000291343,0.00006864054,0.000025573889,0.000015325031,0.00034260674,0.000021573502,0.000005992579,0.000010288634,0.010143434,0.00012395046,0.9885756,0.00037566546],"about_ca_topic_score_codex":0.000015759786,"about_ca_topic_score_gemma":0.000003639176,"teacher_disagreement_score":0.98475784,"about_ca_system_score_codex":0.000018433013,"about_ca_system_score_gemma":0.00007130221,"threshold_uncertainty_score":0.9998987},"labels":[],"label_agreement":null},{"id":"W1491629109","doi":"10.1007/978-3-540-24677-0_14","title":"Cell Modeling Using Agent-Based Formalisms","year":2004,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Carleton University","funders":"","keywords":"Rotation formalisms in three dimensions; Computer science; Reusability; Unified Modeling Language; Ode; Ordinary differential equation; Modeling language; Programming language; SBML; Simple (philosophy); Theoretical computer science; Differential equation; Applied mathematics","score_opus":0.013935745496955467,"score_gpt":0.23700987095728707,"score_spread":0.2230741254603316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1491629109","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":[0.021838132,0.0014739332,0.975848,0.000024481793,0.00040769216,0.00016479297,0.0000041721814,0.000015567923,0.00022323449],"genre_scores_gemma":[0.8397572,0.000020089554,0.15820137,0.00066191575,0.00088408747,0.000003933871,0.000091721726,0.000051604406,0.0003280535],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977409,0.000031203253,0.00032032718,0.0009385989,0.00043762417,0.0005313316],"domain_scores_gemma":[0.9987611,0.000014085279,0.00015843728,0.0008050867,0.00014351045,0.00011777296],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00036577502,0.00036341898,0.00030885814,0.00029476362,0.00016710567,0.00010387585,0.0008544175,0.00039219618,0.000006298989],"category_scores_gemma":[0.000015496154,0.00035961668,0.00020404256,0.00037921243,0.00026474262,0.0000073341466,0.00036459023,0.000271393,0.0000033823203],"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":[0.000005320988,0.00001574958,0.000027881806,0.000031557483,0.000009341295,0.000008976298,0.000031513493,0.98587906,0.009525522,0.0000021370415,0.000015369664,0.0044475812],"study_design_scores_gemma":[0.00025629668,0.0000705717,0.0000024558924,0.00010515772,0.00003258575,0.000009952944,1.16614494e-7,0.9555295,0.04194862,0.0011569725,0.00047710357,0.00041066043],"about_ca_topic_score_codex":0.000017201839,"about_ca_topic_score_gemma":0.00004206684,"teacher_disagreement_score":0.8179191,"about_ca_system_score_codex":0.00043005586,"about_ca_system_score_gemma":0.0029363264,"threshold_uncertainty_score":0.99988556},"labels":[],"label_agreement":null},{"id":"W1500240268","doi":"10.1007/11902140_18","title":"Asymptotical Lower Limits on Required Number of Examples for Learning Boolean Networks","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Boolean model; Computer science; Series (stratigraphy); Boolean function; Boolean network; Algorithm; Discrete mathematics; Mathematics","score_opus":0.013347892793487413,"score_gpt":0.24847293969165798,"score_spread":0.23512504689817057,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1500240268","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":[0.008088204,0.00044274097,0.989215,0.0000543719,0.0004116452,0.00023786927,0.00000470103,0.000015742331,0.0015296827],"genre_scores_gemma":[0.9723693,0.00004835552,0.024668355,0.0002674359,0.0012787298,0.000007500938,0.0000862604,0.00006008473,0.0012139418],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977811,0.000034049364,0.00040687466,0.00096189964,0.00036151177,0.000454583],"domain_scores_gemma":[0.9986709,0.00016089309,0.00024782043,0.00063112547,0.00020166424,0.000087603126],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00045136677,0.00036477932,0.00042686865,0.00014367014,0.00011996801,0.000050097526,0.0005775734,0.00050342915,0.000015139712],"category_scores_gemma":[0.000088705354,0.0003443601,0.00026426621,0.0001445877,0.0005152355,0.000004885196,0.00021952114,0.00031452428,0.0000038879984],"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":[0.00006965078,0.00003670067,0.00072741136,0.000025807407,0.000056642548,0.000005672153,0.000013429146,0.9327858,0.0029939609,0.0005818367,0.00023257217,0.0624705],"study_design_scores_gemma":[0.0017697657,0.0027925253,0.0021561487,0.001100677,0.00030061798,0.00007731135,5.9579696e-7,0.8885342,0.03967415,0.021858638,0.038864236,0.002871128],"about_ca_topic_score_codex":0.0000047365984,"about_ca_topic_score_gemma":0.00003761927,"teacher_disagreement_score":0.9645467,"about_ca_system_score_codex":0.000051016694,"about_ca_system_score_gemma":0.00013881507,"threshold_uncertainty_score":0.9999008},"labels":[],"label_agreement":null},{"id":"W1503846774","doi":"10.1007/11540007_31","title":"Dynamic Modeling, Prediction and Analysis of Cytotoxicity on Microelectronic Sensors","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Toxicant; Computer science; Impulse response; Microelectronics; Cytotoxicity; Biological system; System dynamics; Dynamic data; Artificial intelligence; Chemistry; Nanotechnology; Mathematics; Materials science; Biology","score_opus":0.005923594525652127,"score_gpt":0.2211117635306458,"score_spread":0.21518816900499366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1503846774","genre_codex":"methods","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":[0.38668287,0.0010026718,0.61199605,0.000032309654,0.000054705266,0.000107920256,0.000019858184,0.000008191089,0.000095412164],"genre_scores_gemma":[0.99209595,0.00039069494,0.0070631574,0.000107993474,0.000110712055,0.0000017391736,0.000076105636,0.000019047136,0.0001346213],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99822766,0.000023401723,0.00031667284,0.00085566,0.0002984974,0.00027810314],"domain_scores_gemma":[0.9990367,0.000020807569,0.00016992628,0.0005947129,0.000111158064,0.000066688495],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00028805502,0.0002754766,0.0004095856,0.0006788125,0.00007142898,0.000026543343,0.00032123903,0.0003030285,0.000008387735],"category_scores_gemma":[0.000016265385,0.00026585543,0.00019899815,0.0003822391,0.0002897518,0.0000042066,0.00017422668,0.00022635056,8.556537e-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":[0.000015525527,0.000013053838,0.00022158523,0.000007625129,0.00025247084,0.0000010827965,0.000032921995,0.9570365,0.02561514,0.000025092082,0.0000014998813,0.016777506],"study_design_scores_gemma":[0.000102433274,0.00019216533,0.00032992513,0.000033672357,0.00029614862,0.0000057679667,1.1929063e-7,0.9870342,0.011255078,0.00048324023,0.000052556657,0.00021469234],"about_ca_topic_score_codex":0.000008189763,"about_ca_topic_score_gemma":0.0002639566,"teacher_disagreement_score":0.6054131,"about_ca_system_score_codex":0.000106174615,"about_ca_system_score_gemma":0.00012865299,"threshold_uncertainty_score":0.9999794},"labels":[],"label_agreement":null},{"id":"W1512772576","doi":"10.5772/7626","title":"Stochastic Differential Equations With Applications to Biomedical Signal Processing","year":2010,"lang":"en","type":"book-chapter","venue":"InTech eBooks","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"McMaster University","funders":"","keywords":"Stochastic differential equation; Computer science; Signal processing; Applied mathematics; Mathematics; Digital signal processing","score_opus":0.012121365222625203,"score_gpt":0.24558400859446372,"score_spread":0.23346264337183853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1512772576","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":[0.00046365656,0.00012588088,0.9815383,0.0000488615,0.000041044917,0.0005523383,0.000043591222,0.000042060838,0.017144274],"genre_scores_gemma":[0.8479014,0.0000014622284,0.0028415273,0.000106519095,0.0011011271,0.00031250587,0.00044077312,0.00010934963,0.14718534],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985546,0.000009269013,0.00029084572,0.00058486185,0.00030843623,0.00025201548],"domain_scores_gemma":[0.9988646,0.000012953262,0.00016236049,0.0005186879,0.00021404716,0.00022737148],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00006118973,0.00033466436,0.00027503268,0.00018337327,0.00015972921,0.000047430047,0.0003392218,0.00054944376,0.00015170603],"category_scores_gemma":[0.0000075010144,0.00029503184,0.0001465938,0.00002977637,0.0002805764,9.810163e-7,0.00017107066,0.0003782646,0.000055892135],"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":[0.000057870115,0.000034786215,0.0000010655086,0.00003265114,0.0003003419,0.0000035418695,0.000036036014,0.000036276993,0.9430206,0.0010430451,0.0001557078,0.055278078],"study_design_scores_gemma":[0.0008231216,0.0010384021,0.00000841098,0.00044774928,0.0013254147,0.000091898706,0.000032056752,0.0005800437,0.23279333,0.0051010638,0.7557478,0.0020107024],"about_ca_topic_score_codex":0.00000271801,"about_ca_topic_score_gemma":0.00009621034,"teacher_disagreement_score":0.97869676,"about_ca_system_score_codex":0.00002648478,"about_ca_system_score_gemma":0.00027705685,"threshold_uncertainty_score":0.9999502},"labels":[],"label_agreement":null},{"id":"W1523724710","doi":"10.5555/1357910.1358032","title":"A stochastic particle-based biological system simulator","year":2007,"lang":"en","type":"article","venue":"Research Publications (Maastricht University)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; McGill University","funders":"","keywords":"Locality; Computer science; Grid; Particle system; Stochastic simulation; Visualization; Stochastic modelling; Stochastic process; Simulation; Distributed computing; Artificial intelligence; Mathematics; Computer graphics (images)","score_opus":0.05593385731100372,"score_gpt":0.30621120516906364,"score_spread":0.25027734785805994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1523724710","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":[0.7939748,0.00020424122,0.2019248,0.00040489846,0.00003463538,0.00037749106,0.00001761462,0.00011164863,0.0029498388],"genre_scores_gemma":[0.995954,0.0000075699236,0.0005576393,0.000017679144,0.00014786112,0.000004364898,0.00010967308,0.000014812976,0.0031864515],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979881,0.00028351462,0.00019072382,0.0004973568,0.00038945116,0.0006508585],"domain_scores_gemma":[0.9979321,0.00016299868,0.00006955805,0.00069996266,0.0007536107,0.0003817972],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013797752,0.00013063422,0.00013758623,0.0006947117,0.00042831255,0.000053484877,0.00057081884,0.00019224208,0.000039426497],"category_scores_gemma":[0.00033622433,0.00013432188,0.0001302273,0.003107045,0.00025781657,0.0000109704315,0.00022450995,0.00019648223,0.000070931244],"study_design_candidate":"not_applicable","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":[0.001754291,0.0027674062,0.16149187,0.0001593372,0.0016532205,0.00017807928,0.00013569868,0.17426656,0.42760095,0.1715791,0.041346144,0.017067365],"study_design_scores_gemma":[0.005161388,0.0015775246,0.077168904,0.00007063151,0.0002452504,0.00004316661,0.0041191126,0.09445003,0.04936268,0.000079144695,0.7661822,0.0015399653],"about_ca_topic_score_codex":0.000018811013,"about_ca_topic_score_gemma":0.000028069824,"teacher_disagreement_score":0.72483605,"about_ca_system_score_codex":0.00021566926,"about_ca_system_score_gemma":0.00034788979,"threshold_uncertainty_score":0.54774874},"labels":[],"label_agreement":null},{"id":"W1542295728","doi":"10.1007/11428862_19","title":"Modelling Dynamics of Genetic Networks as a Multiscale Process","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Computer science; Process (computing); Task (project management); Nonlinear system; Dynamics (music); Key (lock); Phenomenon; Genetic algorithm; Artificial intelligence; Machine learning; Systems engineering","score_opus":0.007310036151212782,"score_gpt":0.2275702097607649,"score_spread":0.2202601736095521,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1542295728","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":[0.0144694,0.0024507914,0.9821436,0.000043476375,0.00018758953,0.00019247354,0.0000044094204,0.000010817297,0.00049743266],"genre_scores_gemma":[0.92815506,0.0002895263,0.07020763,0.000147238,0.00069680915,0.0000048801935,0.000041722098,0.00004638885,0.0004107345],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978757,0.000016873346,0.0004224505,0.00090487895,0.00038938783,0.00039069555],"domain_scores_gemma":[0.99865633,0.000026082495,0.0002644016,0.0007322928,0.00021817184,0.00010272589],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022198522,0.0003495849,0.00038630018,0.00021227461,0.00008831375,0.000039074184,0.0008293123,0.00044108398,0.000014729652],"category_scores_gemma":[0.00001341704,0.0003461467,0.00016638933,0.00021679632,0.00048558088,0.0000053269073,0.00031446945,0.00028182464,0.000003054883],"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":[0.000009231683,0.000013176206,0.00015012948,0.00001909831,0.00002544214,0.000004421417,0.000034289034,0.9107927,0.0001614212,0.000045979406,0.0000018314657,0.08874226],"study_design_scores_gemma":[0.00013185169,0.000102778205,0.000023511533,0.00010472358,0.000034396362,0.000025070343,1.9411789e-7,0.9940263,0.0014350493,0.0036053085,0.00016322432,0.00034757305],"about_ca_topic_score_codex":0.000014021059,"about_ca_topic_score_gemma":0.00019069051,"teacher_disagreement_score":0.9136857,"about_ca_system_score_codex":0.000072724695,"about_ca_system_score_gemma":0.0002534785,"threshold_uncertainty_score":0.999899},"labels":[],"label_agreement":null},{"id":"W1560917027","doi":"10.1007/978-3-540-74960-8_7","title":"Learning Gene Regulatory Networks via Globally Regularized Risk Minimization","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Cluster analysis; Gene regulatory network; Exploit; Minification; Gene; Computational biology; Expression (computer science); Regulation of gene expression; Data mining; Machine learning; Artificial intelligence; Gene expression; Biology; Genetics","score_opus":0.006672609672264448,"score_gpt":0.21841664766811095,"score_spread":0.2117440379958465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1560917027","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":[0.005498583,0.0024334034,0.9903749,0.000029799916,0.0006173286,0.00025612072,0.000002931905,0.000044856035,0.00074206933],"genre_scores_gemma":[0.7756786,0.0009638438,0.21664603,0.00077553757,0.003373858,0.000007845102,0.00035091277,0.00015896148,0.0020444386],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9964793,0.00009609371,0.0005728198,0.0014658864,0.0007217898,0.0006641105],"domain_scores_gemma":[0.99777126,0.0000596709,0.00054342026,0.0011204586,0.000312586,0.00019258358],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0012747314,0.0005511058,0.0005012678,0.00037918138,0.00031355853,0.0001253793,0.000989634,0.00089969864,0.000025936652],"category_scores_gemma":[0.00009337481,0.0005685988,0.00027282865,0.00043749475,0.0006344707,0.000010859371,0.00063616136,0.00065149454,0.000008555363],"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":[0.00003568738,0.000010995158,0.000480798,0.000006260576,0.000060002094,0.000014791555,0.000024843786,0.73382246,0.0051191635,0.000034987974,0.00003059685,0.2603594],"study_design_scores_gemma":[0.00072401727,0.00040675138,0.0019016404,0.00016341139,0.00017887956,0.00009474244,3.1249692e-7,0.96685696,0.018920777,0.00420763,0.005161127,0.0013837648],"about_ca_topic_score_codex":0.000011824383,"about_ca_topic_score_gemma":0.00011998395,"teacher_disagreement_score":0.7737289,"about_ca_system_score_codex":0.000167084,"about_ca_system_score_gemma":0.0002484527,"threshold_uncertainty_score":0.9996765},"labels":[],"label_agreement":null},{"id":"W1561965943","doi":"10.1023/a:1021064420348","title":"Monotonicity Properties of Chemical Reactions with a Single Initial Bimolecular Step","year":2002,"lang":"en","type":"article","venue":"Journal of Mathematical Chemistry","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of Guelph","funders":"","keywords":"Monotonic function; Mathematics; Mathematical chemistry; Sign (mathematics); Combinatorics; Pure mathematics; Regular polygon; Mathematical analysis; Applied mathematics; Geometry","score_opus":0.01911611410647766,"score_gpt":0.22078229109153746,"score_spread":0.20166617698505981,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1561965943","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":[0.9952612,0.0006788622,0.002500098,0.00008661466,0.000011337278,0.000053147036,0.0000018191948,0.0000045547536,0.0014023592],"genre_scores_gemma":[0.9952441,0.000023928524,0.0043128417,0.000018905295,0.00018773926,0.0000034386717,0.000001923532,0.00002160051,0.00018555246],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987626,0.000029811723,0.0005513947,0.00015338164,0.00032544456,0.00017733237],"domain_scores_gemma":[0.99888295,0.000014888043,0.00040777604,0.0003024781,0.00026078522,0.00013113541],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016974505,0.00015705547,0.00034182385,0.000026694237,0.000024385503,0.000014754165,0.00021646616,0.0001548452,0.00014642812],"category_scores_gemma":[0.0001870801,0.00011577823,0.00022944622,0.00011922329,0.00018524169,0.000006577856,0.000056479414,0.00017224565,0.0000031485781],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008300242,0.0004265077,0.000050679264,0.00019385894,0.00021381084,0.0000124727785,0.000027973447,0.00013550151,0.9984683,0.000008750677,0.00022513456,0.00015401734],"study_design_scores_gemma":[0.00045251756,0.00014965297,0.000004309177,0.00015412389,0.00015364744,0.00049939466,0.000060391692,0.0008728807,0.996861,0.00007666022,0.00058093586,0.00013451272],"about_ca_topic_score_codex":5.108617e-7,"about_ca_topic_score_gemma":1.4130323e-7,"teacher_disagreement_score":0.0018127438,"about_ca_system_score_codex":0.000026345824,"about_ca_system_score_gemma":0.00004517281,"threshold_uncertainty_score":0.4721299},"labels":[],"label_agreement":null},{"id":"W1573181215","doi":"10.1111/j.1365-2249.2007.03472.x","title":"Understanding diseases by mouse click: the promise and potential of computational approaches in Systems Biology","year":2007,"lang":"en","type":"review","venue":"Clinical & Experimental Immunology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"National Institute of Allergy and Infectious Diseases; National Institutes of Health","keywords":"Systems biology; Computational model; Modelling biological systems; Computer science; Intuition; Data science; Computational biology; Biology; Scale (ratio); Management science; Cognitive science; Artificial intelligence; Physics","score_opus":0.1953867810367892,"score_gpt":0.3998127818443249,"score_spread":0.2044260008075357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1573181215","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018618058,0.97958577,0.00083461776,0.000011598712,0.0002468916,0.0005908991,0.00007673816,0.000007461967,0.00002796037],"genre_scores_gemma":[0.21576849,0.7828198,0.000058466845,0.000018665163,0.00015600387,0.000073668234,0.0009970563,0.0000379484,0.000069895446],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9968069,0.00089878176,0.0012380762,0.0006456313,0.00009352108,0.00031707302],"domain_scores_gemma":[0.998717,0.00020837107,0.0005599333,0.00041838302,0.00002353106,0.00007277809],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00052235596,0.00034182557,0.0013027344,0.000102993225,0.00007901189,0.000018330766,0.00036767503,0.0007374944,0.0000075684898],"category_scores_gemma":[0.000052723888,0.00025101466,0.00045903213,0.00014238791,0.0012706565,0.0000033404638,0.00039177042,0.0002945236,0.0000025912248],"study_design_candidate":"not_applicable","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":[0.0047848974,0.020559827,0.016252723,0.015089741,0.04824289,0.00015635467,0.00067888433,0.0056983465,0.04446932,0.024699187,0.016811777,0.80255604],"study_design_scores_gemma":[0.011027188,0.007197223,0.0005714076,0.0030604673,0.004699739,0.00056872255,0.0055493102,0.0022434948,0.0025384193,0.0008237906,0.9573432,0.0043770457],"about_ca_topic_score_codex":0.000013743854,"about_ca_topic_score_gemma":0.0000021062465,"teacher_disagreement_score":0.94053143,"about_ca_system_score_codex":0.00007216088,"about_ca_system_score_gemma":0.00013415432,"threshold_uncertainty_score":0.9999942},"labels":[],"label_agreement":null},{"id":"W1576327587","doi":"10.1109/cec.2003.1299556","title":"Transcription and evolution of a virtual bacteria culture","year":2003,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"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 Calgary","funders":"","keywords":"Gene; Bacteria; Genome; Transcription (linguistics); Bacterial genome size; Synthetic biology; Inheritance (genetic algorithm); Computational biology; DNA; Genetics; Biology; Computer science","score_opus":0.004545600038504772,"score_gpt":0.19848140615571552,"score_spread":0.19393580611721076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1576327587","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":[0.9895764,0.00082818116,0.008480972,0.000009068668,0.000030473571,0.000037299764,0.0000017871494,0.0000032778685,0.0010325677],"genre_scores_gemma":[0.9976478,0.00008486325,0.00089739374,0.000014856269,0.000026904212,0.0000019066064,0.000015905804,0.000004418315,0.0013059562],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99964076,0.00003821206,0.00008596334,0.00012558009,0.000042289543,0.0000671967],"domain_scores_gemma":[0.9998048,7.139586e-7,0.000025737945,0.00010614516,0.00003411052,0.000028487528],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000066282715,0.000055731925,0.00006700796,0.000016740658,0.000019456742,0.0000036980596,0.000025492332,0.0000766632,0.000031847136],"category_scores_gemma":[0.000008719021,0.000048019752,0.000043562042,0.00005337287,0.000031585532,0.000001446968,0.000005942546,0.00001618514,9.814469e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010522692,0.000012832592,0.0026502907,0.000003457323,0.000030633448,5.971785e-8,0.0000207791,0.000045100078,0.9949182,0.0016558926,0.0003725075,0.00027969276],"study_design_scores_gemma":[0.00046721377,0.00028108273,0.016589245,0.0000047901763,0.000067340414,0.000013430139,0.00026507818,0.00012257481,0.95657307,0.00022118229,0.025246954,0.0001480482],"about_ca_topic_score_codex":0.0000041181706,"about_ca_topic_score_gemma":0.00002078565,"teacher_disagreement_score":0.038345173,"about_ca_system_score_codex":0.0000053745225,"about_ca_system_score_gemma":0.000015782063,"threshold_uncertainty_score":0.19581887},"labels":[],"label_agreement":null},{"id":"W1586768443","doi":"10.20381/ruor-5079","title":"A Framework for Individual-based Simulation of Heterogeneous Cell Populations","year":2011,"lang":"en","type":"dissertation","venue":"Library and Archives Canada (Government of Canada)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Data science","score_opus":0.008163844522928617,"score_gpt":0.19251853760876064,"score_spread":0.18435469308583202,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1586768443","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":[0.9731225,0.0025551144,0.007115524,0.000096932556,0.00044881456,0.00070062693,0.0013202581,0.000006884609,0.014633367],"genre_scores_gemma":[0.9894254,0.000041056715,0.005674183,0.00013323486,0.00007278601,0.000019992538,0.0012009825,0.000038758513,0.0033935963],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985285,0.00004115979,0.00034710864,0.00027813728,0.0006212491,0.00018385977],"domain_scores_gemma":[0.9991129,0.000070620925,0.0004287069,0.0002713837,0.000002596148,0.000113768045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000009314477,0.00020982546,0.0002745554,0.000032207372,0.000090069145,0.0000072207645,0.00018478198,0.00012772897,0.000018285087],"category_scores_gemma":[0.000005526048,0.00022873285,0.0000988571,0.00005544769,0.000027236096,0.000006371876,0.000033631182,0.000071220355,5.303087e-10],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007904861,0.0005040259,0.05659218,0.0053652185,0.0025227852,0.000024971794,0.00042335907,0.55969405,0.31398484,0.02539841,0.0018164731,0.02576881],"study_design_scores_gemma":[0.00042531046,0.0002324577,0.01591133,0.00016471696,0.00036203515,5.202991e-7,0.0004463807,0.011031332,0.9630034,0.0027872375,0.0051625124,0.0004727945],"about_ca_topic_score_codex":0.00037223686,"about_ca_topic_score_gemma":0.02428414,"teacher_disagreement_score":0.6490185,"about_ca_system_score_codex":0.0000021806784,"about_ca_system_score_gemma":0.0011379645,"threshold_uncertainty_score":0.99352014},"labels":[],"label_agreement":null},{"id":"W1587083828","doi":"10.1186/1742-4682-11-52","title":"Mathematical and computational modeling in biology at multiple scales","year":2014,"lang":"en","type":"review","venue":"Theoretical Biology and Medical Modelling","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Cancer Foundation","keywords":"Modelling biological systems; Inference; Computational model; Statistical physics; Systems biology; Mathematical and theoretical biology; Computer science; Mathematical model; Principle of maximum entropy; Computational biology; Biology; Physics; Bioinformatics; Artificial intelligence; Quantum mechanics","score_opus":0.02425712162420793,"score_gpt":0.3150270675019453,"score_spread":0.29076994587773736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1587083828","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00834248,0.68241346,0.3088825,0.000051027248,0.00003713492,0.00017263455,0.000012049862,0.000010799699,0.000077923745],"genre_scores_gemma":[0.22190794,0.7749591,0.0023066138,0.000093647934,0.00022333075,0.0000325639,0.0004378894,0.000031409305,0.000007488041],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973087,0.000575045,0.0007339266,0.00081555615,0.00011475562,0.00045207446],"domain_scores_gemma":[0.9987268,0.0005405244,0.00010910267,0.00025833154,0.000035006404,0.00033024192],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0011106511,0.00039751455,0.0013613881,0.00011605905,0.00010013186,0.0000097457405,0.00022577484,0.0014701135,0.000049585702],"category_scores_gemma":[0.00036721546,0.00029569922,0.00020926062,0.00008596724,0.00154498,0.0000016419418,0.0004571684,0.000413166,0.000012605744],"study_design_candidate":"simulation_or_modeling","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":[0.000104230654,0.00013440225,0.00029146872,0.0031575733,0.00046077376,0.000011035363,0.000027930111,0.017493024,0.000020104213,0.59801084,0.000017575438,0.38027102],"study_design_scores_gemma":[0.0003378101,0.00008897831,2.9505998e-7,0.0008628315,0.00015765183,0.00009653487,0.000003066405,0.8465063,0.000001706694,0.1346562,0.016951673,0.00033692882],"about_ca_topic_score_codex":0.0000024042615,"about_ca_topic_score_gemma":0.000011223181,"teacher_disagreement_score":0.8290133,"about_ca_system_score_codex":0.000022212787,"about_ca_system_score_gemma":0.000079935366,"threshold_uncertainty_score":0.9999495},"labels":[],"label_agreement":null},{"id":"W1589757760","doi":"10.1002/9783527622818.ch7","title":"A Model of Genetic Networks with Delayed Stochastic Dynamics","year":2008,"lang":"en","type":"other","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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 Calgary","funders":"","keywords":"Stochastic modelling; Stochastic dynamics; Computer science; Gene regulatory network; Stochastic process; Expression (computer science); Dynamics (music); Event (particle physics); Gene; Gene expression; Biology; Statistical physics; Mathematics; Genetics; Physics; Statistics","score_opus":0.00579741088619968,"score_gpt":0.19581886054830985,"score_spread":0.19002144966211018,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1589757760","genre_codex":"methods","genre_gemma":"other","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":[0.0024094463,0.0034151578,0.93439233,0.000005862226,0.00004105707,0.00025784617,0.000044768003,0.00003590817,0.059397645],"genre_scores_gemma":[0.31370747,0.001379187,0.02700496,0.000103032566,0.00043485028,0.00003717098,0.00074044184,0.00089765363,0.6556952],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99878407,0.00002830564,0.00024818155,0.0004709742,0.00018672612,0.00028172272],"domain_scores_gemma":[0.9988249,0.0000034243012,0.0002597205,0.00074959226,0.00006537036,0.00009697582],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00003174744,0.00034471095,0.00041096864,0.00011696322,0.000025100577,0.0000049539867,0.00026272857,0.0005006333,0.000107735534],"category_scores_gemma":[0.0000034031414,0.00029111636,0.00016814707,0.00014234423,0.00015580172,4.061275e-7,0.000091325244,0.0000987866,0.0000042070938],"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":[0.000048174497,0.000037206322,0.00012610373,0.000016484952,0.0007106368,0.0000027595634,0.0000028258046,0.91438204,0.00028327713,0.000019700474,0.08398577,0.00038501757],"study_design_scores_gemma":[0.00039711015,0.00021368479,0.00002289226,0.00004101642,0.00033067024,0.000028830667,0.000007229164,0.9959922,0.00006406544,0.0000072336848,0.0024286828,0.00046637436],"about_ca_topic_score_codex":0.00007346801,"about_ca_topic_score_gemma":0.0020393815,"teacher_disagreement_score":0.9073874,"about_ca_system_score_codex":0.000018231884,"about_ca_system_score_gemma":0.00014363843,"threshold_uncertainty_score":0.9999541},"labels":[],"label_agreement":null},{"id":"W1590610492","doi":"10.3233/978-1-60750-072-8-11","title":"The influence of noise on the dynamics of Random Boolean Network","year":2009,"lang":"en","type":"book-chapter","venue":"Frontiers in artificial intelligence and applications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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 Calgary","funders":"","keywords":"Dynamics (music); Boolean network; Random noise; Noise (video); Computer science; Statistical physics; Psychology; Physics; Boolean function; Artificial intelligence; Algorithm","score_opus":0.010560060565249916,"score_gpt":0.23233402610965598,"score_spread":0.22177396554440607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1590610492","genre_codex":"methods","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":[0.08529887,0.049075574,0.7298711,0.006035082,0.00080830575,0.008667566,0.00038113774,0.00005421977,0.11980815],"genre_scores_gemma":[0.96322125,0.014480576,0.0009166817,0.0002200937,0.0005151161,0.00014545562,0.00014068349,0.000046359204,0.0203138],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989665,0.000029826604,0.00047047113,0.00025748136,0.00012711032,0.00014856679],"domain_scores_gemma":[0.9989364,0.00006315676,0.0002983269,0.00057480007,0.00009547178,0.00003182552],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031217778,0.00016278241,0.0002418663,0.00004455571,0.00014531598,0.000013655816,0.0003552986,0.00017838641,0.0000034344184],"category_scores_gemma":[0.00002298432,0.000114689974,0.00012789204,0.00009429578,0.00048752976,0.0000016185062,0.000055915745,0.00015731964,0.0000021991546],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023322062,0.00005173957,0.00029166348,0.000019391238,0.00021820283,3.660359e-7,0.000043202872,0.13195306,0.00078217534,0.5098331,0.0030185385,0.35355532],"study_design_scores_gemma":[0.0001142306,0.00032424225,0.00042549532,0.00026501899,0.00034425413,0.0000024570497,0.00042951215,0.01973223,0.011455774,0.7871342,0.17908698,0.00068564835],"about_ca_topic_score_codex":0.0000061307205,"about_ca_topic_score_gemma":0.00015069514,"teacher_disagreement_score":0.87792236,"about_ca_system_score_codex":0.000015411184,"about_ca_system_score_gemma":0.000044947832,"threshold_uncertainty_score":0.46769214},"labels":[],"label_agreement":null},{"id":"W1624196052","doi":"","title":"Minimal models of biological structures","year":2001,"lang":"en","type":"dissertation","venue":"Library and Archives Canada (Government of Canada)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computational biology; Computer science; Biology","score_opus":0.0044230273986638514,"score_gpt":0.16163992890602571,"score_spread":0.15721690150736187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1624196052","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":[0.90614825,0.0024933727,0.000030579104,0.00008502959,0.00013406182,0.00010645479,0.00018856804,0.0000021864491,0.09081152],"genre_scores_gemma":[0.983099,0.0009848253,0.00047677118,0.000114801,0.00009882147,0.000004454075,0.00041920226,0.000021996033,0.0147801405],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984147,0.000049494207,0.0003150212,0.00030744428,0.0007070304,0.00020629127],"domain_scores_gemma":[0.99933904,0.000025254569,0.0002699578,0.00023291353,0.0000012108534,0.00013160393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000064009805,0.00022612885,0.00033636997,0.000020495925,0.00005733102,0.000005686559,0.00022963063,0.00011689581,0.000028438033],"category_scores_gemma":[0.0000021155417,0.00020696012,0.00007461902,0.00005241887,0.000057554073,0.00000694596,0.000072199626,0.00008680934,3.0033565e-10],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030608128,0.000070478396,0.016786633,0.0005916989,0.0012646548,0.000059551825,0.00008526516,0.004437067,0.92477846,0.027494177,0.0036465046,0.017724719],"study_design_scores_gemma":[0.0003554285,0.00021848432,0.03729857,0.00008535048,0.00012385081,0.0000075020844,0.002070882,0.0011240838,0.94153214,0.0037682033,0.012889438,0.00052607147],"about_ca_topic_score_codex":0.0006089336,"about_ca_topic_score_gemma":0.024403432,"teacher_disagreement_score":0.07695076,"about_ca_system_score_codex":0.0000018580934,"about_ca_system_score_gemma":0.0010548118,"threshold_uncertainty_score":0.99339867},"labels":[],"label_agreement":null},{"id":"W1631958718","doi":"","title":"Infrafrontier - Mouse models and phenotyping data for the European biomedical research community","year":2009,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Czech; Political science; European community; European Research Area; Library science; European union; Regional science; Public administration; Business; Geography; Computer science; International trade","score_opus":0.11930126466389192,"score_gpt":0.35327782804899527,"score_spread":0.23397656338510336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1631958718","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":[0.500287,0.005991112,0.47831544,0.0036412072,0.00008030534,0.0006894865,0.00009494361,0.00004401303,0.010856494],"genre_scores_gemma":[0.99441165,0.00029233348,0.0031603053,0.00032863783,0.00025628367,0.0000034773266,0.00039260165,0.000013673462,0.0011410167],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987513,0.0005117345,0.00013278522,0.00023046063,0.00013959785,0.00023411443],"domain_scores_gemma":[0.99839133,0.00005629363,0.000023472861,0.0013662858,0.00008502444,0.000077621735],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029900705,0.00008167715,0.00008681838,0.000035402023,0.0004467947,0.000047375273,0.0007503029,0.000059219015,0.0000055726437],"category_scores_gemma":[0.00011090873,0.00005572578,0.000032790675,0.000103961844,0.00019120067,0.0000053987346,0.0006414045,0.00017450257,0.0000018081697],"study_design_candidate":"not_applicable","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":[0.00015534736,0.000350826,0.00028251891,0.000030504303,0.0004936707,0.0000015353065,0.0003681762,0.0018046303,0.24381948,0.0011291556,0.50262964,0.24893452],"study_design_scores_gemma":[0.0017316246,0.00066921784,0.0034036776,0.000020972864,0.00019526477,0.000015244896,0.0021452045,0.55675846,0.009177284,0.006610216,0.41865104,0.00062180724],"about_ca_topic_score_codex":0.000036744615,"about_ca_topic_score_gemma":0.000054667995,"teacher_disagreement_score":0.5549538,"about_ca_system_score_codex":0.000004422811,"about_ca_system_score_gemma":0.000028124226,"threshold_uncertainty_score":0.34364286},"labels":[],"label_agreement":null},{"id":"W1651300744","doi":"","title":"Utility Based State Learning for Controlling Partially Observable Gene Regulatory Networks","year":2013,"lang":"en","type":"article","venue":"Infoscience (Ecole Polytechnique Fédérale de Lausanne)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Calgary","funders":"","keywords":"Partially observable Markov decision process; Observable; Reinforcement learning; Computer science; Markov decision process; Markov process; State (computer science); Gene regulatory network; Process (computing); Control (management); Construct (python library); Artificial intelligence; Markov chain; Markov model; Machine learning; Gene; Mathematics; Algorithm; Gene expression; Biology","score_opus":0.011077210890475623,"score_gpt":0.23292240072500847,"score_spread":0.22184518983453286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1651300744","genre_codex":"methods","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":[0.49559253,0.0004160809,0.50258845,0.00015097394,0.0001009153,0.00086115213,0.000008764718,0.000118897435,0.00016221331],"genre_scores_gemma":[0.9741125,0.00007228764,0.022522185,0.0009118001,0.00024247856,0.0006368855,0.000085841595,0.000050058905,0.0013659606],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99716187,0.00019517669,0.0005552747,0.0007563428,0.00027269058,0.0010586656],"domain_scores_gemma":[0.99815285,0.00007748937,0.0003121749,0.00079858035,0.00033346363,0.00032544427],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0012496515,0.0003363913,0.0003795229,0.00011217645,0.00042732517,0.00016124875,0.00063522044,0.00032614617,0.000075810065],"category_scores_gemma":[0.00024196651,0.0003596212,0.00029999856,0.00040654998,0.00028255046,0.000041290445,0.00015782702,0.00024186369,0.000009489202],"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":[0.0001054959,0.00008164845,0.04288846,0.000025213007,0.00005255034,0.0000025287784,0.000023131557,0.34493464,0.59929776,0.000043168067,0.0030600775,0.009485295],"study_design_scores_gemma":[0.00047129663,0.00023388086,0.012966318,0.000027743981,0.000033494256,0.0000042216584,0.000016772747,0.5674414,0.41115943,0.00021675804,0.007036658,0.00039202446],"about_ca_topic_score_codex":0.00012948336,"about_ca_topic_score_gemma":0.00015696706,"teacher_disagreement_score":0.48006627,"about_ca_system_score_codex":0.000056995465,"about_ca_system_score_gemma":0.00034450754,"threshold_uncertainty_score":0.99988556},"labels":[],"label_agreement":null},{"id":"W1685940597","doi":"10.1139/p2012-091","title":"What all the noise is about: the physical basis of cellular individuality","year":2012,"lang":"en","type":"article","venue":"Canadian Journal of Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Physics; Noise (video); Distortion (music); Basis (linear algebra); Field (mathematics); Statistical physics; Data science; Computer science; Artificial intelligence","score_opus":0.01762555731855802,"score_gpt":0.24074991841944965,"score_spread":0.22312436110089162,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1685940597","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":[0.99343145,0.0047497256,0.00036836165,0.0009773591,0.0003069364,0.00005913672,0.000019767702,6.0726865e-7,0.00008665982],"genre_scores_gemma":[0.9972442,0.00012868231,0.000032214986,0.00075217336,0.0017104557,0.000001347076,0.000009691659,0.00001564035,0.000105605584],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990123,0.00014577992,0.00023655753,0.00009390878,0.00020419782,0.00030724905],"domain_scores_gemma":[0.9987564,0.000024251869,0.00030090145,0.00043975931,0.0001768318,0.00030183018],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047042835,0.00012678024,0.00019486142,0.000024758785,0.00011340331,0.000045966157,0.000454505,0.00006475388,0.000022461492],"category_scores_gemma":[0.000024468187,0.00007818027,0.0003500863,0.00016254545,0.00021578377,0.000019961753,0.0000348473,0.00016426224,0.0000048385277],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009524623,0.0006108357,0.15008232,0.00013230083,0.0070936405,0.000023654791,0.030480903,0.006339668,0.58433527,0.0060342117,0.12824346,0.08652852],"study_design_scores_gemma":[0.0004412084,0.00016588837,0.029887035,0.00005356041,0.00097585376,0.000030595358,0.0017641125,0.00018905988,0.7956102,0.0014013271,0.16911264,0.00036854774],"about_ca_topic_score_codex":0.00025097278,"about_ca_topic_score_gemma":0.0004851227,"teacher_disagreement_score":0.21127494,"about_ca_system_score_codex":0.000026434418,"about_ca_system_score_gemma":0.00033729605,"threshold_uncertainty_score":0.31880987},"labels":[],"label_agreement":null},{"id":"W1714157926","doi":"10.1142/9789811285073_0008","title":"Boolean Gates on Actin Filaments","year":2024,"lang":"en","type":"book-chapter","venue":"WORLD SCIENTIFIC eBooks","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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 Alberta","funders":"","keywords":"Protein filament; Actin; Filamin; Physics; Cytoskeleton; Computer science; Cell biology; Biology; Cell; Genetics","score_opus":0.015056180066544885,"score_gpt":0.23592931165231487,"score_spread":0.22087313158577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1714157926","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0030628121,0.001282978,0.00000643101,0.000086550004,0.0017966249,0.0002535011,0.00007229774,0.00005615662,0.99338263],"genre_scores_gemma":[0.049760953,0.000005442494,0.000063515436,0.00015096972,0.000658532,0.000015158291,0.00043031594,0.00011784623,0.9487973],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974248,0.00002055517,0.00036550144,0.0012894686,0.00049898244,0.00040069083],"domain_scores_gemma":[0.99829006,0.000012432928,0.00017804245,0.0012534909,0.00008968303,0.00017631357],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003469046,0.00047618223,0.0003413618,0.00044375056,0.00024381587,0.00027937914,0.0004606388,0.00027642143,0.00045940184],"category_scores_gemma":[0.000005101525,0.0004552635,0.00048116938,0.000057106,0.00034986806,0.0000012817977,0.00029920647,0.00033577424,0.0013192906],"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":[0.00009537642,0.000044692715,0.00002594425,0.00015070586,0.0013752142,0.00009504672,0.00010132316,0.00026489398,0.12850976,0.042757757,0.8161756,0.010403716],"study_design_scores_gemma":[0.00009974457,0.00004865764,0.000004162735,0.00019844317,0.00018007446,0.0000052994483,0.000005571221,0.000025589854,0.028826997,0.0047398168,0.96542376,0.00044190596],"about_ca_topic_score_codex":0.0000010632849,"about_ca_topic_score_gemma":0.00047996518,"teacher_disagreement_score":0.14924817,"about_ca_system_score_codex":0.000061393126,"about_ca_system_score_gemma":0.00011652063,"threshold_uncertainty_score":0.9997899},"labels":[],"label_agreement":null},{"id":"W1721844931","doi":"10.3233/isb-00080","title":"Making the Body Plan: Precision in the Genetic Hierarchy of Drosophila Embryo Segmentation","year":2003,"lang":"en","type":"article","venue":"In Silico Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"British Columbia Institute of Technology; University of British Columbia","funders":"National Center for Research Resources; National Institutes of Health; Russian Foundation for Basic Research","keywords":"Body plan; Drosophila (subgenus); Segmentation; Embryo; Hierarchy; Plan (archaeology); Biology; Artificial intelligence; Computer science; Genetics; Computational biology; Gene; Political science","score_opus":0.018567085991747646,"score_gpt":0.28818259150258935,"score_spread":0.2696155055108417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1721844931","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":[0.9963184,0.002538247,0.00022914461,0.0001547101,0.00007954754,0.00022992774,0.0000036324925,0.0000021462897,0.00044425353],"genre_scores_gemma":[0.99910045,0.00020103688,0.00027260024,0.00024632775,0.00006912984,0.000038705395,0.00003510362,0.000008826209,0.000027828133],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9984281,0.0006898097,0.00031596015,0.00027187826,0.0000826558,0.00021157115],"domain_scores_gemma":[0.9993475,0.00008411422,0.00010908946,0.00042024598,0.000025235418,0.000013802869],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058962,0.000115424,0.00015268663,0.00007781555,0.00004301333,0.0000074531767,0.00029892928,0.00015529015,0.000014412809],"category_scores_gemma":[0.00009302211,0.00007272477,0.00007240328,0.0002651678,0.00013783861,0.0000017147485,0.000053322077,0.00010252197,0.0000028630693],"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":[0.000058623737,0.000083091334,0.22479679,0.000008492645,0.000035681176,0.0000028802913,0.0003258359,0.003695339,0.7659837,0.0005898048,0.00025390324,0.0041658683],"study_design_scores_gemma":[0.001909604,0.0008389419,0.76037073,0.00004695867,0.00007962675,0.000114543625,0.0011863383,0.0015485962,0.20533052,0.008905641,0.019147322,0.00052117725],"about_ca_topic_score_codex":0.000018682496,"about_ca_topic_score_gemma":0.00014129427,"teacher_disagreement_score":0.56065315,"about_ca_system_score_codex":0.00001445268,"about_ca_system_score_gemma":0.00003769453,"threshold_uncertainty_score":0.296563},"labels":[],"label_agreement":null},{"id":"W1735708642","doi":"10.1139/cjp-2013-0146","title":"Exponential state estimation for discrete-time switched genetic regulatory networks with random delays","year":2013,"lang":"en","type":"article","venue":"Canadian Journal of Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Estimator; Dwell time; Piecewise; Bernoulli's principle; Discrete time and continuous time; State (computer science); Control theory (sociology); Set (abstract data type); Class (philosophy); Exponential stability; Applied mathematics; Mathematical optimization; Computer science; Mathematics; Physics; Algorithm; Nonlinear system; Control (management); Statistics","score_opus":0.0038104011451417495,"score_gpt":0.1853797393066455,"score_spread":0.18156933816150375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1735708642","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":[0.6647967,0.00053050404,0.33428523,0.000048208483,0.00010634405,0.000206327,0.0000078903195,0.0000021556343,0.000016643142],"genre_scores_gemma":[0.992514,0.000014646335,0.00631344,0.00007782491,0.0007581998,0.000016264254,0.00006536581,0.000042010593,0.0001982463],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998974,0.00005383828,0.00032153164,0.00017846408,0.00012941605,0.00034274036],"domain_scores_gemma":[0.99844545,0.000015220122,0.00031262188,0.0002648363,0.00052683003,0.00043505398],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014875078,0.00017489385,0.00026218258,0.000060674472,0.00012278742,0.00006662679,0.0001959026,0.00008705431,0.00003091839],"category_scores_gemma":[0.000028582122,0.0001519857,0.00019678484,0.00011641777,0.000095011,0.000016722095,0.000011201715,0.00009011117,0.000005652825],"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":[0.00017372801,0.000017494955,0.002055105,0.000016180002,0.00057644275,0.0000080559485,0.00007742855,0.94138384,0.029526675,0.000014857153,0.011207258,0.0149429375],"study_design_scores_gemma":[0.015955552,0.0030962084,0.045450397,0.00028267037,0.0020652872,0.00024413757,0.00022550793,0.80077535,0.11379337,0.005815168,0.009849636,0.0024467024],"about_ca_topic_score_codex":0.000219027,"about_ca_topic_score_gemma":0.00090569234,"teacher_disagreement_score":0.3279718,"about_ca_system_score_codex":0.000049248498,"about_ca_system_score_gemma":0.00054780155,"threshold_uncertainty_score":0.6197797},"labels":[],"label_agreement":null},{"id":"W1759632117","doi":"10.1186/1471-2105-5-24","title":"Biochemical Network Stochastic Simulator (BioNetS): software for stochastic modeling of biochemical networks","year":2004,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":150,"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":"Defense Advanced Research Projects Agency; Alfred P. Sloan Foundation","keywords":"Computer science; Software; Stochastic modelling; Simulation; Programming language; Mathematics; Statistics","score_opus":0.014494119066310335,"score_gpt":0.2385294678884628,"score_spread":0.22403534882215245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1759632117","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":[0.10592682,0.0015310858,0.8916488,0.000018412395,0.00019507595,0.0005731362,0.000047149755,0.000048194823,0.0000113004735],"genre_scores_gemma":[0.8171256,0.000018880588,0.18129806,0.000112954614,0.0006530909,0.000048745507,0.0006631977,0.00006098139,0.000018455876],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99749905,0.000024361894,0.0010071751,0.00041245163,0.0003131906,0.00074374746],"domain_scores_gemma":[0.9981485,0.00007822763,0.0003675139,0.0007660353,0.00037588287,0.0002638216],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00034099154,0.00043074266,0.0005423443,0.00009629676,0.00015534475,0.00003463341,0.00045642658,0.0005407029,0.0000065065838],"category_scores_gemma":[0.00037540917,0.0004249114,0.00043528716,0.00043139458,0.00018554073,0.000013573529,0.0002542519,0.00017282882,0.0000071971363],"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":[0.00018226035,0.00007103666,0.000053125794,0.00012963286,0.00015837372,1.5414409e-7,0.000036160513,0.99629843,0.0016683625,0.00010536245,0.001102866,0.00019423691],"study_design_scores_gemma":[0.001534383,0.00021645366,0.000014030765,0.00011582637,0.00022583155,0.000013850993,0.00007293726,0.994579,0.0022143826,0.00045697132,0.0000722149,0.00048412778],"about_ca_topic_score_codex":0.0000053231324,"about_ca_topic_score_gemma":0.000007634624,"teacher_disagreement_score":0.7111988,"about_ca_system_score_codex":0.00006437252,"about_ca_system_score_gemma":0.00029420038,"threshold_uncertainty_score":0.9998203},"labels":[],"label_agreement":null},{"id":"W1776383313","doi":"10.1016/j.bpj.2015.08.024","title":"Critical Timing without a Timer for Embryonic Development","year":2015,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Morphogen; Multistability; Timer; Criticality; Computer science; Simple (philosophy); Sonic hedgehog; Interpretation (philosophy); Expression (computer science); Process (computing); Biological system; Biology; Physics; Gene; Genetics","score_opus":0.029826799469264923,"score_gpt":0.2988783880335528,"score_spread":0.2690515885642879,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1776383313","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":[0.9550269,0.00024863967,0.043667495,0.0004471517,0.00026197554,0.00009413349,0.000002879276,0.000010869583,0.00023991555],"genre_scores_gemma":[0.9829682,0.0000053892027,0.014619893,0.00016497924,0.0015483561,0.000012651388,0.000016767939,0.000024439687,0.00063933595],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990186,0.000046472695,0.00019566971,0.00022132424,0.00020711786,0.00031081613],"domain_scores_gemma":[0.9991759,0.000012801522,0.000061593695,0.00016169735,0.000260099,0.0003279172],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025223353,0.00013776303,0.00017113776,0.00003447427,0.00013391784,0.000058094945,0.00016723144,0.00009205895,0.000010049417],"category_scores_gemma":[0.00013136798,0.0001172695,0.0001680984,0.00006820707,0.00006983104,0.000005252131,0.000069371854,0.000099485034,0.00003112141],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020394265,0.00018437515,0.001033024,0.000013449889,0.0002885946,0.000008135945,0.000070535774,0.00040800992,0.97651505,0.0001892478,0.014070809,0.0070148013],"study_design_scores_gemma":[0.0026243124,0.0009887328,0.0024004083,0.000055184933,0.00034025364,0.00035159566,0.00020194724,0.007217588,0.6574736,0.00053976104,0.32684308,0.00096349104],"about_ca_topic_score_codex":3.8114501e-7,"about_ca_topic_score_gemma":0.0000012404613,"teacher_disagreement_score":0.31904143,"about_ca_system_score_codex":0.00003794805,"about_ca_system_score_gemma":0.0002550902,"threshold_uncertainty_score":0.47821113},"labels":[],"label_agreement":null},{"id":"W1821013472","doi":"10.1139/p2012-088","title":"Robust stabilization and <i>H</i><sub>∞</sub> control for discrete-time stochastic genetic regulatory networks with time delays","year":2012,"lang":"en","type":"article","venue":"Canadian Journal of Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Upper and lower bounds; Discrete time and continuous time; Bounded function; Interval (graph theory); Linear matrix inequality; Controller (irrigation); Robust control; Physics; Applied mathematics; Computer science; Mathematical optimization; Control (management); Mathematics; Nonlinear system; Mathematical analysis","score_opus":0.005030671084065057,"score_gpt":0.17101543213511122,"score_spread":0.16598476105104618,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1821013472","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":[0.6565526,0.0023472942,0.34080496,0.000030071782,0.000065943444,0.00016523385,0.000022939243,0.0000021831916,0.000008785854],"genre_scores_gemma":[0.99771506,0.000017570479,0.00085457717,0.000107022555,0.0011728083,0.000006974491,0.00005081297,0.000048993803,0.00002618385],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989529,0.00006545723,0.00026332593,0.00017056025,0.00011746082,0.00043029286],"domain_scores_gemma":[0.9986093,0.00002585391,0.0002646379,0.0002240002,0.00026394584,0.00061226496],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023516046,0.00018981655,0.00027311928,0.00005780673,0.00013879797,0.000035202153,0.00012470993,0.000118130294,0.0000057043676],"category_scores_gemma":[0.000026420928,0.00017316382,0.00012106201,0.00012400786,0.0001387287,0.000018364435,0.00001108488,0.000091561305,0.0000019148601],"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":[0.00012733485,0.000024589837,0.0061711273,0.000017831593,0.0004944379,0.0000032192543,0.00007080138,0.9071492,0.07954563,0.000048589394,0.0020642187,0.004283044],"study_design_scores_gemma":[0.016057478,0.0057255365,0.09631045,0.0005633029,0.008261402,0.0012001902,0.00036459317,0.72888273,0.13028966,0.0011105007,0.006443489,0.004790647],"about_ca_topic_score_codex":0.000013505749,"about_ca_topic_score_gemma":0.0003095393,"teacher_disagreement_score":0.34116247,"about_ca_system_score_codex":0.000056853827,"about_ca_system_score_gemma":0.00040336928,"threshold_uncertainty_score":0.70614153},"labels":[],"label_agreement":null},{"id":"W182431899","doi":"10.1007/978-3-642-19621-8_4","title":"Biological Limits of Hand Preference Learning Hiding Behind the Genes","year":2011,"lang":"en","type":"book-chapter","venue":"Intelligent systems reference library","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Preference; Artificial intelligence; Stability (learning theory); Adaptive behavior; Limit (mathematics); Process (computing); Computer science; Machine learning; Psychology; Mathematics; Social psychology","score_opus":0.09377259991948493,"score_gpt":0.24040572619782294,"score_spread":0.14663312627833802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W182431899","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":[0.16132115,0.1879159,0.0034109927,0.00009594259,0.0015866396,0.0021781183,0.00023052475,0.00019244419,0.6430683],"genre_scores_gemma":[0.73903024,0.012999292,0.000053430656,0.000023204748,0.00051051116,0.000032508135,0.00044448624,0.00008278072,0.24682355],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974609,0.00021556577,0.0008598989,0.00079267175,0.00030192526,0.0003690294],"domain_scores_gemma":[0.99795276,0.00007172348,0.000792361,0.0009134314,0.00013091583,0.00013881136],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00024575865,0.00055790995,0.0006869671,0.00013863087,0.00018300899,0.00009744758,0.0009833322,0.0009450273,0.00037899663],"category_scores_gemma":[0.000032003874,0.0003770878,0.0003511315,0.000051251038,0.00038813258,0.000014366904,0.00046775272,0.000503806,0.00009527198],"study_design_candidate":"not_applicable","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":[0.002136774,0.0006033965,0.06714666,0.003228455,0.0150673855,0.00017867454,0.0028493444,0.01107894,0.4070804,0.2388695,0.03696971,0.21479075],"study_design_scores_gemma":[0.00011758962,0.00061330263,0.0002881355,0.00072934723,0.00023041734,0.000047140336,0.000119353055,0.00010792861,0.13018206,0.0014845661,0.8652142,0.00086594565],"about_ca_topic_score_codex":0.000021492284,"about_ca_topic_score_gemma":0.0000073755114,"teacher_disagreement_score":0.8282445,"about_ca_system_score_codex":0.00001437401,"about_ca_system_score_gemma":0.00015846123,"threshold_uncertainty_score":0.9998681},"labels":[],"label_agreement":null},{"id":"W1843850325","doi":"10.7554/elife.07158","title":"Theory, models and biology","year":2015,"lang":"en","type":"editorial","venue":"eLife","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":95,"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 Health Network","funders":"","keywords":"Mathematical and theoretical biology; Systems biology; Computational biology; Biology; Cognitive science; Computer science; Bioinformatics; Psychology","score_opus":0.016481768190559725,"score_gpt":0.2799730371708709,"score_spread":0.26349126898031117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1843850325","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010365404,0.045844812,0.0056373538,0.0000713887,0.9324684,0.0002963658,0.00033630495,0.000055367513,0.0049246126],"genre_scores_gemma":[0.018411273,0.0030583015,0.000341223,0.00008902855,0.9705304,0.000024348341,0.0023859004,0.00007733162,0.0050821905],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985719,0.0001781028,0.00021178606,0.00056710106,0.00020575563,0.00026538197],"domain_scores_gemma":[0.99883485,0.0000403691,0.0001275205,0.00055451924,0.00028762274,0.00015511744],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00062330835,0.00027114156,0.00034481724,0.00005775087,0.00004981881,0.000023097353,0.00026078842,0.0009807575,0.000009295887],"category_scores_gemma":[0.00027272623,0.0002486353,0.000115282215,0.000057553938,0.00013361021,0.0000014690227,0.00028440624,0.00021565685,0.00001650167],"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":[0.00003891622,0.000010177675,0.000016259692,0.000010036508,0.00021064068,8.7103723e-7,0.0000113984715,0.00024193787,0.001066142,0.00010733884,0.9972245,0.0010617828],"study_design_scores_gemma":[0.00026380966,0.00011647488,0.0000025851366,0.000007969485,0.000117840194,0.0000015775798,0.000008629565,0.00021057442,0.00058054837,0.001884534,0.9965262,0.00027927925],"about_ca_topic_score_codex":0.0000121581,"about_ca_topic_score_gemma":0.000024995577,"teacher_disagreement_score":0.042786513,"about_ca_system_score_codex":0.000017923969,"about_ca_system_score_gemma":0.0002896537,"threshold_uncertainty_score":0.9999966},"labels":[],"label_agreement":null},{"id":"W1885746588","doi":"10.1093/nar/gkv595","title":"BioJazz:<i>in silico</i>evolution of cellular networks with unbounded complexity using rule-based modeling","year":2015,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Engineering and Physical Sciences Research Council","keywords":"In silico; DECIPHER; Computer science; Biology; Systems biology; Computational biology; Network dynamics; Evolutionary dynamics; Biological network; Bioinformatics; Genetics; Gene","score_opus":0.09343234369012643,"score_gpt":0.3240143837950815,"score_spread":0.2305820401049551,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1885746588","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":[0.8679616,0.00106948,0.13044532,0.000042703206,0.00002733697,0.0002058698,0.000003931725,0.000010243935,0.00023350536],"genre_scores_gemma":[0.9944153,0.000013163906,0.00524555,0.000013775337,0.00015418672,0.000009431528,0.00006605859,0.000041353465,0.00004118743],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974761,0.00044309907,0.00032949343,0.00049141573,0.00066497753,0.0005949137],"domain_scores_gemma":[0.9984174,0.000017300203,0.00008040052,0.00067721563,0.00060484494,0.00020283245],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016203678,0.0001788324,0.00028324669,0.00026675127,0.00012664527,0.000032128562,0.00036360772,0.00023760844,0.000012735194],"category_scores_gemma":[0.00006647013,0.00016855773,0.00009528856,0.0009351851,0.00043743988,0.0000078895155,0.00018911119,0.00028347544,0.000004215325],"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":[0.00037151264,0.000111886184,0.022408579,0.0000222007,0.000050337567,0.0000056455956,0.000027639233,0.7398064,0.2368571,0.00010426689,0.00007028516,0.00016411956],"study_design_scores_gemma":[0.0010860958,0.00027551834,0.0005843128,0.0000423834,0.000022197699,0.0000033960778,0.00026657162,0.9686457,0.028379504,0.0003559028,0.00014420031,0.00019424505],"about_ca_topic_score_codex":0.00057691627,"about_ca_topic_score_gemma":0.00025826687,"teacher_disagreement_score":0.22883925,"about_ca_system_score_codex":0.00023696912,"about_ca_system_score_gemma":0.00052774005,"threshold_uncertainty_score":0.68735844},"labels":[],"label_agreement":null},{"id":"W1896710669","doi":"10.1371/journal.pone.0127364","title":"Inferring Broad Regulatory Biology from Time Course Data: Have We Reached an Upper Bound under Constraints Typical of In Vivo Studies?","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Institute of Arthritis and Musculoskeletal and Skin Diseases; National Institutes of Health; Compute Canada; Western Canada Research Grid; University of Miami","keywords":"Systems biology; Computer science; In silico; Ode; Gene regulatory network; Biological network; Node (physics); Algorithm; Biology; Computational biology; Mathematics; Physics; Applied mathematics; Gene expression; Genetics","score_opus":0.10543999157074777,"score_gpt":0.31624412026238297,"score_spread":0.2108041286916352,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1896710669","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":[0.9950841,0.004228401,0.000059792965,0.00018293248,0.00003652147,0.00013602745,0.00011131828,0.000012846997,0.00014806484],"genre_scores_gemma":[0.9970733,0.00022559405,0.0015626546,0.00010139368,0.00025655047,0.000007855303,0.000523351,0.000026726993,0.00022259708],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983581,0.00022165189,0.00037583584,0.0005742937,0.00019192153,0.00027821955],"domain_scores_gemma":[0.9983691,0.000031050095,0.00014883908,0.001121391,0.00017270818,0.00015689348],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042199437,0.00019176478,0.0004882222,0.0000651619,0.00002934363,0.000010396788,0.00037361475,0.00026866986,0.000072692295],"category_scores_gemma":[0.00013706031,0.00019124382,0.000053122647,0.0000939664,0.0005027508,0.000011814694,0.00038188358,0.00012248648,0.000014484205],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017740237,0.0010614237,0.08048847,0.000019778448,0.0023156437,0.0000048120864,0.00019568116,0.00018559536,0.9137953,0.00006696469,0.0012791305,0.00040982178],"study_design_scores_gemma":[0.008242567,0.0015318424,0.0817476,0.00058307336,0.0031755725,0.000016520344,0.0043725935,0.012564975,0.87617946,0.0068669836,0.0026631197,0.0020557072],"about_ca_topic_score_codex":0.00005234084,"about_ca_topic_score_gemma":0.00037392092,"teacher_disagreement_score":0.037615832,"about_ca_system_score_codex":0.00004499541,"about_ca_system_score_gemma":0.00018989904,"threshold_uncertainty_score":0.7798697},"labels":[],"label_agreement":null},{"id":"W1905489153","doi":"","title":"Exploration of signaling cycles using dynamic optimization","year":2010,"lang":"en","type":"article","venue":"Infoscience (Ecole Polytechnique Fédérale de Lausanne)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"McMaster University","funders":"","keywords":"Function (biology); MAPK/ERK pathway; Mechanism (biology); Signal transduction; Computer science; Biological system; Protein kinase A; Biology; Kinase; Computational biology; Cell biology; Physics","score_opus":0.013359926340712374,"score_gpt":0.2727725740840015,"score_spread":0.25941264774328915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1905489153","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":[0.6086811,0.0000492978,0.39088374,0.000033489632,0.00007323183,0.00013868425,0.000005088807,0.00002711333,0.00010825454],"genre_scores_gemma":[0.8800677,0.000044099823,0.11958993,0.00006827629,0.000076593096,0.00002500362,0.000031356674,0.000018374581,0.00007864496],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988251,0.000053736203,0.0003191102,0.00031895444,0.00018694202,0.00029620266],"domain_scores_gemma":[0.99907273,0.00001177859,0.00023875854,0.00043640885,0.0001480826,0.000092211456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047899876,0.00014883482,0.0001588573,0.00015969855,0.00013289944,0.000037042486,0.00033820455,0.0002221191,0.000029938272],"category_scores_gemma":[0.00010154544,0.00016486578,0.000100804835,0.00042359057,0.00020462691,0.000045705678,0.00010542882,0.00012840565,0.000001393091],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007662214,0.00002919944,0.0018072976,0.0000068782474,0.0000070217898,5.529764e-7,0.000030101266,0.25421846,0.7431019,0.000060699847,0.00001893197,0.0007113275],"study_design_scores_gemma":[0.00008983063,0.000082894134,0.0003625847,0.000020172862,0.000020597035,0.000010574598,0.000049605165,0.23912394,0.75970215,0.0001916176,0.00017011198,0.00017595702],"about_ca_topic_score_codex":0.000045902172,"about_ca_topic_score_gemma":0.0001234526,"teacher_disagreement_score":0.27138662,"about_ca_system_score_codex":0.000025808951,"about_ca_system_score_gemma":0.00016900303,"threshold_uncertainty_score":0.6723031},"labels":[],"label_agreement":null},{"id":"W1907262747","doi":"10.3233/isb-140463","title":"The utility of simple mathematical models in understanding gene regulatory dynamics","year":2015,"lang":"en","type":"review","venue":"In Silico Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Simple (philosophy); Noise (video); Computational biology; Operon; Bursting; Work (physics); Gene regulatory network; Computer science; Gene; Biology; Neuroscience; Artificial intelligence; Genetics; Gene expression; Physics; Epistemology","score_opus":0.0918474865876045,"score_gpt":0.34239479443411724,"score_spread":0.25054730784651275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1907262747","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0035487337,0.99284756,0.0024283016,0.000012790928,0.000082966886,0.00043784807,0.000060167175,0.0000064361275,0.00057517726],"genre_scores_gemma":[0.12419523,0.8750147,0.0001066225,0.000007940126,0.000081549864,0.000055672077,0.00045196695,0.00004125891,0.000045055305],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9971221,0.0006676369,0.0010491406,0.00057889137,0.0001297836,0.0004524337],"domain_scores_gemma":[0.9982819,0.00014976403,0.00038560096,0.0010444422,0.000059405695,0.00007889472],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0015239893,0.00035901653,0.001389067,0.0001612169,0.00004265165,0.000008654926,0.00058715104,0.0008942915,0.000009233772],"category_scores_gemma":[0.000117771015,0.00025894534,0.00039184614,0.0003785534,0.0004501532,0.0000024677972,0.000344498,0.00027209838,0.0000030948374],"study_design_candidate":"design_other","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":[0.00013907984,0.00043902703,0.0015378807,0.004173069,0.0010628947,0.000020402616,0.00012069336,0.0012109061,0.00040237248,0.032471195,0.0014469828,0.9569755],"study_design_scores_gemma":[0.0016948512,0.0005267109,0.00015439541,0.0024282318,0.0011487518,0.00016784167,0.00062598655,0.08355236,0.00025518012,0.42384306,0.48320585,0.0023967721],"about_ca_topic_score_codex":0.00002153254,"about_ca_topic_score_gemma":0.00068456307,"teacher_disagreement_score":0.9545787,"about_ca_system_score_codex":0.00024876493,"about_ca_system_score_gemma":0.00036407175,"threshold_uncertainty_score":0.9999863},"labels":[],"label_agreement":null},{"id":"W1909028472","doi":"10.1186/s13015-015-0055-3","title":"Erratum to: Inferring interaction type in gene regulatory networks using co-expression data","year":2015,"lang":"en","type":"erratum","venue":"Algorithms for Molecular Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; University of Toronto","funders":"","keywords":"Computer science; Expression (computer science); Type (biology); Data type; Computational biology; Data mining; Gene regulatory network; Data science; Gene expression; Gene; Biology; Genetics; Ecology","score_opus":0.04794319886971091,"score_gpt":0.3569521048979705,"score_spread":0.3090089060282596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1909028472","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":[0.12406406,0.055521365,0.74546397,0.00029510682,0.06488354,0.0049333903,0.0013775013,0.00020672468,0.0032543514],"genre_scores_gemma":[0.41207594,0.003976649,0.16097938,0.0035929552,0.03395932,0.00068267557,0.35440502,0.002092943,0.028235115],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99589527,0.00035041195,0.0007864344,0.0018409744,0.00024156613,0.00088536466],"domain_scores_gemma":[0.9963458,0.0000218189,0.0004513653,0.0024826995,0.00040037397,0.00029789735],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0009035511,0.00069981255,0.0008775831,0.00043864848,0.000118509946,0.000053225976,0.0012667484,0.0019829322,0.000010432687],"category_scores_gemma":[0.00028582738,0.0007489143,0.0002473837,0.00047387855,0.000121211706,0.000014179505,0.0012329868,0.00068146054,0.000008447663],"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":[0.00025545072,0.00009333362,0.00019439259,0.000045067296,0.00046529234,0.000027917129,0.000021433583,0.027388792,0.48064053,0.000008978358,0.48617837,0.0046804403],"study_design_scores_gemma":[0.0015974116,0.0011244687,0.00014628084,0.00037928112,0.000528989,0.000116306896,0.00007269802,0.1747432,0.09553177,0.00034384613,0.72317773,0.002238029],"about_ca_topic_score_codex":0.00008157782,"about_ca_topic_score_gemma":0.00011389654,"teacher_disagreement_score":0.5844846,"about_ca_system_score_codex":0.00019403711,"about_ca_system_score_gemma":0.000559842,"threshold_uncertainty_score":0.99949616},"labels":[],"label_agreement":null},{"id":"W1915556453","doi":"10.1139/p11-147","title":"New robust passivity criteria for discrete-time genetic regulatory networks with Markovian jumping parameters","year":2012,"lang":"en","type":"article","venue":"Canadian Journal of Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Passivity; Upper and lower bounds; Interval (graph theory); Set (abstract data type); Stability (learning theory); Control theory (sociology); Linear matrix inequality; Applied mathematics; Discrete time and continuous time; Computer science; Mathematics; Mathematical optimization; Control (management); Mathematical analysis; Statistics","score_opus":0.011404187830274685,"score_gpt":0.21703504761870662,"score_spread":0.20563085978843193,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1915556453","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":[0.6925203,0.0022271401,0.3044638,0.00014620893,0.0003745296,0.0001756916,0.000017673836,0.000003829941,0.00007077618],"genre_scores_gemma":[0.973201,0.000016291882,0.023714257,0.00016774576,0.0025220376,0.000003872044,0.000035205594,0.00005478634,0.00028482423],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9987019,0.000082308405,0.00029338626,0.00019397265,0.00013073676,0.000597736],"domain_scores_gemma":[0.99810535,0.000018273597,0.0003038111,0.00035948987,0.00016458068,0.0010484946],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002580871,0.00022021883,0.00030531108,0.00006920707,0.00014437614,0.000058312853,0.00025563294,0.00013315202,0.000028622337],"category_scores_gemma":[0.000025176616,0.00020102905,0.00025898928,0.00016153255,0.000097356424,0.000021155105,0.000018901812,0.00012674024,0.0000018721599],"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":[0.00046303435,0.00009287451,0.13843982,0.00011024974,0.0029008908,0.000048132086,0.0004232557,0.5843206,0.041313373,0.00019403428,0.15589198,0.07580174],"study_design_scores_gemma":[0.012499826,0.0060976995,0.5466611,0.0012696126,0.007789432,0.0016342596,0.00087901903,0.07757169,0.12995401,0.0021056822,0.20526169,0.008275978],"about_ca_topic_score_codex":0.00019419329,"about_ca_topic_score_gemma":0.001244461,"teacher_disagreement_score":0.5067489,"about_ca_system_score_codex":0.000083956504,"about_ca_system_score_gemma":0.0007336735,"threshold_uncertainty_score":0.81977266},"labels":[],"label_agreement":null},{"id":"W1964079967","doi":"10.3934/nhm.2008.3.333","title":"The simulation of gene knock-out in scale-free random Boolean models of genetic networks","year":2008,"lang":"en","type":"article","venue":"Networks and Heterogeneous Media","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"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 Calgary","funders":"Ministero dell’Istruzione, dell’Università e della Ricerca","keywords":"Boolean network; Boolean model; Distribution (mathematics); Computer science; Scale (ratio); Topology (electrical circuits); Boolean function; Statistical physics; Mathematics; Discrete mathematics; Algorithm; Physics; Combinatorics; Mathematical analysis; Quantum mechanics","score_opus":0.010810323754582775,"score_gpt":0.21595677330927862,"score_spread":0.20514644955469585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964079967","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":[0.90655494,0.031021487,0.06193752,0.000014949359,0.00016304156,0.00024419205,0.0000063623725,0.000007055289,0.000050481634],"genre_scores_gemma":[0.9875982,0.011331304,0.000446548,0.000039420058,0.0004397358,0.000017459204,0.000045873043,0.000037022473,0.000044467022],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99815565,0.00016581954,0.00066505285,0.0003844585,0.0002327371,0.000396265],"domain_scores_gemma":[0.99862146,0.00013522885,0.00027255385,0.0007215733,0.00012487208,0.00012430064],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031269557,0.00023987517,0.00043675455,0.000064204876,0.00013862255,0.000010786211,0.00033492318,0.00027660586,0.000004074825],"category_scores_gemma":[0.000035751036,0.00019555647,0.00020434498,0.00013997547,0.00032159584,0.0000049368837,0.00015711639,0.00012526625,2.7954061e-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":[0.0002723338,0.000036454134,0.013268969,0.000007752762,0.0001011626,0.0000060901084,0.00011753682,0.97864854,0.001619547,0.0000022303673,0.0001296519,0.0057897097],"study_design_scores_gemma":[0.0016758838,0.00013123977,0.005190243,0.000025036183,0.00008585153,0.000033448086,0.000024747666,0.98889977,0.0032970137,0.00014166743,0.00027294373,0.00022218125],"about_ca_topic_score_codex":0.000026975553,"about_ca_topic_score_gemma":0.0010203255,"teacher_disagreement_score":0.08104326,"about_ca_system_score_codex":0.000012120191,"about_ca_system_score_gemma":0.000041444808,"threshold_uncertainty_score":0.79745615},"labels":[],"label_agreement":null},{"id":"W1964602782","doi":"10.1002/1521-4028(200206)42:3<172::aid-jobm172>3.0.co;2-8","title":"A mutation in the folA promoter delays adaptation to minimal medium by Escherichia coli K-12","year":2002,"lang":"en","type":"article","venue":"Journal of Basic Microbiology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Concordia University","keywords":"Escherichia coli; Adaptation (eye); Mutation; Microbiology; Chemistry; Biology; Genetics; Gene","score_opus":0.010360077963915554,"score_gpt":0.21594771450161415,"score_spread":0.2055876365376986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964602782","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":[0.9942585,0.0011714451,0.0024585738,0.0017649968,0.00013104473,0.00013851286,0.0000074622208,0.0000015315325,0.00006788584],"genre_scores_gemma":[0.9969716,0.00007260482,0.0013792507,0.0010911865,0.0002510188,0.0000068594413,0.000036331,0.000011667707,0.0001794798],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988594,0.00027599515,0.00041449408,0.00017252516,0.00006950936,0.00020807215],"domain_scores_gemma":[0.99939096,0.000024999827,0.0002620583,0.00016226721,0.00010602379,0.00005366434],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049736747,0.00012252813,0.00019761168,0.00008956781,0.00003835587,0.00001436369,0.00024454846,0.00015472632,0.000062795654],"category_scores_gemma":[0.00006432542,0.00008986616,0.00011878669,0.00015845224,0.00004681461,0.000005442192,0.000031052048,0.00013876303,0.00001251742],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000073898154,0.00009033042,0.00040158536,0.000003913559,0.00007453157,0.000013032291,0.00071615604,0.0005670203,0.96315086,0.000002017184,0.033635784,0.0012708955],"study_design_scores_gemma":[0.0056832754,0.0072325626,0.010510845,0.00009370599,0.0005321907,0.0028794024,0.003357946,0.0035262282,0.56767,0.00014009446,0.3973004,0.0010733552],"about_ca_topic_score_codex":0.000007067697,"about_ca_topic_score_gemma":0.00012406621,"teacher_disagreement_score":0.39548084,"about_ca_system_score_codex":0.00002716411,"about_ca_system_score_gemma":0.000039043643,"threshold_uncertainty_score":0.36646354},"labels":[],"label_agreement":null},{"id":"W1964701075","doi":"10.3182/20110828-6-it-1002.01553","title":"Cell energy metabolism : a constrained ensemble Kalman filter","year":2011,"lang":"en","type":"article","venue":"IFAC Proceedings Volumes","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Group for Research in Decision Analysis; Polytechnique Montréal","funders":"","keywords":"Kalman filter; Ensemble Kalman filter; Extended Kalman filter; Invariant extended Kalman filter; Context (archaeology); Control theory (sociology); Fast Kalman filter; Alpha beta filter; Computer science; State variable; Filter (signal processing); Energy (signal processing); Mathematical optimization; Mathematics; Moving horizon estimation; Statistics; Artificial intelligence; Physics; Control (management)","score_opus":0.0105792967176634,"score_gpt":0.19691169551887067,"score_spread":0.18633239880120728,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964701075","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":[0.95236856,0.002290562,0.0010277609,0.00004675104,0.00013543127,0.00010113986,0.000007825269,0.000058598478,0.04396338],"genre_scores_gemma":[0.9872035,0.00014183023,0.0037877208,0.00028512956,0.0003506694,0.00003656832,0.000029823674,0.000044152286,0.008120645],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9986056,0.000013022752,0.00025976766,0.000523788,0.00016756762,0.00043024067],"domain_scores_gemma":[0.9992601,0.0000028945472,0.0001436327,0.00022954414,0.00019936379,0.00016446429],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013502772,0.00026149378,0.0002600878,0.00008731649,0.00010689573,0.00003705642,0.0003023345,0.00020305825,0.00020007219],"category_scores_gemma":[0.000022067989,0.0002561991,0.00021143242,0.0001802284,0.00013356165,0.0000103403645,0.0001508812,0.00007487731,0.00003109897],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008328734,0.00014524382,0.008968481,0.00003644328,0.00029110647,0.000005424532,0.00045287728,0.0000064082155,0.9448,0.0014929074,0.038312364,0.005405464],"study_design_scores_gemma":[0.0005266273,0.00013575755,0.0031546704,0.000008876034,0.00016790685,0.000027121236,0.00026673608,0.0003387626,0.88010955,0.0007064655,0.114086255,0.00047128444],"about_ca_topic_score_codex":0.000059315793,"about_ca_topic_score_gemma":0.000017716486,"teacher_disagreement_score":0.07577389,"about_ca_system_score_codex":0.000009971233,"about_ca_system_score_gemma":0.000054498265,"threshold_uncertainty_score":0.99998903},"labels":[],"label_agreement":null},{"id":"W1965421273","doi":"10.1007/s11538-015-0073-9","title":"A Modelling Framework for Gene Regulatory Networks Including Transcription and Translation","year":2015,"lang":"en","type":"article","venue":"Bulletin of Mathematical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; University of Victoria","funders":"","keywords":"Transcription (linguistics); Messenger RNA; Gene; Biology; Translation (biology); Gene expression; Mathematics; Genetics; Computer science; Computational biology","score_opus":0.05343283456217945,"score_gpt":0.2805075419571269,"score_spread":0.22707470739494745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965421273","genre_codex":"methods","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":[0.23520756,0.0023115329,0.76185477,0.0002948161,0.000040705534,0.00018548605,0.000004715526,0.000009661802,0.00009074416],"genre_scores_gemma":[0.8271689,0.000107422406,0.17234123,0.00006465444,0.00018270113,0.000029691693,0.00005639927,0.000018725465,0.000030299407],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990016,0.000087395674,0.00034211346,0.00029055728,0.00007118812,0.00020711862],"domain_scores_gemma":[0.9993791,0.00009046435,0.000111994304,0.00022364584,0.00009381709,0.00010095291],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006014693,0.00014036111,0.0002820662,0.00003968245,0.000045216195,0.00000663974,0.00009891067,0.00034217178,0.000017208025],"category_scores_gemma":[0.000096928095,0.00012979482,0.000118125,0.000049674334,0.00013853693,0.0000011027458,0.00003303539,0.00006616891,0.00000207595],"study_design_candidate":"simulation_or_modeling","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":[0.0018432516,0.00055764976,0.00057684607,0.00055411854,0.0010027891,0.0000019240576,0.0010320107,0.2685301,0.49268857,0.19177914,0.0038713452,0.03756227],"study_design_scores_gemma":[0.0024160803,0.001220845,0.00004339415,0.0001623359,0.00044380556,0.00004437209,0.00024227898,0.5129557,0.07723643,0.37756512,0.026899176,0.00077041815],"about_ca_topic_score_codex":0.0000025963777,"about_ca_topic_score_gemma":5.413052e-7,"teacher_disagreement_score":0.5919613,"about_ca_system_score_codex":0.000008332717,"about_ca_system_score_gemma":0.00001771339,"threshold_uncertainty_score":0.52928793},"labels":[],"label_agreement":null},{"id":"W1965648656","doi":"10.1049/ip-syb:20050092","title":"Reconstructing gene regulatory networks: from random to scale-free connectivity","year":2006,"lang":"en","type":"article","venue":"Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute","funders":"Innovative Research Group Project of the National Natural Science Foundation of China","keywords":"Gene regulatory network; Computer science; Scale-free network; Biological network; Scale (ratio); Computational biology; Complex network; Expression (computer science); Data mining; Gene; Artificial intelligence; Theoretical computer science; Biology; Gene expression; Genetics","score_opus":0.005372903658405254,"score_gpt":0.20629948667036463,"score_spread":0.20092658301195937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965648656","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":[0.9573915,0.0050354265,0.0350914,0.0000707071,0.0011986308,0.00037542335,0.00007278834,0.000053425232,0.0007107112],"genre_scores_gemma":[0.994469,0.00002711697,0.0012995483,0.00009631656,0.0032162436,0.00006849593,0.0003905088,0.000042084466,0.0003906916],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9974917,0.00049710326,0.0005429568,0.0008416465,0.000104115985,0.0005224596],"domain_scores_gemma":[0.9982304,0.00007222494,0.00024222548,0.001181282,0.00012829792,0.00014554271],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00058300834,0.00030146894,0.0005593026,0.0000943063,0.00016025893,0.00003518934,0.0004276452,0.0004631877,0.00001943385],"category_scores_gemma":[0.00008835255,0.0002899718,0.00021894518,0.00021846686,0.00014291589,0.000003873918,0.00026834558,0.00011335656,0.000023481225],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021669226,0.000039203245,0.15480204,0.000009472335,0.00030462182,0.0000046077935,0.000013712062,0.026654532,0.80714923,0.00022914274,0.008170091,0.0024066225],"study_design_scores_gemma":[0.01820206,0.0013886422,0.14863496,0.00029700104,0.00094928936,0.00059332844,0.00071617396,0.041811585,0.64724004,0.0046891104,0.13000366,0.0054741395],"about_ca_topic_score_codex":0.0012053859,"about_ca_topic_score_gemma":0.0007319243,"teacher_disagreement_score":0.1599092,"about_ca_system_score_codex":0.000048395974,"about_ca_system_score_gemma":0.00005250711,"threshold_uncertainty_score":0.99995524},"labels":[],"label_agreement":null},{"id":"W1966066354","doi":"10.1126/science.1250220","title":"Screening for noise in gene expression identifies drug synergies","year":2014,"lang":"en","type":"article","venue":"Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":226,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Discovery Centre","funders":"National Center for Advancing Translational Sciences; National Institute of Allergy and Infectious Diseases; National Institute of General Medical Sciences; National Institutes of Health","keywords":"Gene; Drug; Gene expression; Computational biology; Noise (video); Biology; Genetics; Computer science; Pharmacology; Artificial intelligence","score_opus":0.008862507838256812,"score_gpt":0.2513408335975663,"score_spread":0.2424783257593095,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966066354","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":[0.97672504,0.0003681726,0.022586998,0.00004984972,0.00009419791,0.000069286994,0.0000012407792,0.0000066256935,0.00009861638],"genre_scores_gemma":[0.9918645,0.000018541788,0.007356239,0.00004828394,0.000109796565,0.000017055507,0.000008116473,0.0000062193203,0.0005712258],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991439,0.00002475048,0.00011441007,0.0003410381,0.00015130348,0.00022459141],"domain_scores_gemma":[0.9995418,0.000011080893,0.000045931105,0.00029770684,0.000053479846,0.000050003357],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006824222,0.00007090034,0.00008074997,0.00008273352,0.00014340905,0.000042599433,0.00030731314,0.000030784606,0.000002890202],"category_scores_gemma":[0.00012227483,0.000064132546,0.000048617352,0.00020907634,0.00018909624,0.000008526612,0.00014252271,0.000023339775,0.0000019379884],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007047773,0.0000057918596,0.003581858,0.0000038839553,0.0000017873845,1.17101514e-7,0.000030286614,0.0053761182,0.9893918,0.000014810964,0.00028357195,0.0013029504],"study_design_scores_gemma":[0.00013331344,0.000016505293,0.00761662,0.000012753132,0.0000043039295,8.349583e-7,0.00006269228,0.0039013957,0.9855792,0.00014928782,0.0024291298,0.00009396314],"about_ca_topic_score_codex":0.00000607225,"about_ca_topic_score_gemma":0.000033832086,"teacher_disagreement_score":0.015230758,"about_ca_system_score_codex":0.000007219822,"about_ca_system_score_gemma":0.000036283956,"threshold_uncertainty_score":0.26152495},"labels":[],"label_agreement":null},{"id":"W1966689781","doi":"10.1080/21642583.2014.886800","title":"Estimating parameters of S-systems by an auxiliary function guided coordinate descent method","year":2014,"lang":"en","type":"article","venue":"Systems Science & Control Engineering","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Coordinate descent; Nonlinear system; Mathematical optimization; Mathematics; Function (biology); Set (abstract data type); Constraint (computer-aided design); Simple (philosophy); Descent (aeronautics); Series (stratigraphy); Applied mathematics; Ordinary differential equation; Algorithm; Computer science; Differential equation","score_opus":0.007294956379677043,"score_gpt":0.2351526965235889,"score_spread":0.22785774014391186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966689781","genre_codex":"methods","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":[0.34019217,0.0004328621,0.6584848,0.000007096884,0.0006426757,0.00018444302,0.0000036436163,0.000025848689,0.000026449688],"genre_scores_gemma":[0.9894198,0.0000017701014,0.010271214,0.000012621206,0.00017789289,0.000040543797,0.00001176253,0.00002302018,0.000041377938],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99818105,0.00014458648,0.0004552141,0.00048283074,0.00034069325,0.0003956062],"domain_scores_gemma":[0.9988071,0.000031190993,0.000222842,0.00053530093,0.0002294702,0.00017411787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002456943,0.00019411535,0.0003440242,0.000129448,0.000107236316,0.00007951533,0.00034155647,0.00009533354,6.293111e-7],"category_scores_gemma":[0.00024253635,0.00018558685,0.00008878768,0.00034149212,0.00007813132,0.000023056622,0.00004549423,0.00006687075,0.0000014490731],"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":[0.0000040663585,0.0000061978253,0.00034663387,0.0000291157,0.000027605765,1.1702261e-7,0.000007946495,0.5352031,0.463747,0.00006381313,0.00003562025,0.0005287498],"study_design_scores_gemma":[0.00038232497,0.00014999836,0.00035837616,0.00004638277,0.000057046425,0.000013094229,0.000041190433,0.97904605,0.019321699,0.0000028849188,0.00039066604,0.00019028607],"about_ca_topic_score_codex":0.0001603537,"about_ca_topic_score_gemma":0.0000020967605,"teacher_disagreement_score":0.6492276,"about_ca_system_score_codex":0.000051902636,"about_ca_system_score_gemma":0.00007113331,"threshold_uncertainty_score":0.7568012},"labels":[],"label_agreement":null},{"id":"W1966746696","doi":"10.1098/rstb.2013.0003","title":"From simple to detailed models for cell polarization","year":2013,"lang":"en","type":"review","venue":"Philosophical Transactions of the Royal Society B Biological Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":89,"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":"National Institute of General Medical Sciences","keywords":"Polarization (electrochemistry); Computer science; In silico; Theoretical computer science; Mathematical model; Biological system; Statistical physics; Physics; Chemistry; Biology","score_opus":0.07312525483569995,"score_gpt":0.30613705864029145,"score_spread":0.2330118038045915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966746696","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0024025629,0.80792314,0.18640211,0.0007111316,0.00020951191,0.0017033132,0.00051806925,0.000025165251,0.0001049928],"genre_scores_gemma":[0.14866106,0.8348599,0.013817978,0.00033406165,0.0010622534,0.0005552616,0.0003419532,0.000046099376,0.00032142983],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99797446,0.00020559615,0.00050889584,0.0007312645,0.00024208768,0.00033769364],"domain_scores_gemma":[0.9989421,0.00013923405,0.00025251275,0.00042282706,0.00009822615,0.00014510535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003390177,0.00032745546,0.0007559347,0.000024250927,0.00043017088,0.00003740378,0.0010569465,0.0006642717,0.000070478265],"category_scores_gemma":[0.000042537376,0.00018109803,0.0020034763,0.00048092753,0.00048637865,0.0000054512752,0.000101933954,0.0001919707,0.0000065630006],"study_design_candidate":"not_applicable","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":[0.000121329256,0.00222504,0.00037322936,0.0038947668,0.004012845,3.5318317e-7,0.00021708195,0.19805697,0.01077497,0.0014281712,0.005086292,0.77380896],"study_design_scores_gemma":[0.0012494859,0.0033771733,0.0000804396,0.0013978556,0.0056345905,0.000004018816,0.0001837848,0.06921094,0.00482776,0.13114406,0.7792674,0.0036225328],"about_ca_topic_score_codex":0.00004671526,"about_ca_topic_score_gemma":0.000003746589,"teacher_disagreement_score":0.77418107,"about_ca_system_score_codex":0.000030765885,"about_ca_system_score_gemma":0.0001234199,"threshold_uncertainty_score":0.7384963},"labels":[],"label_agreement":null},{"id":"W1966845489","doi":"10.1088/1367-2630/10/6/063002","title":"Avalanches, branching ratios, and clustering of attractors in random Boolean networks and in the segment polarity network of<i>Drosophila</i>","year":2008,"lang":"en","type":"article","venue":"New Journal of Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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 Calgary","funders":"","keywords":"Attractor; Boolean network; Cluster analysis; Perturbation (astronomy); Cluster (spacecraft); Measure (data warehouse); Topology (electrical circuits); Boolean model","score_opus":0.012095770553712156,"score_gpt":0.22322387378797623,"score_spread":0.21112810323426406,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966845489","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":[0.98463947,0.0064255144,0.008723042,0.000062522005,0.00005050901,0.00007471527,8.5101806e-7,5.6872415e-7,0.000022788281],"genre_scores_gemma":[0.99683505,0.0018715096,0.00063108717,0.000063129664,0.000582128,3.9573956e-7,0.0000034654468,0.00000906843,0.0000041876465],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99902666,0.00014156383,0.00042990583,0.00011057459,0.00014704137,0.000144281],"domain_scores_gemma":[0.9993643,0.000045565146,0.000356358,0.00014281314,0.000042755884,0.000048179696],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050450343,0.00011111691,0.00032601785,0.000024269857,0.000038608938,0.000008178777,0.000118917196,0.00007423781,5.961392e-7],"category_scores_gemma":[0.00001747688,0.00008827105,0.00009577917,0.00014868616,0.00007149043,0.0000114056065,0.00005244315,0.00019168267,1.8257634e-8],"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":[0.00048100113,0.00010990911,0.44405603,0.000045243825,0.00017438651,0.000014404453,0.0006951189,0.46610504,0.08142944,0.00002686772,0.00038825048,0.0064743212],"study_design_scores_gemma":[0.013538566,0.0008985728,0.91425014,0.0006348749,0.00038464443,0.0004730719,0.00033903052,0.027896944,0.038024735,0.0019001516,0.0009604573,0.0006988255],"about_ca_topic_score_codex":0.000036991445,"about_ca_topic_score_gemma":0.00012504272,"teacher_disagreement_score":0.4701941,"about_ca_system_score_codex":0.000009970601,"about_ca_system_score_gemma":0.00006882527,"threshold_uncertainty_score":0.35995892},"labels":[],"label_agreement":null},{"id":"W1967052210","doi":"10.1016/j.febslet.2005.08.062","title":"Alternative signaling pathways: When, where and why?","year":2005,"lang":"en","type":"review","venue":"FEBS Letters","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":24,"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":"Signal transduction; Biology; Computational biology; Biological pathway; Signalling pathways; Neuroscience; Cell biology; Genetics","score_opus":0.02606076761490357,"score_gpt":0.2630751032474867,"score_spread":0.23701433563258312,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1967052210","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00067912624,0.9976077,0.0009942106,0.00019655842,0.00013797425,0.0002592743,0.00003233833,0.000016608123,0.000076208715],"genre_scores_gemma":[0.000120157085,0.9951817,0.00085323694,0.0013348707,0.0018565172,0.000048354217,0.00029155848,0.00008757895,0.0002260211],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981134,0.00020362412,0.00040779353,0.0007336101,0.00018340349,0.0003581678],"domain_scores_gemma":[0.9989846,0.00002286185,0.00030969924,0.00052084634,0.000036876172,0.00012514167],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018109818,0.0004854468,0.0008626529,0.00010890101,0.0000855072,0.00006506364,0.0003338203,0.0003182287,0.00005198586],"category_scores_gemma":[0.000015133021,0.00043649538,0.0004954986,0.00010237107,0.00009608168,0.000003971753,0.00019337736,0.00022506314,0.00002890132],"study_design_candidate":"not_applicable","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":[0.0000063262337,0.000022846376,0.000015744292,0.0017780432,0.0012341947,0.000033659537,0.000055798657,0.0002447107,0.0025824762,0.000015469403,0.038813777,0.955197],"study_design_scores_gemma":[0.00011921171,0.00003058419,5.8270416e-7,0.0011374701,0.0006238693,0.00003800831,0.0000073048354,0.000016739588,0.00014888051,0.000010208878,0.9974079,0.00045920254],"about_ca_topic_score_codex":0.000015163266,"about_ca_topic_score_gemma":0.000030601626,"teacher_disagreement_score":0.95859414,"about_ca_system_score_codex":0.00004799429,"about_ca_system_score_gemma":0.00006289051,"threshold_uncertainty_score":0.99980867},"labels":[],"label_agreement":null},{"id":"W1967885456","doi":"10.1016/j.jtbi.2004.05.008","title":"Modeling genetic networks from clonal analysis","year":2004,"lang":"en","type":"article","venue":"Journal of Theoretical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canada Research Chairs; University of Toronto; University of New Brunswick","funders":"National Center for Research Resources; National Institute on Aging; National Institutes of Health; Badan Riset dan Inovasi Nasional","keywords":"Mutual information; Binary number; Equivalence (formal languages); Computer science; Bayesian network; Perturbation (astronomy); Correlation; Mathematics; Theoretical computer science; Data mining; Algorithm; Artificial intelligence; Discrete mathematics; Physics","score_opus":0.005203434046949611,"score_gpt":0.2370746050497131,"score_spread":0.23187117100276347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1967885456","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":[0.5959148,0.002091514,0.4015907,0.0001889312,0.00012771427,0.000024186682,0.0000052926785,0.0000028740158,0.000054004293],"genre_scores_gemma":[0.9882846,0.00043951708,0.009777124,0.00029797078,0.0011184372,0.0000013666122,0.000057293903,0.000017482009,0.000006237955],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99840814,0.00019566175,0.0006289139,0.0002973977,0.0001444153,0.00032547253],"domain_scores_gemma":[0.9989809,0.000035239686,0.00021812937,0.0003538684,0.00020915976,0.00020271057],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003863747,0.00019107903,0.00048761247,0.00016590797,0.000058749614,0.000019259047,0.00041346127,0.0003292577,0.00015726671],"category_scores_gemma":[0.000112841866,0.00014987917,0.00070470513,0.00032835145,0.00033822306,0.0000028752438,0.0001228885,0.00022432973,0.000005703453],"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":[0.0002114263,0.0000736625,0.0074633798,0.000001102745,0.00248921,0.0000164834,0.0000123334985,0.9496464,0.028254725,0.010807363,0.000033249846,0.0009906687],"study_design_scores_gemma":[0.0051954035,0.003054298,0.011840917,0.000056207777,0.010794581,0.00036710838,0.00015613346,0.5837333,0.02807878,0.3535136,0.0016492613,0.0015603675],"about_ca_topic_score_codex":0.000013861071,"about_ca_topic_score_gemma":0.000017178838,"teacher_disagreement_score":0.39236978,"about_ca_system_score_codex":0.000032743617,"about_ca_system_score_gemma":0.000087266424,"threshold_uncertainty_score":0.6111895},"labels":[],"label_agreement":null},{"id":"W1967936225","doi":"10.1016/j.tree.2008.10.004","title":"Systems biology spins off a new model for the study of canalization","year":2008,"lang":"en","type":"article","venue":"Trends in Ecology & Evolution","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; Université de Montréal","funders":"","keywords":"Robustness (evolution); Biology; Natural selection; Evolutionary biology; Gene; Systems biology; Computational biology; Gene expression; Genetics; Gene regulatory network; Phenotype; Selection (genetic algorithm); Computer science; Artificial intelligence","score_opus":0.02676573246385749,"score_gpt":0.2804668368066462,"score_spread":0.2537011043427887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1967936225","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":[0.9647023,0.001451925,0.033303507,0.00006334702,0.0001629098,0.00026402253,0.0000074844424,0.0000062660865,0.000038255825],"genre_scores_gemma":[0.99825555,0.00009633851,0.00011171812,0.000015340373,0.00013331334,0.00008353861,0.0000963447,0.000011525829,0.0011963313],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990513,0.00011490213,0.0003057332,0.00026758865,0.000055430373,0.00020508296],"domain_scores_gemma":[0.99939746,0.000019882185,0.00015771804,0.00031476078,0.000078712124,0.000031453466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019794705,0.00010833218,0.00020921703,0.0001620198,0.000099293415,0.0000017953199,0.00016224562,0.0001734822,0.000005301414],"category_scores_gemma":[0.000034197,0.00009028465,0.000076852164,0.0002788556,0.00008105937,0.0000026002301,0.00004546621,0.000045905814,6.329093e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007270488,0.00019122256,0.3157053,0.0000040466603,0.00016432533,3.3315266e-7,0.00020743706,0.67555386,0.004123217,0.00022620519,0.0028323173,0.0009190355],"study_design_scores_gemma":[0.0012753423,0.00067783816,0.3556693,0.000002398553,0.0001341512,0.000010019458,0.0002111573,0.6411092,0.00014139769,0.00008822809,0.0005620282,0.00011895483],"about_ca_topic_score_codex":0.00074233,"about_ca_topic_score_gemma":0.0199465,"teacher_disagreement_score":0.03996398,"about_ca_system_score_codex":0.00007120367,"about_ca_system_score_gemma":0.00013916339,"threshold_uncertainty_score":0.9979369},"labels":[],"label_agreement":null},{"id":"W1968414492","doi":"10.1016/j.jtbi.2010.07.034","title":"Considerations for using integral feedback control to construct a perfectly adapting synthetic gene network","year":2010,"lang":"en","type":"article","venue":"Journal of Theoretical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":106,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of Toronto","funders":"","keywords":"Synthetic biology; Gene regulatory network; Realization (probability); Computer science; Control theory (sociology); Adaptation (eye); Controller (irrigation); Construct (python library); Harmonic oscillator; Feedback control; Control (management); Control engineering; Topology (electrical circuits); Mathematics; Physics; Biology; Gene; Engineering; Computational biology; Genetics; Artificial intelligence; Computer network","score_opus":0.010231692237071566,"score_gpt":0.2642738300045511,"score_spread":0.2540421377674796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968414492","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":[0.8741534,0.00024170912,0.12396312,0.0006871476,0.0006350621,0.0002006634,0.00002082231,0.0000044533626,0.00009367367],"genre_scores_gemma":[0.9237899,0.0000061399423,0.07402026,0.00059946213,0.0015427594,0.0000057974426,0.0000064008746,0.000021771377,0.000007491314],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99845475,0.00023931537,0.0005640412,0.00025637698,0.000081522645,0.0004039983],"domain_scores_gemma":[0.9984406,0.0003628761,0.00027864927,0.00026653564,0.00042086426,0.00023043921],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001011912,0.00018788995,0.00044406243,0.00008084199,0.00015334497,0.000032087373,0.0002084618,0.00028054081,0.00015966254],"category_scores_gemma":[0.0016132115,0.00014747246,0.0003655001,0.00009371459,0.0005814694,0.0000033714437,0.000068377616,0.00026831363,0.0000036827057],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034958255,0.000032324784,0.001514577,0.000004132207,0.00032981613,0.0000041072003,0.000014270157,0.0037351323,0.88897324,0.103601575,0.0003613888,0.0010798754],"study_design_scores_gemma":[0.008847068,0.007859132,0.0011623733,0.00016507371,0.0027742872,0.008102211,0.00035768797,0.0472408,0.5753582,0.33042696,0.015697131,0.0020090814],"about_ca_topic_score_codex":0.0000011397029,"about_ca_topic_score_gemma":0.000009565822,"teacher_disagreement_score":0.31361502,"about_ca_system_score_codex":0.000017095737,"about_ca_system_score_gemma":0.00017795044,"threshold_uncertainty_score":0.6013752},"labels":[],"label_agreement":null},{"id":"W1969236385","doi":"10.1103/physreve.82.021911","title":"Minimal genetic device with multiple tunable functions","year":2010,"lang":"en","type":"article","venue":"Physical Review E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; New England Biolabs Foundation","keywords":"Computer science; Mathematics; Topology (electrical circuits); Combinatorics","score_opus":0.008218223985857842,"score_gpt":0.25373597461569974,"score_spread":0.2455177506298419,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969236385","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":[0.98996854,0.008001117,0.00052009686,0.00017675833,0.000050821116,0.00019748509,0.000005222789,0.000014782074,0.0010651848],"genre_scores_gemma":[0.9958568,0.0010682172,0.0013462552,0.00045094473,0.0005352929,0.00006556009,0.000054003405,0.00002385794,0.0005990216],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99914515,0.000037789498,0.00013520903,0.00033090395,0.00013349425,0.00021744923],"domain_scores_gemma":[0.9991928,0.000015511607,0.00006460449,0.00051356957,0.00009286627,0.00012067381],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007022119,0.00015069378,0.0002229241,0.000012991285,0.00007205572,0.0000119447595,0.0001571115,0.00003830272,0.000061466984],"category_scores_gemma":[0.00006243082,0.000115045084,0.00015633163,0.00018687866,0.000067929905,0.0000026395824,0.000060677117,0.00011992143,0.00012972967],"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":[0.00003242797,0.00028244377,0.01666942,0.00034900758,0.00022471687,0.000004426006,0.000008657792,0.0002594809,0.95413923,0.000065828914,0.008706332,0.01925804],"study_design_scores_gemma":[0.00055672135,0.00038256825,0.033956166,0.00019505413,0.00071285997,0.000043844404,0.000010484585,0.0017919607,0.049086213,0.00007854149,0.91256976,0.0006158036],"about_ca_topic_score_codex":0.000008862352,"about_ca_topic_score_gemma":0.00012488732,"teacher_disagreement_score":0.905053,"about_ca_system_score_codex":0.0000040745417,"about_ca_system_score_gemma":0.000051441675,"threshold_uncertainty_score":0.46914023},"labels":[],"label_agreement":null},{"id":"W1969913124","doi":"10.1126/science.339.6120.646-a","title":"Physical Laws Shape Biology","year":2013,"lang":"en","type":"letter","venue":"Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute on Governance","funders":"","keywords":"Physical law; Law; Biology; Political science; Philosophy; Epistemology","score_opus":0.0095078013104822,"score_gpt":0.2550489041941861,"score_spread":0.24554110288370387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969913124","genre_codex":"empirical","genre_gemma":"commentary","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":[0.8203884,0.0018489562,0.0003309601,0.16938964,0.0013335312,0.0004548998,0.000043792093,0.000061728526,0.0061481185],"genre_scores_gemma":[0.45637703,0.00012656096,0.0008202109,0.5100877,0.018538967,0.000086601896,0.00062287453,0.000087240755,0.0132528115],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99807423,0.00005687711,0.00014442325,0.00088919315,0.00026578,0.0005694972],"domain_scores_gemma":[0.9988091,0.00000982541,0.000111732224,0.00083693274,0.00015131886,0.000081101265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018610198,0.0002365019,0.00024264204,0.00010425727,0.00014639932,0.00006082626,0.0010271909,0.00040885698,0.00010005088],"category_scores_gemma":[0.00004985562,0.000200049,0.0001752589,0.00035717935,0.0010886684,0.0000036953786,0.0003770703,0.0003600288,0.00030134298],"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":[0.0000010837592,0.000010682659,0.00017730551,0.0000082659335,0.000031488184,0.0000046950977,0.000008704125,0.000017781282,0.2679253,0.000019364463,0.7291318,0.0026635258],"study_design_scores_gemma":[0.000072872535,0.00008242964,0.00019796344,0.0000051870466,0.000030390755,0.000008787148,0.0000028276,0.00075439323,0.023761636,0.0003226627,0.9744641,0.0002967256],"about_ca_topic_score_codex":0.00000886254,"about_ca_topic_score_gemma":0.000002717284,"teacher_disagreement_score":0.36401138,"about_ca_system_score_codex":0.000024219316,"about_ca_system_score_gemma":0.0002362869,"threshold_uncertainty_score":0.81577617},"labels":[],"label_agreement":null},{"id":"W1970127369","doi":"10.1159/000163533","title":"Time-Based Changes in Fibroblast Three-Dimensional Locomotory Characteristics and Phenotypes","year":2008,"lang":"en","type":"article","venue":"Experimental Cell Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Phenotype; Embryonic stem cell; Population; Biology; Fibroblast; Evolutionary biology; Cell biology; Genetics; Cell culture; Gene; Medicine","score_opus":0.008115316644333603,"score_gpt":0.2154023203975629,"score_spread":0.2072870037532293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970127369","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":[0.9969268,0.0025697013,0.000029856603,0.00004447532,0.000057248384,0.00012881415,0.00001450024,0.0000114440645,0.00021714604],"genre_scores_gemma":[0.9984246,0.000029809875,0.0005075235,0.00027049644,0.00016620384,0.000025734822,0.00030277038,0.00002078202,0.00025206956],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990521,0.00007588267,0.00016438524,0.00039326353,0.000058727583,0.00025561283],"domain_scores_gemma":[0.99960333,0.000014199909,0.00007084844,0.00021387312,0.000020628962,0.00007709535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006888101,0.00018747688,0.00021447489,0.00006963242,0.00008099573,0.0000041039534,0.00010633569,0.00017982462,0.00015744109],"category_scores_gemma":[0.0000052305554,0.00018285948,0.000052386476,0.00006614102,0.00031219725,0.0000018724647,0.00012208255,0.00006666623,0.00003263521],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009927152,0.00011259606,0.014514869,0.00000564854,0.000017724478,0.0000076083415,0.000025741087,0.000100945654,0.98462707,0.0000027011076,0.0003012818,0.0001845634],"study_design_scores_gemma":[0.00075139536,0.0005650608,0.0094440095,0.0000075372773,0.000007637892,0.0000143579955,0.000016820388,0.0020277775,0.98245525,0.000005114712,0.0044286125,0.00027640135],"about_ca_topic_score_codex":0.000016906783,"about_ca_topic_score_gemma":0.000046530182,"teacher_disagreement_score":0.00507086,"about_ca_system_score_codex":0.000021506625,"about_ca_system_score_gemma":0.000042727035,"threshold_uncertainty_score":0.7456793},"labels":[],"label_agreement":null},{"id":"W1970433700","doi":"10.1142/s0218301308010271","title":"A COMPUTATIONAL MODEL FOR LESION DYNAMICS IN MULTIPLE SCLEROSIS OF THE BRAIN","year":2008,"lang":"en","type":"article","venue":"International Journal of Modern Physics E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"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":"University at Buffalo; McMaster University; Pfizer","keywords":"Multiple sclerosis; Lesion; Neuroscience; Myelin; Central nervous system; Degeneration (medical); Pathological; Programmed cell death; Pathology; Biology; Medicine; Immunology","score_opus":0.039874495414042706,"score_gpt":0.26230198971150653,"score_spread":0.22242749429746383,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970433700","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":[0.6183117,0.000053820655,0.3812198,0.00026816936,0.0000658641,0.000040731964,0.000025798021,5.546975e-7,0.000013554535],"genre_scores_gemma":[0.9939495,0.00003149896,0.005644129,0.00011698668,0.00014107657,0.000002387481,0.000033687265,0.000011034657,0.00006973927],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992089,0.000027533435,0.00029835358,0.00009487812,0.00029538383,0.000074932526],"domain_scores_gemma":[0.9990884,0.000035896846,0.0003022173,0.000098425495,0.00045241756,0.000022660743],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012779223,0.00007221454,0.00012106192,0.000043734864,0.000032957898,0.000005237086,0.00032634524,0.00004579887,7.692408e-7],"category_scores_gemma":[0.000051119096,0.000059783437,0.00023480946,0.000054815187,0.000059576905,0.0000079225765,0.00006934475,0.000062023195,1.6777753e-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":[0.00011211016,0.0001093287,0.011615874,0.000002837442,0.000116226525,5.593784e-7,0.00008685534,0.94971734,0.03496437,0.00028422222,0.00040444778,0.0025857964],"study_design_scores_gemma":[0.00085531763,0.00003142321,0.0045456523,0.000027760307,0.000012260624,0.000014433719,0.00000967477,0.97601944,0.008243292,0.010161184,0.000022811575,0.00005676643],"about_ca_topic_score_codex":0.0000040390964,"about_ca_topic_score_gemma":0.000038553637,"teacher_disagreement_score":0.37563777,"about_ca_system_score_codex":0.000066486464,"about_ca_system_score_gemma":0.00014054913,"threshold_uncertainty_score":0.24378978},"labels":[],"label_agreement":null},{"id":"W1970557025","doi":"10.1089/cmb.2014.0057","title":"Asynchronous Stochastic Boolean Networks as Gene Network Models","year":2014,"lang":"en","type":"article","venue":"Journal of Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":23,"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 Alberta","funders":"","keywords":"Asynchronous communication; Boolean network; Gene regulatory network; Computer science; Robustness (evolution); ENCODE; Biological network; Attractor; Stochastic process; Theoretical computer science; Boolean function; Mathematics; Gene; Algorithm; Biology; Computational biology; Genetics","score_opus":0.0065819920977378005,"score_gpt":0.23475709909424486,"score_spread":0.22817510699650706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970557025","genre_codex":"methods","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":[0.29598698,0.0016255176,0.701723,0.00011944647,0.00030995085,0.000046596266,0.0000016328702,0.00000484462,0.00018207794],"genre_scores_gemma":[0.9833164,0.00005116143,0.013085746,0.0006548557,0.0027121033,0.0000021569385,0.00011858446,0.000022573988,0.000036416423],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985107,0.00024341994,0.00054528215,0.00023243492,0.00015868121,0.00030948984],"domain_scores_gemma":[0.9986997,0.0000963507,0.00049378996,0.00018588905,0.00037051973,0.00015372247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005841464,0.0001827304,0.00034546695,0.0000861677,0.00011375792,0.000019110665,0.00028505217,0.00020336996,0.00002435656],"category_scores_gemma":[0.00006082035,0.00016385238,0.00025156475,0.00013769337,0.000113909606,0.000006553821,0.00008712633,0.00016650664,0.000010186938],"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":[0.00009986282,0.000032736032,0.0004149068,0.0000018308656,0.00026868275,0.0000022997888,0.0000069732346,0.98927116,0.0013112135,0.002488885,0.0015776097,0.004523823],"study_design_scores_gemma":[0.0012701071,0.0016176113,0.0019279767,0.00002312063,0.00017899871,0.00066271937,0.000013185168,0.8885444,0.00037708867,0.10092034,0.004068913,0.0003955441],"about_ca_topic_score_codex":0.0000028281906,"about_ca_topic_score_gemma":0.000004348684,"teacher_disagreement_score":0.6886372,"about_ca_system_score_codex":0.000026499007,"about_ca_system_score_gemma":0.00015318992,"threshold_uncertainty_score":0.6681706},"labels":[],"label_agreement":null},{"id":"W1970587132","doi":"10.1073/pnas.1116998108","title":"Metabolic cycling without cell division cycling in respiring yeast","year":2011,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":89,"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":"National Institutes of Health; National Institute of General Medical Sciences; McKnight Foundation","keywords":"Cell cycle; Yeast; Cycling; Cell division; Biology; Metabolic pathway; Saccharomyces cerevisiae; Gene; Cell biology; Division (mathematics); Biochemistry; Genetics; Cell","score_opus":0.039287833092452214,"score_gpt":0.2895467977328367,"score_spread":0.2502589646403845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970587132","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":[0.9954221,0.0005269485,0.000005832924,0.00006441526,0.000011087351,0.000067943474,0.0000015523634,0.0000026939326,0.0038974134],"genre_scores_gemma":[0.99732757,0.00006103682,0.0024121094,0.00005626264,0.00006397012,0.0000035602163,1.3950721e-7,0.0000047939093,0.00007054724],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988679,0.00000874109,0.00028036503,0.0002456636,0.00045695875,0.000140367],"domain_scores_gemma":[0.9995509,0.000008717741,0.0002962735,0.000012110168,0.00010601069,0.000026007643],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011941154,0.00007896381,0.00013086021,0.00013802071,0.00008587791,0.000008285623,0.00053143234,0.0000799565,0.0000036590097],"category_scores_gemma":[0.00015355207,0.00005780387,0.00008516893,0.00047804677,0.00025667096,0.000019185813,0.00019307253,0.00008574169,6.1838466e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000805304,0.00002242352,0.11658166,0.0000118267,0.0000086894315,2.0232236e-9,0.00007758986,0.000760863,0.8817746,0.0005008724,0.000013936871,0.00023945239],"study_design_scores_gemma":[0.00009783715,0.000016118383,0.16914488,0.000029182891,0.000010631424,8.485642e-7,0.00007504411,0.0009651816,0.82763827,0.0018976617,0.00006486497,0.00005946843],"about_ca_topic_score_codex":0.0000066983444,"about_ca_topic_score_gemma":2.872164e-7,"teacher_disagreement_score":0.054136354,"about_ca_system_score_codex":0.0000068527174,"about_ca_system_score_gemma":0.000019315632,"threshold_uncertainty_score":0.23571734},"labels":[],"label_agreement":null},{"id":"W1970708036","doi":"10.1103/physrevlett.107.218101","title":"Gene Expression Noise Facilitates Adaptation and Drug Resistance Independently of Mutation","year":2011,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":89,"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 Ottawa","funders":"","keywords":"Biology; Gene; Mutation; Adaptation (eye); Population; Genetics; Drug resistance; Gene expression; Computational biology; Neuroscience; Medicine","score_opus":0.015958944819351065,"score_gpt":0.24285344613465876,"score_spread":0.2268945013153077,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970708036","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":[0.9783402,0.018817885,0.002457612,0.0001798778,0.000014700138,0.00013900395,0.000004538943,0.0000046679706,0.00004149345],"genre_scores_gemma":[0.9937555,0.0037938873,0.0018326552,0.0004692836,0.00004157942,0.00001917678,0.000046928955,0.000008875003,0.000032089476],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992791,0.000094728784,0.00017381628,0.00022783353,0.00012796106,0.00009659097],"domain_scores_gemma":[0.9995611,0.000010956914,0.0001262547,0.0002116108,0.000046109868,0.000043968153],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011662515,0.000099428915,0.0001783127,0.000017514274,0.000025386158,0.000002299639,0.00007873061,0.000011434926,0.0000055486357],"category_scores_gemma":[0.000029860588,0.000087466186,0.00009109959,0.00007548586,0.000058485755,0.0000062455424,0.000036904064,0.00003593186,0.00000344769],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025279229,0.000035674744,0.00044338586,0.00026171515,0.000034911387,0.0000012411302,0.00026657313,0.00009144754,0.9959297,0.0000073457454,0.0011028443,0.0017998664],"study_design_scores_gemma":[0.00025075316,0.00003793734,0.0053392057,0.00040304326,0.00015894725,0.000001832158,0.0000464111,0.0002613126,0.99181205,0.00016426167,0.0013049659,0.00021927658],"about_ca_topic_score_codex":0.0000058534483,"about_ca_topic_score_gemma":0.000005618779,"teacher_disagreement_score":0.015415304,"about_ca_system_score_codex":0.000005309329,"about_ca_system_score_gemma":0.0000085976835,"threshold_uncertainty_score":0.35667676},"labels":[],"label_agreement":null},{"id":"W1970995125","doi":"10.1145/2506583.2512380","title":"Sparse and Stable Reconstruction of Genetic Regulatory Networks Using Time Series Gene Expression Data","year":2013,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Toronto Metropolitan University","funders":"","keywords":"Gene regulatory network; Computer science; Series (stratigraphy); Stability (learning theory); Gene; Genetic algorithm; Network topology; Expression (computer science); Computational biology; Set (abstract data type); Regular polygon; Regulation of gene expression; Time series; Gene expression; Biology; Mathematics; Genetics; Machine learning","score_opus":0.013249845516458084,"score_gpt":0.2127405516563206,"score_spread":0.19949070613986253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970995125","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":[0.98724174,0.0019373302,0.010472368,0.000011835724,0.00006171248,0.00014260996,0.0000072497965,0.00001041902,0.000114702605],"genre_scores_gemma":[0.9411144,0.00039704642,0.057210304,0.000021314596,0.0002078288,0.000004545979,0.00013204172,0.000024295852,0.000888174],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99893296,0.00007076975,0.000276404,0.00042086796,0.0000998921,0.00019909073],"domain_scores_gemma":[0.998749,0.000005065695,0.00014462357,0.0009236326,0.00009257731,0.000085107386],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014062485,0.00014347296,0.00019254825,0.000042696836,0.00007507289,0.000024632365,0.00019121039,0.00015210173,0.00021616385],"category_scores_gemma":[0.000012170323,0.00013262396,0.00003827521,0.00009309575,0.00014006997,0.000022284872,0.00037456138,0.00004154341,0.000004000552],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015344067,0.0000119537435,0.012326588,0.000010194408,0.00006381658,3.335639e-7,0.000004004945,0.010318391,0.9710476,0.0000017943598,0.0016844341,0.004515557],"study_design_scores_gemma":[0.0003953916,0.00012531961,0.019757608,0.000041285188,0.0001459743,0.00014419878,0.00008346806,0.15813114,0.8197897,0.0001056413,0.0008729466,0.0004073229],"about_ca_topic_score_codex":0.000049803897,"about_ca_topic_score_gemma":0.000012191153,"teacher_disagreement_score":0.15125789,"about_ca_system_score_codex":0.0000078001885,"about_ca_system_score_gemma":0.00003883627,"threshold_uncertainty_score":0.54082483},"labels":[],"label_agreement":null},{"id":"W1971445167","doi":"10.1038/nrm2766","title":"Systems biology of stem cell fate and cellular reprogramming","year":2009,"lang":"en","type":"review","venue":"Nature Reviews Molecular Cell Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":388,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of General Medical Sciences; Stem Cell Network","keywords":"Biology; Reprogramming; Cell fate determination; Signalling; Robustness (evolution); Systems biology; Stem cell; Cell biology; Gene regulatory network; Computational biology; Attractor; Cellular differentiation; Regulation of gene expression; Population; Stem cell biology; Gene expression; Gene; Genetics; Transcription factor; Mathematics","score_opus":0.014829151911576525,"score_gpt":0.28441572893801054,"score_spread":0.269586577026434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971445167","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00035431152,0.9949012,0.0012759649,0.0000062812105,0.00040301858,0.0019647095,0.000058113204,0.000025553163,0.0010108493],"genre_scores_gemma":[0.0027639496,0.9934783,0.0009869388,0.00007663683,0.00034371208,0.00015631113,0.0016593004,0.00012925883,0.00040561057],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99271435,0.0022946503,0.0019976997,0.0019971647,0.00015571414,0.0008404358],"domain_scores_gemma":[0.9952822,0.000058680107,0.0021573093,0.0020564876,0.00018600877,0.00025934697],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0013336508,0.0012346782,0.00465736,0.00036454416,0.00009223629,0.00003461359,0.00094447593,0.0041900533,0.00000777296],"category_scores_gemma":[0.000043920263,0.0009770683,0.0017874229,0.00064740615,0.00029187815,0.000003696557,0.00044218593,0.0011203348,0.000024545627],"study_design_candidate":"not_applicable","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":[0.000007959358,0.0000786001,0.00001633047,0.013368406,0.00035189482,0.000019827383,0.0000051257243,0.000007935617,0.036286425,0.00017582491,0.00031434267,0.94936734],"study_design_scores_gemma":[0.00023263902,0.0004100606,1.5087552e-7,0.0015979689,0.001890479,0.00003309118,0.000005803699,0.0000074459294,0.0074303583,0.00002012311,0.98754686,0.00082502875],"about_ca_topic_score_codex":0.00000883674,"about_ca_topic_score_gemma":0.0000017493381,"teacher_disagreement_score":0.9872325,"about_ca_system_score_codex":0.000051013343,"about_ca_system_score_gemma":0.00021541076,"threshold_uncertainty_score":0.999268},"labels":[],"label_agreement":null},{"id":"W1971644094","doi":"10.1371/journal.pcbi.1002271","title":"A Density-Dependent Switch Drives Stochastic Clustering and Polarization of Signaling Molecules","year":2011,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":69,"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":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; Rita Allen Foundation; Welch Foundation; National Science Foundation","keywords":"Cluster analysis; Positive feedback; Cell signaling; Negative feedback; Biological system; Directionality; Physics; Signal transduction; Mechanism (biology); Biophysics; Biology; Statistical physics; Topology (electrical circuits); Computer science; Cell biology; Genetics; Mathematics; Voltage; Artificial intelligence","score_opus":0.016119359007631614,"score_gpt":0.2237520665483821,"score_spread":0.20763270754075047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971644094","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":[0.6948081,0.00025472383,0.30480596,0.000011343333,0.000021138561,0.000059467235,0.000005157088,0.000006236683,0.000027841152],"genre_scores_gemma":[0.98762316,0.0000070790734,0.012098676,0.000049261125,0.00004926934,0.0000047259823,0.00014364197,0.000011107717,0.000013071301],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992768,0.00007497603,0.00020232424,0.00025342527,0.00006965677,0.00012277729],"domain_scores_gemma":[0.9995854,0.000024410792,0.000116092,0.00010070455,0.00012958607,0.00004382461],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007789079,0.000104223014,0.00015066605,0.00007523201,0.000052425956,0.000005117046,0.000081990875,0.00009705286,0.000011518472],"category_scores_gemma":[0.00003499992,0.000105027786,0.000043804346,0.00006469819,0.00009285276,0.0000029640512,0.00011370909,0.000039802293,0.0000017805864],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006106319,0.00006601174,0.023737896,0.000018978095,0.00026477716,0.0000010805736,0.00015262645,0.053569198,0.9207258,0.00078302406,0.000003249355,0.00061627425],"study_design_scores_gemma":[0.001838004,0.001209872,0.109857894,0.00008294381,0.00046386707,0.00011038111,0.00031986568,0.3412843,0.5243969,0.019455587,0.000023257948,0.0009571163],"about_ca_topic_score_codex":0.000013355536,"about_ca_topic_score_gemma":0.000015143396,"teacher_disagreement_score":0.39632893,"about_ca_system_score_codex":0.000005858379,"about_ca_system_score_gemma":0.000032495584,"threshold_uncertainty_score":0.42829087},"labels":[],"label_agreement":null},{"id":"W1972746135","doi":"10.1145/952532.952561","title":"Inference of transcriptional regulation relationships from gene expression data","year":2003,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"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":"","keywords":"Inference; False positive paradox; Event (particle physics); Computer science; Gene; Computational biology; Expression (computer science); Data mining; Transcriptional regulation; Microarray analysis techniques; Correlation; Gene expression; Artificial intelligence; Biology; Mathematics; Genetics","score_opus":0.052325842690366116,"score_gpt":0.267251417320557,"score_spread":0.2149255746301909,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972746135","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":[0.8377004,0.0007471011,0.16001986,0.000026963116,0.000050829683,0.00006231088,0.000053579686,0.000007273653,0.0013316236],"genre_scores_gemma":[0.9718432,0.000050721763,0.025542302,0.00001573841,0.00006241898,0.0000027553485,0.0019736553,0.000008152355,0.00050104386],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991134,0.00015453939,0.0002111558,0.00029752034,0.00013763549,0.00008579457],"domain_scores_gemma":[0.9990366,0.000022307033,0.00007786007,0.00075193605,0.000069061694,0.00004222726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023780567,0.00008013598,0.000092503644,0.000029650759,0.0000559918,0.000006541855,0.00018608592,0.00012606497,0.0002732101],"category_scores_gemma":[0.00012458694,0.00007532932,0.000044291042,0.000092983675,0.000036788,0.0000071523264,0.000045108474,0.000050774703,0.000005917529],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000118427115,0.000025655296,0.024325183,0.0000018218396,0.000032843964,7.758413e-8,0.000011619804,0.002095581,0.9718192,0.00070391595,0.00081014365,0.00016207177],"study_design_scores_gemma":[0.00027578985,0.000020813659,0.06368568,0.000008020347,0.00004744021,0.0000011307342,0.000036816913,0.0015618084,0.92470926,0.0014815249,0.008043685,0.00012800477],"about_ca_topic_score_codex":0.000011486182,"about_ca_topic_score_gemma":0.00004657472,"teacher_disagreement_score":0.13447757,"about_ca_system_score_codex":0.0000047330745,"about_ca_system_score_gemma":0.000053025135,"threshold_uncertainty_score":0.30718404},"labels":[],"label_agreement":null},{"id":"W1973102932","doi":"10.1016/j.devcel.2005.10.004","title":"Tracing the Sources of Cellular Variation","year":2005,"lang":"en","type":"review","venue":"Developmental Cell","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Biology; Tracing; Variation (astronomy); Computational biology; Evolutionary biology; Computer science","score_opus":0.015352628836875316,"score_gpt":0.24029602281005766,"score_spread":0.22494339397318233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973102932","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015544192,0.9964744,0.00037075698,0.0000034289603,0.000072120245,0.00023056017,0.000009098775,0.0000053335084,0.0012798732],"genre_scores_gemma":[0.0056325565,0.99075323,0.0010436026,0.000019129384,0.00029413757,0.000025831909,0.00036583957,0.00004152952,0.0018241468],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99872226,0.00012083265,0.0004745094,0.00032226418,0.00017159985,0.0001885264],"domain_scores_gemma":[0.99926573,0.000016304444,0.00036908055,0.00027651232,0.00003191127,0.000040446732],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026266568,0.00026774223,0.00050648546,0.00006316239,0.0000859978,0.00001607131,0.0003375764,0.00024902314,0.000056272173],"category_scores_gemma":[0.000007219736,0.00019125234,0.00036994202,0.00019059902,0.000046893292,0.0000015788537,0.00013922247,0.00010990485,0.000037258862],"study_design_candidate":"design_other","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":[0.000004227636,0.000070038244,0.000026465481,0.0021364891,0.0005097571,0.000002660847,0.00018411268,0.00011253452,0.0032411136,0.0000053565172,0.0009858324,0.99272144],"study_design_scores_gemma":[0.00006477909,0.000014213078,0.00001308032,0.00024152437,0.0003911748,0.000012715889,0.000032671538,0.000006464482,0.008646976,0.0000016389407,0.990344,0.00023077309],"about_ca_topic_score_codex":0.000004595565,"about_ca_topic_score_gemma":0.00000783553,"teacher_disagreement_score":0.99249065,"about_ca_system_score_codex":0.000043275297,"about_ca_system_score_gemma":0.00023054791,"threshold_uncertainty_score":0.7799044},"labels":[],"label_agreement":null},{"id":"W1973271480","doi":"10.1142/s021797920603576x","title":"MEAN FIELD MODEL OF THE GENETIC TOGGLE SWITCH","year":2006,"lang":"en","type":"article","venue":"International Journal of Modern Physics B","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"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 Calgary","funders":"","keywords":"Mean field theory; Computer science; Genetic algorithm; Field (mathematics); Exponential growth; Statistical physics; Applied mathematics; Algorithm; Simulation; Physics; Mathematics; Machine learning; Quantum mechanics","score_opus":0.008424201093510233,"score_gpt":0.23154503315862496,"score_spread":0.22312083206511474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973271480","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":[0.8339987,0.00038812173,0.16470869,0.00028538454,0.0001819972,0.000025293142,0.0000057251104,0.0000010661853,0.00040502],"genre_scores_gemma":[0.99697983,0.000034353237,0.0018016151,0.00013575424,0.0007821701,7.2063006e-7,0.0000041798576,0.000010889463,0.00025046186],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99915004,0.000020531475,0.0002913894,0.00009396365,0.0003607165,0.000083390805],"domain_scores_gemma":[0.99905914,0.000008993227,0.00032343002,0.0001916852,0.00039393193,0.000022812379],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007560335,0.00008052528,0.00011144579,0.000024772417,0.000021444188,0.00001224173,0.00048719882,0.0000498013,0.0000049509736],"category_scores_gemma":[0.000010790062,0.00006124693,0.00026070236,0.000042574575,0.000030864107,0.000005059327,0.000097949516,0.00007501373,6.493781e-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":[0.00003732932,0.000077704215,0.004287908,0.0000021601102,0.00019243335,0.0000011470427,0.000027782084,0.50488275,0.48273325,0.00041843965,0.001372263,0.005966842],"study_design_scores_gemma":[0.0006059235,0.000088008244,0.002751613,0.000030950843,0.00010287243,0.000033088156,0.000010928117,0.15742159,0.79001194,0.048122287,0.00066904054,0.00015178134],"about_ca_topic_score_codex":0.000013206127,"about_ca_topic_score_gemma":0.000022772452,"teacher_disagreement_score":0.34746113,"about_ca_system_score_codex":0.000016848579,"about_ca_system_score_gemma":0.000086974185,"threshold_uncertainty_score":0.24975775},"labels":[],"label_agreement":null},{"id":"W1973668822","doi":"10.1002/cjce.5450780220","title":"On the control of an unstable periodic state in the repeated fed‐batch operation of a biochemical system","year":2000,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Floquet theory; Control theory (sociology); Constant (computer programming); Mathematics; Stability (learning theory); Steady state (chemistry); Flow (mathematics); Volumetric flow rate; Control variable; Mechanics; Control (management); Chemistry; Physics; Computer science; Nonlinear system; Statistics","score_opus":0.003411290438718356,"score_gpt":0.17037732776155512,"score_spread":0.16696603732283677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973668822","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":[0.9989948,0.00045239052,0.00014655487,0.000253808,0.000019104342,0.000084549756,0.000008061774,0.0000012349628,0.000039485887],"genre_scores_gemma":[0.9998067,0.000005107576,0.000029301993,0.000059995105,0.00006904181,0.0000029449834,0.000006036763,0.0000105602585,0.000010325757],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99917704,0.00007968751,0.00033916003,0.00008509322,0.0001474699,0.00017156774],"domain_scores_gemma":[0.99941975,0.00003754104,0.000099415345,0.00027016582,0.00007585279,0.00009728273],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005944617,0.00009596861,0.00018052291,0.000044338136,0.0000358804,0.000020399259,0.00035326503,0.00006873615,0.000020183588],"category_scores_gemma":[0.0000654396,0.000053860167,0.000096032294,0.00015735022,0.00007344063,0.000004194935,0.0000050574663,0.00017087202,4.4059905e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007507513,0.000011885063,0.00008249328,0.000016876551,0.00008591959,0.0000071237937,0.00024587978,0.18029547,0.8187671,0.00008188743,0.00011919473,0.00021112741],"study_design_scores_gemma":[0.00063842133,0.00018238093,0.00022761857,0.00011908558,0.00007996631,0.00012654935,0.00012670671,0.0492213,0.9488033,0.000028688713,0.00031283015,0.00013312137],"about_ca_topic_score_codex":0.00057434547,"about_ca_topic_score_gemma":0.00019512442,"teacher_disagreement_score":0.13107416,"about_ca_system_score_codex":0.000052490723,"about_ca_system_score_gemma":0.00018774149,"threshold_uncertainty_score":0.2196354},"labels":[],"label_agreement":null},{"id":"W1974796209","doi":"10.1016/j.physleta.2007.03.074","title":"Chaos in a discrete model of a two-gene system","year":2007,"lang":"en","type":"article","venue":"Physics Letters A","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Physics; Chaotic; Synchronization of chaos; Statistical physics; CHAOS (operating system); Cooperativity; Synchronization (alternating current); Chaotic systems; Control theory (sociology); Topology (electrical circuits); Nonlinear system; Control (management); Genetics; Quantum mechanics; Biology; Computer science; Mathematics; Artificial intelligence","score_opus":0.009059035567962417,"score_gpt":0.2306244819100183,"score_spread":0.22156544634205588,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974796209","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":[0.86066103,0.000103413615,0.1389057,0.00005913937,0.000024473373,0.00008019521,0.0000062914896,0.0000059185336,0.00015384238],"genre_scores_gemma":[0.9977317,0.000005106759,0.0017261303,0.00021559458,0.00023103283,0.000007677207,0.00003305125,0.000019867737,0.000029864144],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991616,0.00002458961,0.0002160064,0.0002373744,0.00012696662,0.00023343822],"domain_scores_gemma":[0.99948084,0.0000048065117,0.00009695456,0.0003445491,0.000027790611,0.000045039433],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020042574,0.00011899805,0.0001809042,0.000040483093,0.000019066529,0.0000047270523,0.00013950118,0.000042890486,4.7799585e-7],"category_scores_gemma":[0.0000027405365,0.00012076463,0.00012822004,0.0001632288,0.000043866083,0.0000023387215,0.00006523487,0.000051442566,0.000002105394],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024295397,0.000020509367,0.0020809583,0.000023832261,0.00005082625,0.0000028068746,0.00004391479,0.08518664,0.91193235,0.00027664434,0.000073892916,0.00028330815],"study_design_scores_gemma":[0.0006158858,0.00002882043,0.000572394,0.000028147655,0.000047202808,0.0000029188132,0.000038500366,0.05599839,0.9423278,0.00008510155,0.00003975886,0.00021509892],"about_ca_topic_score_codex":0.000028567023,"about_ca_topic_score_gemma":0.00002993046,"teacher_disagreement_score":0.13717957,"about_ca_system_score_codex":0.000025427766,"about_ca_system_score_gemma":0.000018782881,"threshold_uncertainty_score":0.49246386},"labels":[],"label_agreement":null},{"id":"W1975085341","doi":"10.1063/1.4810923","title":"Introduction to Focus Issue: Quantitative Approaches to Genetic Networks","year":2013,"lang":"en","type":"article","venue":"Chaos An Interdisciplinary Journal of Nonlinear Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computational biology; Boolean network; Computer science; Gene regulatory network; Gene; Biological network; Function (biology); Systems biology; Focus (optics); Biology; Theoretical computer science; Boolean function; Gene expression; Genetics; Physics; Algorithm","score_opus":0.029936228284847953,"score_gpt":0.29985403540756805,"score_spread":0.2699178071227201,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975085341","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":[0.91568273,0.00031904885,0.07831909,0.004846038,0.00053171243,0.00022241757,0.0000019292177,0.000005498682,0.00007151415],"genre_scores_gemma":[0.9288656,0.000018554532,0.066793874,0.00014006777,0.0038824452,0.000011432449,0.000004572123,0.000022250635,0.00026119998],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99815214,0.00007983469,0.00048863183,0.0005174857,0.00036818426,0.00039369924],"domain_scores_gemma":[0.9981895,0.000009439545,0.0002380831,0.0005189812,0.0005262241,0.0005177636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073625863,0.00019511652,0.0002594469,0.00033464105,0.00029443545,0.00013786263,0.0008576565,0.00007408293,0.00009412779],"category_scores_gemma":[0.00008109885,0.00016210027,0.00013944019,0.00082268607,0.00025795196,0.000056163946,0.0007131568,0.00015329746,0.000087002314],"study_design_candidate":"simulation_or_modeling","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":[0.00037510102,0.0004491381,0.0014215057,0.000015358084,0.00016858829,0.000018645633,0.0028595552,0.43448797,0.46584734,0.00006806242,0.023443718,0.07084504],"study_design_scores_gemma":[0.0017490423,0.029033497,0.09697216,0.0002870306,0.000354038,0.0019005238,0.017146079,0.53433424,0.28434914,0.0014358107,0.029583177,0.0028552772],"about_ca_topic_score_codex":0.0000048586207,"about_ca_topic_score_gemma":0.000020822079,"teacher_disagreement_score":0.18149818,"about_ca_system_score_codex":0.00005880114,"about_ca_system_score_gemma":0.00012975639,"threshold_uncertainty_score":0.6610257},"labels":[],"label_agreement":null},{"id":"W1975154158","doi":"10.1016/j.jtbi.2005.06.020","title":"Modelling the evolution of genetic regulatory networks","year":2005,"lang":"en","type":"article","venue":"Journal of Theoretical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":49,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Cancer Agency","funders":"","keywords":"Evolvability; Gene regulatory network; Degree distribution; Computer science; Network topology; Redundancy (engineering); Biological network; Gene; Complex network; Computational biology; Biology; Genetics; Gene expression","score_opus":0.005096151102467836,"score_gpt":0.22185937429158034,"score_spread":0.2167632231891125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975154158","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":[0.6867155,0.0072017033,0.3053402,0.00036246184,0.00012837334,0.000045870212,0.0000012096058,0.0000019045415,0.00020282892],"genre_scores_gemma":[0.9944809,0.00036752227,0.003861964,0.00009311734,0.001148127,0.0000011549587,0.0000028187249,0.000013224158,0.000031171552],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99863756,0.00028205835,0.00057966635,0.00015311281,0.00012018438,0.00022742306],"domain_scores_gemma":[0.9989083,0.00005779615,0.00038697658,0.0003462477,0.00021977191,0.00008094428],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007445306,0.00012443044,0.00026339755,0.000064103995,0.0000532348,0.00000564734,0.00037816897,0.00022611192,0.000051220257],"category_scores_gemma":[0.000069550806,0.000078777666,0.0003019943,0.00011951424,0.00070658757,0.0000027125072,0.000089125504,0.00017396694,0.0000021798385],"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":[0.00017855295,0.000052305295,0.0024328462,0.0000037055577,0.00022781236,9.562502e-7,0.00001662808,0.89163226,0.03784085,0.06400606,0.00046700393,0.0031410274],"study_design_scores_gemma":[0.0015612376,0.0019466483,0.0031148405,0.00006095341,0.0007689464,0.000516896,0.00021060604,0.87114614,0.039238334,0.06467281,0.016201654,0.0005609008],"about_ca_topic_score_codex":0.0000024481562,"about_ca_topic_score_gemma":0.0000015724513,"teacher_disagreement_score":0.30776545,"about_ca_system_score_codex":0.000040537816,"about_ca_system_score_gemma":0.00008101952,"threshold_uncertainty_score":0.321246},"labels":[],"label_agreement":null},{"id":"W1976177296","doi":"10.1109/isb.2012.6314104","title":"Alternating weighted least squares parameter estimation for biological S-systems","year":2012,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nonlinear system; Estimation theory; Non-linear least squares; Least-squares function approximation; Ordinary differential equation; Applied mathematics; Mathematics; Set (abstract data type); Mathematical optimization; Generalized least squares; Ordinary least squares; Nonlinear regression; Action (physics); Computer science; Differential equation; Algorithm; Regression analysis; Statistics; Mathematical analysis","score_opus":0.02627640407889102,"score_gpt":0.2762724610284379,"score_spread":0.24999605694954688,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976177296","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":[0.8305507,0.00087091513,0.16790809,0.000032905227,0.00017351923,0.00017645568,0.0000053465205,0.000018769215,0.00026333155],"genre_scores_gemma":[0.98409575,0.00001548872,0.014493421,0.000064094485,0.00058285333,0.00006496148,0.00019745169,0.00001323121,0.00047271885],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992155,0.00005292424,0.00018655157,0.00019899762,0.00007354472,0.00027250135],"domain_scores_gemma":[0.99955326,0.000028704902,0.0000771591,0.00020311834,0.000057175166,0.00008055917],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022762924,0.000114503964,0.00012615138,0.000028848615,0.00006757206,0.000024524157,0.000097682096,0.00012388271,0.00002283152],"category_scores_gemma":[0.00006591132,0.000087042645,0.000112574504,0.000053599826,0.000028028197,0.000004064071,0.000042783107,0.000027051123,0.000014229658],"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":[0.00020785813,0.0003833456,0.25806656,0.00009341919,0.0009035195,8.5938825e-7,0.00011239923,0.018975873,0.656713,0.0051217484,0.015451045,0.043970354],"study_design_scores_gemma":[0.0017293141,0.0007766326,0.021184161,0.000032937198,0.00023001425,0.00005560642,0.00032422633,0.5089677,0.36935735,0.00057786074,0.09551999,0.0012441971],"about_ca_topic_score_codex":0.000010177586,"about_ca_topic_score_gemma":0.0000027581025,"teacher_disagreement_score":0.4899918,"about_ca_system_score_codex":0.00000994543,"about_ca_system_score_gemma":0.000008472692,"threshold_uncertainty_score":0.3549496},"labels":[],"label_agreement":null},{"id":"W1976189901","doi":"10.1073/pnas.0914302107","title":"Exploiting the determinants of stochastic gene expression in <i>Saccharomyces cerevisiae</i> for genome-wide prediction of expression noise","year":2010,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Gene; Biology; Computational biology; Noise (video); Gene expression; Context (archaeology); Genetics; Saccharomyces cerevisiae; Gene regulatory network; Regulation of gene expression; Genome; Computer science; Artificial intelligence","score_opus":0.022501555469439435,"score_gpt":0.2743315524759086,"score_spread":0.2518299970064692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976189901","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":[0.9992644,0.00024025278,0.00005529575,0.00010433892,0.000019963923,0.00024708555,0.000025979787,0.0000016549925,0.000041009287],"genre_scores_gemma":[0.997591,0.000030358357,0.0022115826,0.000020420606,0.0000971163,0.00002888361,9.4473614e-7,0.0000052713626,0.000014374442],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998693,0.000009988798,0.0004482509,0.0002298044,0.0004939508,0.00012499308],"domain_scores_gemma":[0.99885654,0.00007771713,0.0007531687,0.000025166846,0.00026537394,0.00002200444],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011649336,0.0000893685,0.00017285509,0.00009616122,0.00010608541,0.0000062169433,0.0006190932,0.00010793336,0.0000026797231],"category_scores_gemma":[0.0005423275,0.000054684533,0.00010875261,0.00029191936,0.0004188403,0.000028044378,0.00016825595,0.0000866325,4.3016705e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026817725,0.000026938826,0.033314884,0.00006241051,0.0000065474383,8.094597e-10,0.0000819958,0.0011086179,0.96515006,0.00003283132,0.00004272743,0.00014616609],"study_design_scores_gemma":[0.00017031196,0.00004888408,0.043189254,0.00010743353,0.000016527598,0.0000017321541,0.00015795868,0.0018068607,0.95338666,0.0010448333,0.00002320221,0.00004636155],"about_ca_topic_score_codex":0.0000013304497,"about_ca_topic_score_gemma":2.8644106e-7,"teacher_disagreement_score":0.011763424,"about_ca_system_score_codex":0.000005940262,"about_ca_system_score_gemma":0.000032219286,"threshold_uncertainty_score":0.22299705},"labels":[],"label_agreement":null},{"id":"W1976711793","doi":"10.1063/1.1802495","title":"Reducing a chemical master equation by invariant manifold methods","year":2004,"lang":"en","type":"article","venue":"The Journal of Chemical Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"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 Lethbridge","funders":"","keywords":"Master equation; Eigenvalues and eigenvectors; Invariant manifold; Ordinary differential equation; Manifold (fluid mechanics); Invariant (physics); Differential equation; Mathematics; Dimension (graph theory); Simple (philosophy); Applied mathematics; Partial differential equation; Mathematical analysis; Physics; Pure mathematics; Quantum mechanics; Mathematical physics","score_opus":0.022241272789093904,"score_gpt":0.27536350407901,"score_spread":0.2531222312899161,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976711793","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":[0.8697989,0.00056242314,0.12889504,0.00049159396,0.000059335038,0.0000498556,0.0000016379763,0.0000034368657,0.00013778925],"genre_scores_gemma":[0.98722595,0.0000540205,0.011520615,0.00024633127,0.0008786742,0.0000011532602,0.000015878111,0.000021857459,0.000035499466],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989865,0.00010756328,0.00036148328,0.00013231473,0.00022343625,0.00018871714],"domain_scores_gemma":[0.9991523,0.00003394484,0.00031385155,0.0002836093,0.00012502415,0.000091297115],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059376494,0.00014052153,0.00021120597,0.000013384649,0.000031893862,0.000017330503,0.00032233528,0.00009810805,0.000006990792],"category_scores_gemma":[0.00007187397,0.000099549325,0.00019922962,0.00013202352,0.00006626725,0.000007978847,0.00010099692,0.0002150658,0.0000036826596],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007560066,0.000064330496,0.0000070666356,0.0000057911375,0.00013769061,8.4631864e-7,0.00006444019,0.0017220249,0.9940178,0.00007231706,0.0015279021,0.002304186],"study_design_scores_gemma":[0.00044460155,0.000057407928,0.000005768237,0.000020899304,0.0001733211,0.000056019548,0.000021307576,0.00028637282,0.99414295,0.0041279932,0.00054581265,0.0001175426],"about_ca_topic_score_codex":0.0000039101296,"about_ca_topic_score_gemma":8.450497e-8,"teacher_disagreement_score":0.11742708,"about_ca_system_score_codex":0.000049104052,"about_ca_system_score_gemma":0.000070644666,"threshold_uncertainty_score":0.40595037},"labels":[],"label_agreement":null},{"id":"W1977055260","doi":"10.1042/bse0450177","title":"Sensitivity analysis: from model parameters to system behaviour","year":2008,"lang":"en","type":"review","venue":"Essays in Biochemistry","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":103,"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 Waterloo","funders":"","keywords":"Sensitivity (control systems); Parametrization (atmospheric modeling); Interpretation (philosophy); Set (abstract data type); Range (aeronautics); Computer science; Uncertainty analysis; Econometrics; Biological system; Mathematics; Engineering; Physics; Simulation; Biology","score_opus":0.019988529481196313,"score_gpt":0.2766529967093643,"score_spread":0.25666446722816794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977055260","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033599656,0.96280855,0.0021363785,0.0000059570643,0.00010016989,0.00038557316,0.0005681407,0.00004566242,0.00034992717],"genre_scores_gemma":[0.09287857,0.89926916,0.0027922036,0.000037282996,0.0003302112,0.00018273664,0.0039357855,0.0001160926,0.00045794883],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99606055,0.00029162478,0.0009443819,0.0017232659,0.0003834865,0.0005966973],"domain_scores_gemma":[0.9971018,0.000046925292,0.00043625556,0.001993251,0.00009465826,0.00032711917],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003264037,0.0008531294,0.002306085,0.00033103116,0.00008847596,0.00004488374,0.0005874917,0.0012730067,0.0000064303026],"category_scores_gemma":[0.000071322946,0.00087366806,0.0017131341,0.0012784236,0.000098725155,0.0000027945403,0.00043049853,0.00041562662,0.00003052006],"study_design_candidate":"not_applicable","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":[0.00032926563,0.0021150396,0.012544951,0.025619172,0.057852138,0.0028310423,0.0003810113,0.4157114,0.029111601,0.00004453494,0.038236525,0.4152233],"study_design_scores_gemma":[0.0050128265,0.0004930347,0.00069505157,0.047224503,0.13783732,0.0018469574,0.0012441741,0.07202234,0.15469015,0.000081629696,0.5453307,0.033521328],"about_ca_topic_score_codex":0.00018157269,"about_ca_topic_score_gemma":0.00012496879,"teacher_disagreement_score":0.50709414,"about_ca_system_score_codex":0.00031457152,"about_ca_system_score_gemma":0.00040328727,"threshold_uncertainty_score":0.9993714},"labels":[],"label_agreement":null},{"id":"W1977101885","doi":"10.1007/s00354-009-0115-7","title":"Evolutionary Synthesis of Stochastic Gene Network Models Using Feature-based Search Spaces","year":2011,"lang":"en","type":"article","venue":"New Generation Computing","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Fitness function; Genetic programming; Modular design; Series (stratigraphy); Feature (linguistics); Function (biology); Noise (video); Fitness approximation; Set (abstract data type); Stochastic modelling; Measure (data warehouse); Artificial intelligence; Gene regulatory network; Genetic network; Gene expression programming; Genetic algorithm; Machine learning; Data mining; Mathematics; Gene","score_opus":0.049398231280847735,"score_gpt":0.25364821949205335,"score_spread":0.2042499882112056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977101885","genre_codex":"methods","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":[0.42405325,0.0009565582,0.57471365,0.000017483831,0.00010406829,0.00008322634,0.0000023277983,0.000010815054,0.00005860922],"genre_scores_gemma":[0.85702986,0.0000055195073,0.14143158,0.00004747931,0.0013425968,0.0000018277033,0.00006520496,0.000024631354,0.00005129538],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99871814,0.0001460371,0.00026133898,0.0003714577,0.00021798947,0.00028502155],"domain_scores_gemma":[0.9991912,0.000021975551,0.00016019166,0.00034525595,0.0001798153,0.00010154945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027495364,0.00016996513,0.00020787655,0.00007773555,0.00018876758,0.000018752093,0.0001665857,0.00014994763,0.000019043238],"category_scores_gemma":[0.000025188556,0.00018226878,0.00013819512,0.0002480362,0.000050883915,0.000006062947,0.00009420384,0.000072119205,0.0000013788476],"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":[0.000022728691,0.000021874035,0.00054851634,0.0000064815954,0.00007619848,5.4672086e-7,0.000034906276,0.8534319,0.14289191,0.000065775006,0.000972388,0.0019267737],"study_design_scores_gemma":[0.00014992357,0.000052149062,0.00023031746,0.000019418349,0.00007012183,0.000004409369,0.000011775339,0.8442202,0.15498886,0.00008160213,0.000018294815,0.0001529095],"about_ca_topic_score_codex":0.0000801823,"about_ca_topic_score_gemma":0.00002195605,"teacher_disagreement_score":0.43328208,"about_ca_system_score_codex":0.000031165328,"about_ca_system_score_gemma":0.00027544922,"threshold_uncertainty_score":0.74327046},"labels":[],"label_agreement":null},{"id":"W1977594523","doi":"10.1016/j.pbiomolbio.2004.03.001","title":"Reaction–diffusion models of development with state-dependent chemical diffusion coefficients","year":2004,"lang":"en","type":"review","venue":"Progress in Biophysics and Molecular Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":56,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Diffusion; Statistical physics; Juxtacrine signalling; Effective diffusion coefficient; Reaction–diffusion system; Biological system; Chemistry; Physics; Thermodynamics; Biology","score_opus":0.011335630902915098,"score_gpt":0.27790696094069417,"score_spread":0.26657133003777905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977594523","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.099457845,0.8928852,0.0069700126,0.000003246329,0.000058249952,0.00057059113,0.00002160966,0.000009897627,0.000023323493],"genre_scores_gemma":[0.1175344,0.8786567,0.0025967245,0.00001294425,0.000045136996,0.00011434089,0.0009458512,0.0000780828,0.000015842179],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977245,0.00011273247,0.00065591175,0.00086766836,0.00021350685,0.00042569073],"domain_scores_gemma":[0.99881035,0.000010541597,0.00046830764,0.00047767253,0.00011822954,0.00011490612],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002122412,0.0005132965,0.001055526,0.00021225623,0.00004885732,0.000013765609,0.00028684628,0.00054795307,7.4903255e-7],"category_scores_gemma":[0.000005322897,0.00040037965,0.00020010216,0.0003223622,0.00033721462,0.0000031691968,0.00043334943,0.00021820156,0.0000011288296],"study_design_candidate":"design_other","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":[0.00009822729,0.00050761935,0.00022061483,0.002630531,0.00043893626,0.00002453019,0.000045420707,0.00006485135,0.029810017,0.0003752419,0.0000011281926,0.9657829],"study_design_scores_gemma":[0.01095567,0.0039078034,0.00020551024,0.031618487,0.003978564,0.0004544075,0.00013332315,0.0005888783,0.38777167,0.0048507857,0.5465325,0.0090023745],"about_ca_topic_score_codex":0.000009704684,"about_ca_topic_score_gemma":0.0000075504554,"teacher_disagreement_score":0.9567805,"about_ca_system_score_codex":0.00007512667,"about_ca_system_score_gemma":0.00033699727,"threshold_uncertainty_score":0.9998448},"labels":[],"label_agreement":null},{"id":"W1979521110","doi":"10.1089/cmb.2007.0038","title":"A Physical Analogy of the Genetic Toggle Switch","year":2007,"lang":"en","type":"article","venue":"Journal of Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Calgary","funders":"","keywords":"Analogy; Statistical physics; Probability distribution; Computer science; Field (mathematics); Stochastic modelling; Stochastic process; Biological system; Physics; Mathematics; Biology; Statistics","score_opus":0.006131849924920689,"score_gpt":0.2622982573992441,"score_spread":0.25616640747432345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979521110","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":[0.96100163,0.00053470244,0.037937906,0.00020681054,0.0001744232,0.000036086167,0.0000028249058,9.498089e-7,0.00010464681],"genre_scores_gemma":[0.99526125,0.0000121775975,0.0039876048,0.00015623811,0.00054432824,3.2352355e-7,0.0000073089627,0.000006642533,0.000024127345],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99914587,0.00008197987,0.0003904019,0.000107133164,0.00013367065,0.00014095604],"domain_scores_gemma":[0.9990015,0.00006683908,0.0004211648,0.00013348214,0.00032683794,0.00005014333],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029781167,0.00008385516,0.00020346403,0.000071998395,0.00003649668,0.0000027596707,0.00024623537,0.000085117375,0.000009229176],"category_scores_gemma":[0.000055558747,0.000056884608,0.00025686764,0.00016755813,0.00014419995,0.0000015951542,0.000068386835,0.000089434005,0.0000015064611],"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":[0.00023604435,0.00024414234,0.09952688,0.000011743749,0.00063664425,0.0000070205338,0.00009079949,0.1373328,0.7458142,0.00156199,0.0015225582,0.013015201],"study_design_scores_gemma":[0.001727808,0.0016673162,0.787955,0.000023994491,0.0002623691,0.00069853885,0.000100849065,0.0038667878,0.16157252,0.028429639,0.013368852,0.0003263378],"about_ca_topic_score_codex":0.0000024061615,"about_ca_topic_score_gemma":0.000010518271,"teacher_disagreement_score":0.6884281,"about_ca_system_score_codex":0.000012429999,"about_ca_system_score_gemma":0.0001286601,"threshold_uncertainty_score":0.2319687},"labels":[],"label_agreement":null},{"id":"W1980538968","doi":"10.1002/cplx.20100","title":"Modeling pathways of differentiation in genetic regulatory networks with Boolean networks","year":2005,"lang":"en","type":"article","venue":"Complexity","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"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 Calgary","funders":"National Institutes of Health; National Science Foundation","keywords":"Attractor; Observable; Cellular differentiation; Nonlinear system; Perturbation (astronomy); Computer science; Gene regulatory network; Variety (cybernetics); Gene; Topology (electrical circuits); Biology; Biological system; Mathematics; Physics; Genetics; Gene expression; Artificial intelligence; Mathematical analysis","score_opus":0.02102476204328716,"score_gpt":0.21903822916844048,"score_spread":0.19801346712515333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980538968","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":[0.78884226,0.0014816303,0.20939942,0.000017291726,0.000030510957,0.00011816747,0.0000019588304,0.000011859833,0.000096924],"genre_scores_gemma":[0.99581033,0.0001066277,0.0034799536,0.000055939396,0.000358055,0.000011000072,0.00011703205,0.000029459346,0.000031581734],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99867713,0.00010076576,0.00037126997,0.0003819912,0.0001595379,0.00030928914],"domain_scores_gemma":[0.99914604,0.0000060759057,0.00012606163,0.0005545064,0.000085594475,0.000081704085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017243902,0.00019339348,0.0002700691,0.00006939558,0.000060522743,0.000012216265,0.00020931785,0.00015580644,0.0000200346],"category_scores_gemma":[0.0000066726257,0.00018508373,0.000106694104,0.00019220261,0.00011046685,0.000004923873,0.00010476612,0.000120095254,0.0000010652889],"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":[0.00006822793,0.00006596174,0.024398293,0.000008381385,0.000054304972,8.201013e-7,0.000024592899,0.9682709,0.003936937,0.000107185835,0.000059464015,0.0030049533],"study_design_scores_gemma":[0.0004603788,0.00007631703,0.08611763,0.000024001201,0.000030374733,0.000004086509,0.000021359525,0.9114164,0.0014661066,0.00010680512,0.00007801714,0.00019853379],"about_ca_topic_score_codex":0.000026981881,"about_ca_topic_score_gemma":0.001063279,"teacher_disagreement_score":0.20696811,"about_ca_system_score_codex":0.000035714293,"about_ca_system_score_gemma":0.000037368056,"threshold_uncertainty_score":0.75474954},"labels":[],"label_agreement":null},{"id":"W1980789113","doi":"10.1103/physreve.80.031129","title":"Long delay times in reaction rates increase intrinsic fluctuations","year":2009,"lang":"en","type":"article","venue":"Physical Review E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"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 Waterloo","funders":"","keywords":"Probabilistic logic; Statistical physics; Limit (mathematics); Nonlinear system; Markov process; Stochastic process; Coupling (piping); Characterization (materials science); Dynamics (music); Simple (philosophy); Noise (video); Master equation; Reaction rate; Biological system; Mathematics; Physics; Computer science; Chemistry; Mathematical analysis; Statistics; Materials science; Quantum mechanics","score_opus":0.008120647896126076,"score_gpt":0.2870797801433196,"score_spread":0.2789591322471935,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980789113","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":[0.9749872,0.023088675,0.00015678022,0.00056197256,0.000017589884,0.00018892744,0.0000013900908,0.0000107092,0.0009867441],"genre_scores_gemma":[0.9892313,0.009555327,0.00006486092,0.00065578683,0.00024203493,0.000016231754,0.000116093295,0.0000074338054,0.00011094081],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99926865,0.00009132699,0.00017213433,0.00023144121,0.00009342423,0.00014303421],"domain_scores_gemma":[0.9995305,0.000012636776,0.00006244314,0.00028278725,0.000048544927,0.000063070445],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001350957,0.0001110899,0.00020974183,0.000029190342,0.000029859528,0.00000789274,0.00009211294,0.000031377414,0.000016771592],"category_scores_gemma":[0.00011540153,0.000098561744,0.00013181033,0.00026452824,0.0000208744,0.000005022677,0.000025354419,0.00006911979,0.000052277323],"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":[0.00003515294,0.0006470507,0.0027439434,0.00021427438,0.0001312947,0.000014537022,0.000027439943,0.00040815165,0.5591073,0.0010930164,0.0076173893,0.42796043],"study_design_scores_gemma":[0.0022474434,0.0011853488,0.6285252,0.002573081,0.001564919,0.00008820589,0.000028843733,0.0062278546,0.19700485,0.01354884,0.14457904,0.0024263896],"about_ca_topic_score_codex":0.000010465998,"about_ca_topic_score_gemma":0.000021847789,"teacher_disagreement_score":0.62578124,"about_ca_system_score_codex":0.000017488004,"about_ca_system_score_gemma":0.00003098055,"threshold_uncertainty_score":0.40192315},"labels":[],"label_agreement":null},{"id":"W1980804701","doi":"10.1016/j.procs.2012.04.040","title":"Measuring Gene Expression Noise in Early Drosophila Embryos: Nucleus-to-nucleus Variability","year":2012,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"British Columbia Institute of Technology","funders":"National Institute of General Medical Sciences; National Institutes of Health; National Science Foundation","keywords":"Noise (video); Computer science; Blastoderm; Biological system; Nucleus; Expression (computer science); Biology; Computational biology; Embryo; Cell biology; Artificial intelligence; Embryogenesis","score_opus":0.014430564874460513,"score_gpt":0.2245146065377121,"score_spread":0.2100840416632516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980804701","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":[0.96037436,0.00013620005,0.038738873,0.000054330965,0.00036308914,0.00019494975,0.0000020877499,0.000025911108,0.00011022929],"genre_scores_gemma":[0.95430976,0.000008272696,0.044771343,0.0001602108,0.00069168356,0.00002358924,0.0000031650754,0.000017419601,0.00001453209],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99785864,0.00006960485,0.00027131438,0.0007245455,0.00041458255,0.000661317],"domain_scores_gemma":[0.99870974,0.000013468497,0.00007936307,0.0006574062,0.00015801624,0.00038200695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013848781,0.00019226983,0.0001843876,0.00015658014,0.0001648829,0.00008096962,0.0007290427,0.00009632009,0.000004204416],"category_scores_gemma":[0.000118559365,0.00018575258,0.000072601506,0.0007846044,0.00016524618,0.00004150959,0.0007407955,0.00010197525,0.000031211443],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013900513,0.0000920763,0.13860661,0.00001084667,0.0000054660654,9.149985e-7,0.00046735402,0.002354105,0.85626197,0.000018136225,0.00006389035,0.0021047336],"study_design_scores_gemma":[0.00025460005,0.00008903904,0.41815355,0.000028958513,0.000010611112,0.000012341524,0.000006542045,0.00557586,0.57484907,0.000089077774,0.00057333155,0.00035702958],"about_ca_topic_score_codex":0.0000073273454,"about_ca_topic_score_gemma":0.0000028029651,"teacher_disagreement_score":0.28141293,"about_ca_system_score_codex":0.000067279325,"about_ca_system_score_gemma":0.00013858237,"threshold_uncertainty_score":0.75747705},"labels":[],"label_agreement":null},{"id":"W1981248236","doi":"10.1103/physreve.80.062902","title":"Contrasting methods for symbolic analysis of biological regulatory networks","year":2009,"lang":"en","type":"article","venue":"Physical Review E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Symbolic data analysis; Symbolic dynamics; Contrast (vision); Monotonic function; Dynamics (music); Theoretical computer science; The Symbolic; Statistical physics; Mathematics; Artificial intelligence; Pure mathematics; Physics; Psychology","score_opus":0.026522316134157262,"score_gpt":0.3723549596749134,"score_spread":0.3458326435407561,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981248236","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":[0.5347124,0.15519299,0.30863667,0.00025709966,0.000061750274,0.00072177,0.000014437801,0.00003001318,0.00037286873],"genre_scores_gemma":[0.98653257,0.0062530246,0.005952924,0.0007323287,0.0003091746,0.00003164746,0.00015526719,0.000010716807,0.000022330098],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986148,0.0002433624,0.0003853784,0.0003981594,0.00008938673,0.0002689532],"domain_scores_gemma":[0.9989351,0.00011032707,0.00023205549,0.00048453643,0.00013920564,0.00009878387],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006531988,0.00018328264,0.00087168335,0.000052823576,0.0000459719,0.000005708062,0.00021641374,0.00008080525,0.000009562267],"category_scores_gemma":[0.0002942524,0.00014538129,0.0010037388,0.00067732827,0.000071352224,0.0000020549007,0.000042249474,0.00006337656,7.161639e-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":[0.0000781051,0.00038726776,0.0020451138,0.00023597524,0.0040714378,5.6288803e-7,0.000015775673,0.009797973,0.5368579,0.004187847,0.0014753755,0.44084662],"study_design_scores_gemma":[0.0019313948,0.002908039,0.20195328,0.0011864343,0.03694385,0.0000093942235,0.00002915559,0.5088895,0.15512298,0.007693727,0.08068144,0.0026508141],"about_ca_topic_score_codex":7.859502e-7,"about_ca_topic_score_gemma":6.944671e-7,"teacher_disagreement_score":0.49909154,"about_ca_system_score_codex":0.0000093690205,"about_ca_system_score_gemma":0.000021068176,"threshold_uncertainty_score":0.5928477},"labels":[],"label_agreement":null},{"id":"W1982349563","doi":"10.1109/tbcas.2013.2291398","title":"Stochastic Multiple-Valued Gene Networks","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Circuits and Systems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":37,"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 Alberta","funders":"","keywords":"Probabilistic logic; Gene regulatory network; Computer science; Boolean network; Granularity; Theoretical computer science; Binary number; Algorithm; Network dynamics; Boolean function; Mathematics; Gene; Biology; Artificial intelligence; Discrete mathematics; Genetics","score_opus":0.01201071772024575,"score_gpt":0.22450434465427663,"score_spread":0.21249362693403087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1982349563","genre_codex":"methods","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":[0.14191087,0.0005950771,0.85637826,0.000033978573,0.00080348836,0.0001814339,0.000016604794,0.000029265691,0.00005100895],"genre_scores_gemma":[0.9986347,0.00006135076,0.000042593838,0.00011488395,0.00062377536,0.000049151775,0.00003913543,0.00003119599,0.00040324614],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998388,0.00017437588,0.00033756747,0.0004847021,0.00027665426,0.0003387302],"domain_scores_gemma":[0.99909323,0.00004958628,0.00007984671,0.00039238302,0.00006130402,0.0003236639],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003976178,0.00021778315,0.00028999848,0.00010704678,0.00020904337,0.000046104753,0.00014794387,0.00030057807,0.000014094836],"category_scores_gemma":[0.000015860198,0.00018973916,0.0001386662,0.00019635743,0.00017595514,0.0000032900728,0.0000026816806,0.00015018601,0.000012626336],"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":[0.00013866293,0.0006794481,0.00028204516,0.00015143442,0.0012338473,0.0000106991765,0.00012968779,0.5831944,0.2862423,0.0001411276,0.0025427416,0.12525365],"study_design_scores_gemma":[0.002369787,0.00091430725,0.000593513,0.00009006535,0.0002765893,0.00014956389,0.00008730516,0.9763734,0.005646694,0.00001533727,0.012736421,0.0007470473],"about_ca_topic_score_codex":0.0000300114,"about_ca_topic_score_gemma":0.000017153776,"teacher_disagreement_score":0.8567238,"about_ca_system_score_codex":0.000017448325,"about_ca_system_score_gemma":0.000028971013,"threshold_uncertainty_score":0.77373385},"labels":[],"label_agreement":null},{"id":"W1982813016","doi":"10.1016/j.copbio.2006.08.004","title":"Accommodating space, time and randomness in network simulation","year":2006,"lang":"en","type":"review","venue":"Current Opinion in Biotechnology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Randomness; Computer science; Scale (ratio); Bridge (graph theory); Range (aeronautics); Distributed computing; Biology; Physics; Aerospace engineering; Mathematics; Engineering","score_opus":0.03420671544272026,"score_gpt":0.34480268650596435,"score_spread":0.3105959710632441,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1982813016","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005609004,0.9974872,0.00054595707,0.000033239125,0.0007027733,0.000600313,0.000016139958,0.000030646646,0.000022829572],"genre_scores_gemma":[0.00070843083,0.9969453,0.00019779765,0.000002349752,0.00064190006,0.00007991483,0.0013481149,0.000048491667,0.000027704122],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976403,0.00028316662,0.0007687062,0.00076217164,0.00010081808,0.00044482478],"domain_scores_gemma":[0.99891615,0.000070615926,0.0003975488,0.00055170077,0.00002543918,0.00003853659],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00042547562,0.00042677665,0.0012116537,0.00049222034,0.000051006384,0.000021741236,0.00031031817,0.0013261155,0.0000064822952],"category_scores_gemma":[0.000075726086,0.0004190962,0.00020272854,0.00084817613,0.00013606397,0.0000041123258,0.00038871152,0.0005084207,0.000012237573],"study_design_candidate":"not_applicable","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":[0.000016273621,0.00006173887,0.0003960345,0.0020878674,0.000052779917,8.4285716e-7,0.0000023147782,0.01485284,0.000014912227,0.0000962724,0.0010127651,0.9814054],"study_design_scores_gemma":[0.00064729917,0.000033066426,0.00005274134,0.0031710914,0.00006352228,0.000009496127,0.0000015064109,0.0040617506,0.0000072699054,0.00007997687,0.99146277,0.00040948953],"about_ca_topic_score_codex":0.000009136313,"about_ca_topic_score_gemma":0.00002659041,"teacher_disagreement_score":0.99045,"about_ca_system_score_codex":0.00006272892,"about_ca_system_score_gemma":0.00008363666,"threshold_uncertainty_score":0.9999704},"labels":[],"label_agreement":null},{"id":"W1982814315","doi":"10.1007/s00285-010-0394-0","title":"Model of cell signal transduction in a three-dimensional domain","year":2011,"lang":"en","type":"article","venue":"Journal of Mathematical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Cytosol; Cascade; Signalling; Signal transduction; Cell signaling; Biophysics; Intracellular; Function (biology); Compartment (ship); SIGNAL (programming language); Cell biology; Enzyme; Cellular compartment; Biological system; Biology; Physics; Cell; Chemistry; Biochemistry; Computer science","score_opus":0.02412124539745042,"score_gpt":0.23521961353770018,"score_spread":0.21109836814024976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1982814315","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":[0.93532187,0.00026503718,0.06393872,0.00003463659,0.00002887575,0.000047066267,0.0000020946243,0.0000010894535,0.00036058403],"genre_scores_gemma":[0.9593355,0.000015897935,0.040527895,0.000023968762,0.00006373514,0.0000014817606,0.0000026167056,0.000008425196,0.000020453535],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989782,0.00008310764,0.0005667749,0.00012199309,0.000098000746,0.00015191882],"domain_scores_gemma":[0.9994067,0.000019772466,0.0002733898,0.0001358815,0.00010091343,0.000063318366],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005187904,0.00010199596,0.0003155904,0.000102406186,0.000012242081,0.0000013184791,0.00015478686,0.00017481942,0.00020069389],"category_scores_gemma":[0.000020725161,0.000077323704,0.00020393866,0.000079665995,0.000118817814,0.000003220523,0.00003094487,0.0001097848,0.0000030920135],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020600884,0.00031501165,0.0013015516,0.000023090734,0.000073050396,0.0000033517608,0.00009143084,0.001701555,0.99477077,0.0012478838,0.00004653129,0.00021978623],"study_design_scores_gemma":[0.0015196756,0.0013292157,0.0008406104,0.00005393868,0.00013597166,0.00016968454,0.00008295818,0.015546735,0.75408137,0.2259382,0.000058221063,0.00024339814],"about_ca_topic_score_codex":0.0000015150064,"about_ca_topic_score_gemma":0.000011155662,"teacher_disagreement_score":0.24068937,"about_ca_system_score_codex":0.000009844463,"about_ca_system_score_gemma":0.0000746276,"threshold_uncertainty_score":0.31531692},"labels":[],"label_agreement":null},{"id":"W1982915164","doi":"10.1371/journal.pone.0085864","title":"Pooled Screening for Synergistic Interactions Subject to Blocking and Noise","year":2014,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; Ottawa Hospital; McGill University","funders":"Ottawa Hospital Research Institute","keywords":"Pooling; Set (abstract data type); Computer science; Noise (video); Replication (statistics); Bayesian probability; Blocking (statistics); Computational biology; Biology; Statistics; Artificial intelligence; Mathematics","score_opus":0.024999526313986976,"score_gpt":0.24294126171254582,"score_spread":0.21794173539855885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1982915164","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":[0.9526377,0.00013434769,0.046678912,0.00020666947,0.000019267773,0.00014555122,0.0000049523464,0.00001256387,0.00016003358],"genre_scores_gemma":[0.98702776,0.000008346898,0.011752646,0.00019227111,0.00035526307,0.000045028915,0.000039797724,0.000020099571,0.0005587564],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99936664,0.000030167575,0.00011716139,0.00024841743,0.00007502593,0.00016261343],"domain_scores_gemma":[0.9995382,0.0000322416,0.00004117618,0.00022120142,0.00007673996,0.000090454596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012559308,0.00009158641,0.00014056837,0.000052182884,0.00009397036,0.00002361321,0.00007388224,0.000043174397,0.000007871205],"category_scores_gemma":[0.00020028952,0.00009698119,0.000053637687,0.00007218292,0.000016868977,0.0000017530319,0.00006666212,0.000035603876,0.000003951257],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042253476,0.000081636696,0.002654792,0.000022165108,0.00035353578,1.7937113e-7,0.000016926268,0.00081554195,0.9941022,0.00003059894,0.00021864173,0.0016615523],"study_design_scores_gemma":[0.00063899264,0.00037220714,0.004619659,0.00013539483,0.00092949375,0.0000029258965,0.000043533404,0.03466623,0.95345974,0.00010853964,0.00463958,0.00038371093],"about_ca_topic_score_codex":0.000009019375,"about_ca_topic_score_gemma":0.00007244595,"teacher_disagreement_score":0.04064244,"about_ca_system_score_codex":0.000006305653,"about_ca_system_score_gemma":0.000008787257,"threshold_uncertainty_score":0.39547783},"labels":[],"label_agreement":null},{"id":"W1984112897","doi":"10.1103/physreve.91.012711","title":"Weak correlation of starch and volume in synchronized photosynthetic cells","year":2015,"lang":"en","type":"article","venue":"Physical Review E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"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 Guelph","funders":"Bundesministerium für Bildung und Forschung","keywords":"Chlamydomonas reinhardtii; Cell division; Starch; Cell; Photosynthesis; Population; Cell cycle; Biology; Volume (thermodynamics); Biophysics; Algae; Cell size; Cell growth; Cell biology; Division (mathematics); Botany; Biological system; Mutant; Biochemistry; Physics; Mathematics","score_opus":0.011793712874900896,"score_gpt":0.2688470737861489,"score_spread":0.25705336091124803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1984112897","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":[0.9686144,0.030476145,0.00025939272,0.000067969326,0.000022050242,0.00017590071,0.0000025732247,0.0000024713133,0.0003790837],"genre_scores_gemma":[0.99413633,0.0055270945,0.00011865603,0.000040194347,0.000050541345,0.00001125385,0.00001764996,0.000008344058,0.00008995915],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99934006,0.00009955654,0.00016624393,0.0001785116,0.00011044083,0.00010517866],"domain_scores_gemma":[0.9995878,0.000010637172,0.00007102646,0.0002112421,0.000052931755,0.00006641645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020424205,0.000081455146,0.00025217116,0.000017341546,0.0000075940284,0.0000027737622,0.00006900102,0.000027671475,0.000009327617],"category_scores_gemma":[0.000060284263,0.000072137474,0.00007123654,0.00012510954,0.00005212568,0.0000020376813,0.00005581811,0.000044562843,0.0000124813905],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012640633,0.00043817092,0.011406622,0.0014016038,0.00013747218,0.000002408028,0.00013907706,0.0020119105,0.94428945,0.00022517366,0.003914854,0.03590685],"study_design_scores_gemma":[0.005678531,0.00282788,0.019338997,0.004448886,0.0015049245,0.000025853764,0.00018811093,0.14918318,0.5686073,0.0041089766,0.24202028,0.0020671017],"about_ca_topic_score_codex":0.0000139688145,"about_ca_topic_score_gemma":0.000009696248,"teacher_disagreement_score":0.37568218,"about_ca_system_score_codex":0.000012145716,"about_ca_system_score_gemma":0.00004235586,"threshold_uncertainty_score":0.29416808},"labels":[],"label_agreement":null},{"id":"W1985607197","doi":"10.1016/j.jtbi.2009.07.005","title":"A model of sequential branching in hierarchical cell fate determination","year":2009,"lang":"en","type":"article","venue":"Journal of Theoretical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":50,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Cell fate determination; Gene regulatory network; Cellular differentiation; Ode; Modular design; Computer science; Biology; Biological system; Mathematics; Applied mathematics; Genetics; Gene; Gene expression; Transcription factor","score_opus":0.008674432232334649,"score_gpt":0.2626497590494801,"score_spread":0.25397532681714546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985607197","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":[0.95255506,0.00026093246,0.046396945,0.0002784317,0.000050566658,0.000036081143,0.000002556843,0.000001195509,0.0004182122],"genre_scores_gemma":[0.995082,0.00008820072,0.0045315875,0.00013188145,0.00014190275,3.8192067e-7,0.0000062264908,0.0000057945194,0.000011994825],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989114,0.00020943346,0.00047525982,0.0001368054,0.00008768998,0.00017941171],"domain_scores_gemma":[0.9994476,0.000026858173,0.0002278707,0.00013959287,0.0000890166,0.000069106965],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005271358,0.00009686209,0.00026782084,0.00012591864,0.000015730335,0.0000046338273,0.00020527966,0.00019265285,0.000015713587],"category_scores_gemma":[0.00010694518,0.000077455166,0.00019501575,0.00008440896,0.00022308521,0.000003292232,0.000041252864,0.00017069707,5.659616e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026171395,0.000098416414,0.00086051214,0.0000050536796,0.000019669702,0.000004147899,0.00003158477,0.0053328206,0.97255224,0.015340845,0.000017126675,0.005475896],"study_design_scores_gemma":[0.0017132919,0.0020337587,0.0013645462,0.000036279725,0.00011063332,0.00009296004,0.00002132012,0.08244626,0.6922324,0.21957839,0.00011458605,0.00025558606],"about_ca_topic_score_codex":4.1038217e-7,"about_ca_topic_score_gemma":0.0000013705411,"teacher_disagreement_score":0.2803198,"about_ca_system_score_codex":0.000014294324,"about_ca_system_score_gemma":0.0000603864,"threshold_uncertainty_score":0.315853},"labels":[],"label_agreement":null},{"id":"W1985937069","doi":"10.1049/ip-syb:20050105","title":"Parameter estimation in stochastic biochemical reactions","year":2006,"lang":"en","type":"article","venue":"Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":116,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Interval (graph theory); Stochastic process; Sampling (signal processing); Estimation theory; Markov process; Applied mathematics; Statistical physics; Simple (philosophy); Mathematics; Process (computing); Computer science; Mathematical optimization; Algorithm; Statistics; Physics","score_opus":0.007525155116205971,"score_gpt":0.24340858607755447,"score_spread":0.2358834309613485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985937069","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":[0.945739,0.0013686889,0.05213683,0.000050055998,0.00023754028,0.00017247391,0.0000081019625,0.0000174387,0.00026989993],"genre_scores_gemma":[0.998421,0.000005872623,0.0004878312,0.000015817595,0.00024520498,0.00005786516,0.00035203595,0.000012913198,0.00040145265],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989761,0.000116286195,0.00031122434,0.00032013413,0.000046685822,0.00022955278],"domain_scores_gemma":[0.99952483,0.000024458994,0.00009331499,0.0002860489,0.000037519174,0.00003382979],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017095818,0.000121906945,0.00017548983,0.000095165626,0.00003263734,0.000010748201,0.000097243465,0.00024806266,0.000006415911],"category_scores_gemma":[0.000060627895,0.00011477062,0.00006962283,0.00015304623,0.00007140149,0.0000017298214,0.000036212135,0.00006503755,0.000025421341],"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":[0.000029529774,0.00007756661,0.010397099,0.000018063696,0.00006228616,0.0000018620539,0.0000059263866,0.111814275,0.87320405,0.001394833,0.0026610552,0.00033347242],"study_design_scores_gemma":[0.006761084,0.0016258911,0.094131276,0.0003255385,0.0004752474,0.0008144281,0.00039819194,0.5619217,0.21359861,0.014759965,0.10091451,0.0042735264],"about_ca_topic_score_codex":0.0003595728,"about_ca_topic_score_gemma":0.00007758352,"teacher_disagreement_score":0.65960544,"about_ca_system_score_codex":0.000029866145,"about_ca_system_score_gemma":0.000028316072,"threshold_uncertainty_score":0.46802104},"labels":[],"label_agreement":null},{"id":"W1986076932","doi":"10.1039/b615197n","title":"Introduction to monitoring and manipulating signaling networks","year":2006,"lang":"en","type":"editorial","venue":"Molecular BioSystems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Université de Montréal","funders":"","keywords":"Computer science; Human–computer interaction","score_opus":0.004308852935897865,"score_gpt":0.22162621579130798,"score_spread":0.21731736285541012,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986076932","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18253362,0.013270264,0.02407674,0.00012966421,0.7788211,0.00088824675,0.000039790084,0.000104632345,0.00013590987],"genre_scores_gemma":[0.27895278,0.000059407026,0.00089713366,0.000009673339,0.7183454,0.00005019176,0.000878631,0.0001410005,0.0006658126],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99678457,0.0002111022,0.00060435943,0.0012708452,0.00057376456,0.0005553534],"domain_scores_gemma":[0.9983401,0.000025751451,0.00031499818,0.00084127137,0.00028055458,0.00019734047],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00056405994,0.000557999,0.00056621846,0.0001920813,0.00017661904,0.00018696046,0.000300845,0.001168214,0.000003699892],"category_scores_gemma":[0.0001630746,0.0006228614,0.00023383129,0.000309101,0.000036320882,0.0000038046755,0.00029461936,0.0003678634,0.000008876896],"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":[0.000022423697,0.000013001249,0.00028411625,0.000103198756,0.00023913446,0.000016262573,0.000006086277,0.0366484,0.4171145,0.0000018359231,0.5450981,0.00045289056],"study_design_scores_gemma":[0.0003273334,0.00019774283,0.000045126068,0.00023107878,0.0003062933,0.00001479636,0.000032491138,0.0013040215,0.10428999,0.0000034644374,0.89224625,0.0010014347],"about_ca_topic_score_codex":0.000117394025,"about_ca_topic_score_gemma":0.000024530838,"teacher_disagreement_score":0.3471481,"about_ca_system_score_codex":0.0000879693,"about_ca_system_score_gemma":0.00006886813,"threshold_uncertainty_score":0.9996223},"labels":[],"label_agreement":null},{"id":"W1986314791","doi":"10.1142/s0218339013500083","title":"ON MODELING OF LIVING ORGANISMS USING HIERARCHICAL COARSE-GRAINING ABSTRACTIONS OF KNOWLEDGE","year":2012,"lang":"en","type":"article","venue":"Journal of Biological Systems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Organism; Abstraction; Theoretical computer science; Living systems; Granularity; Representation (politics); Living cell; Function (biology); Data science; Living matter; Biochemical engineering; Artificial intelligence; Biological system; Biology; Programming language; Engineering; Epistemology","score_opus":0.05623051190482447,"score_gpt":0.2953022919049182,"score_spread":0.23907178000009371,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986314791","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":[0.98125535,0.0028557603,0.015186222,0.000006852709,0.0003350191,0.00005561327,0.000003898042,0.0000025960815,0.0002987139],"genre_scores_gemma":[0.9982089,0.00007679486,0.0010179809,0.0000063803896,0.0006586037,7.374956e-7,0.0000020505422,0.000011204581,0.00001736807],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985082,0.00024365755,0.00074636086,0.00011928362,0.00015872269,0.0002237506],"domain_scores_gemma":[0.9987053,0.00015182563,0.0006194843,0.0001627871,0.00022801761,0.00013254404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010333338,0.00012616612,0.00042051592,0.00009912857,0.000055006625,0.000007677966,0.00017013375,0.00022520605,0.000018565064],"category_scores_gemma":[0.0003802717,0.0000886504,0.00026636262,0.00012432173,0.00007698481,0.000006805811,0.00006460045,0.0001835029,0.0000016467758],"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":[0.000060334827,0.00028235037,0.010488635,0.00003443657,0.00026448863,0.0000012215557,0.00013108095,0.15514077,0.83303237,0.00024932908,0.00005821311,0.00025675874],"study_design_scores_gemma":[0.0030005497,0.01185491,0.03481042,0.005932022,0.001842505,0.00294065,0.009537492,0.6809524,0.24179886,0.0008463816,0.0036303937,0.0028533898],"about_ca_topic_score_codex":0.000009329117,"about_ca_topic_score_gemma":0.0000010883748,"teacher_disagreement_score":0.59123355,"about_ca_system_score_codex":0.000028834,"about_ca_system_score_gemma":0.000064509324,"threshold_uncertainty_score":0.36150584},"labels":[],"label_agreement":null},{"id":"W1986382561","doi":"10.1073/pnas.0500554102","title":"A coherent framework for multiresolution analysis of biological networks with “memory”: Ras pathway, cell cycle, and immune system","year":2005,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"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":"U.S. Air Force; Office of Science; Tata Institute of Fundamental Research; York University; U.S. Department of Energy; National Institutes of Health; National Science Foundation","keywords":"Biological system; In silico; Computer science; Bistability; Systems biology; Computational biology; Biology; Algorithm; Physics; Genetics","score_opus":0.019418494978581273,"score_gpt":0.2654132851230058,"score_spread":0.24599479014442455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986382561","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":[0.9975139,0.0014428097,0.00048633982,0.0001524523,0.000005319552,0.00019239761,0.000014041659,0.0000035861183,0.00018918833],"genre_scores_gemma":[0.9926366,0.00005602725,0.0071670613,0.000028019662,0.00007059021,0.000017047118,0.000001771004,0.000003419116,0.000019465138],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989569,0.000011197737,0.00030814455,0.0002582323,0.00033432248,0.00013117542],"domain_scores_gemma":[0.9991391,0.00005074149,0.0005216696,0.000016518377,0.00024258083,0.000029430816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008004043,0.00009462904,0.00023657909,0.00011350547,0.00011261017,0.0000087401195,0.0003207354,0.000151129,0.000002488036],"category_scores_gemma":[0.00008230493,0.000058543937,0.00014977712,0.00068661745,0.00048548396,0.000009811969,0.00009602654,0.00006202581,4.574537e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016494188,0.0001123377,0.022019055,0.00010474577,0.0005717074,3.1427556e-9,0.000073303825,0.11905123,0.8463369,0.010363484,0.00005884811,0.0011434234],"study_design_scores_gemma":[0.00039815478,0.00024812794,0.11697748,0.000086712105,0.00040560638,0.0000030593044,0.00042691044,0.15278459,0.7278492,0.0005861,0.00007062038,0.00016345042],"about_ca_topic_score_codex":0.000003488393,"about_ca_topic_score_gemma":5.458292e-7,"teacher_disagreement_score":0.11848772,"about_ca_system_score_codex":0.000017529199,"about_ca_system_score_gemma":0.000017494323,"threshold_uncertainty_score":0.23873526},"labels":[],"label_agreement":null},{"id":"W1986452936","doi":"10.1007/s10489-006-6937-9","title":"Cell modeling with reusable agent-based formalisms","year":2006,"lang":"en","type":"article","venue":"Applied Intelligence","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Rotation formalisms in three dimensions; Unified Modeling Language; Reuse; Simple (philosophy); Representation (politics); Process (computing); Diagrammatic reasoning; Artificial intelligence; Human–computer interaction; Theoretical computer science; Programming language; Ecology","score_opus":0.007951114189164775,"score_gpt":0.20270717961594906,"score_spread":0.19475606542678428,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986452936","genre_codex":"methods","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":[0.39504224,0.00038766625,0.59362715,0.000017702623,0.00002249443,0.0001279418,0.0000020897348,0.000021872826,0.010750836],"genre_scores_gemma":[0.9886132,0.000025664465,0.010259221,0.00015084745,0.00014463653,0.000039837236,0.0001230075,0.00003171507,0.00061185437],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988557,0.000013404394,0.00022756653,0.00039902885,0.00017508549,0.00032918],"domain_scores_gemma":[0.9992742,0.0000055441183,0.000076101904,0.0005124284,0.00006908405,0.00006263161],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012635243,0.00018741093,0.00014079594,0.00004478127,0.000099580124,0.000029074194,0.00025966566,0.00010855214,0.000040457253],"category_scores_gemma":[0.0000020065092,0.00016687597,0.00007551138,0.00019527883,0.000057839028,0.000002733269,0.000054927747,0.0000719331,0.000052852654],"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":[0.00006010939,0.00005200663,0.0002843789,0.000013142863,0.000019302168,0.0000019250765,0.0000059132067,0.85108256,0.14614141,0.0008444021,0.00087191386,0.0006229284],"study_design_scores_gemma":[0.00013432777,0.000080183025,0.000015370002,0.000006100251,0.000041900177,0.0000025664394,0.000058525664,0.117165916,0.8777231,0.0004372312,0.0040532635,0.00028153972],"about_ca_topic_score_codex":0.00005734909,"about_ca_topic_score_gemma":0.000052041996,"teacher_disagreement_score":0.73391664,"about_ca_system_score_codex":0.00001746254,"about_ca_system_score_gemma":0.00005888955,"threshold_uncertainty_score":0.68050045},"labels":[],"label_agreement":null},{"id":"W1986493401","doi":"10.1016/j.bbi.2012.09.008","title":"Systems biology of complex symptom profiles: Capturing interactivity across behavior, brain and immune regulation","year":2012,"lang":"en","type":"review","venue":"Brain Behavior and Immunity","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Institute of Arthritis and Musculoskeletal and Skin Diseases; National Institutes of Health; U.S. Department of Veterans Affairs; U.S. Department of Defense","keywords":"Systems biology; Cognitive science; Neuroscience; Interactivity; Modelling biological systems; Autism; Biology; Field (mathematics); Context (archaeology); Data science; Computer science; Computational biology; Psychology","score_opus":0.05283492482880376,"score_gpt":0.3498154939283049,"score_spread":0.29698056909950116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986493401","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32585785,0.6728743,0.000054587406,0.0000054711813,0.00015959407,0.00078651117,0.00023026351,0.000013499962,0.000017939848],"genre_scores_gemma":[0.544853,0.45139626,0.000087075394,0.000007598855,0.00018106516,0.00029840847,0.0027554082,0.000075483804,0.00034572784],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99696445,0.0009948962,0.00088137283,0.0005579228,0.00013064583,0.00047068726],"domain_scores_gemma":[0.99785304,0.00012859063,0.00080555765,0.0009469045,0.00012411547,0.0001417786],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00096125976,0.00056312664,0.0015487574,0.00013468387,0.0002515638,0.000057931527,0.00032249955,0.00075824454,0.000018666962],"category_scores_gemma":[0.000069202564,0.0005168958,0.0003971294,0.0001826568,0.0004235806,0.000017412543,0.000651908,0.00039318355,0.0000019029965],"study_design_candidate":"design_other","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":[0.000027441876,0.00042475256,0.009572457,0.004687591,0.00048748823,0.0000027169328,0.0002718321,0.000002175919,0.07728763,0.000048107864,0.00012300961,0.9070648],"study_design_scores_gemma":[0.001234504,0.00049045973,0.16217494,0.0029805317,0.005424906,0.00065598567,0.0006070386,0.000024500992,0.002413944,0.00000593407,0.82190424,0.0020829877],"about_ca_topic_score_codex":0.00048307615,"about_ca_topic_score_gemma":0.00004109064,"teacher_disagreement_score":0.9049818,"about_ca_system_score_codex":0.000050724248,"about_ca_system_score_gemma":0.000076896875,"threshold_uncertainty_score":0.99972826},"labels":[],"label_agreement":null},{"id":"W1986519972","doi":"10.1016/j.jmaa.2009.03.037","title":"Hopf bifurcation analysis for a model of genetic regulatory system with delay","year":2009,"lang":"en","type":"article","venue":"Journal of Mathematical Analysis and Applications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Center manifold; Hopf bifurcation; Mathematics; Stability (learning theory); Bifurcation; Biological applications of bifurcation theory; Range (aeronautics); Applied mathematics; Control theory (sociology); Manifold (fluid mechanics); Mathematical analysis; Nonlinear system; Computer science; Physics","score_opus":0.00836728447650913,"score_gpt":0.23346116654178883,"score_spread":0.2250938820652797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986519972","genre_codex":"methods","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":[0.34755605,0.00033915453,0.6518762,0.00006472985,9.771154e-7,0.00011133484,0.0000079179945,0.000002319839,0.000041313568],"genre_scores_gemma":[0.94868535,0.000059667364,0.051038537,0.00002226434,0.00006861985,0.000025332633,0.000021123711,0.000007732087,0.00007139335],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987434,0.000031626714,0.0006714972,0.00020345327,0.00022702165,0.0001229938],"domain_scores_gemma":[0.9983807,0.000029513381,0.0006473245,0.0003891864,0.00043768695,0.00011555977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037172204,0.00012881587,0.0005576155,0.0003790371,0.00007230218,0.000018968878,0.00015996302,0.000084237945,0.000004198424],"category_scores_gemma":[0.00001396897,0.00009362167,0.0005655537,0.0010349039,0.000063251835,0.000005694328,0.000015050743,0.000044030803,3.118883e-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":[0.0001538358,0.00057557586,0.009493117,0.00019901931,0.018627767,8.72225e-7,0.000099115314,0.88316697,0.064649135,0.017272722,0.00012067897,0.0056412183],"study_design_scores_gemma":[0.0008289919,0.0005631863,0.025929276,0.00004496058,0.048598155,0.000045227076,0.0002913701,0.9078241,0.009987327,0.0052746627,0.00022030965,0.00039245162],"about_ca_topic_score_codex":8.322634e-7,"about_ca_topic_score_gemma":0.00000729816,"teacher_disagreement_score":0.6011293,"about_ca_system_score_codex":0.000016216332,"about_ca_system_score_gemma":0.000049525108,"threshold_uncertainty_score":0.3817781},"labels":[],"label_agreement":null},{"id":"W1987067655","doi":"10.1186/1471-2105-12-67","title":"MIR@NT@N: a framework integrating transcription factors, microRNAs and their targets to identify sub-network motifs in a meta-regulation network model","year":2011,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":70,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Child and Family Research Institute; Institute for Research in Immunology and Cancer; University of British Columbia","funders":"Canadian Institutes of Health Research; National Institute of General Medical Sciences; Centre National de la Recherche Scientifique; Fonds National de la Recherche Luxembourg; Michael Smith Health Research BC; Université de Montréal; Child and Family Research Institute; Institute of Genetics; Institut National de la Santé et de la Recherche Médicale; Université du Luxembourg","keywords":"Computational biology; Gene regulatory network; microRNA; Biology; Computer science; Biological network; Systems biology; Transcription factor; Gene; Bioinformatics; Genetics; Gene expression","score_opus":0.039982651521636915,"score_gpt":0.25350007155950977,"score_spread":0.21351742003787286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987067655","genre_codex":"methods","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":[0.4579108,0.0012355904,0.5402776,0.000013406568,0.000103158294,0.00032684166,0.000013967902,0.00002290532,0.000095725125],"genre_scores_gemma":[0.78188246,0.000074527125,0.21746424,0.00016492675,0.00015282347,0.000037071626,0.00015697833,0.000033422217,0.000033555323],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980389,0.00011240147,0.00077210343,0.0003501704,0.00016996422,0.00055644405],"domain_scores_gemma":[0.99890035,0.000032798787,0.0002690117,0.00051695615,0.00010170799,0.00017919327],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006461221,0.00041770705,0.0005135683,0.00012396455,0.00015359472,0.00007306666,0.00025998172,0.00039613017,0.000019030012],"category_scores_gemma":[0.00006871406,0.00033292538,0.0003087521,0.00044805545,0.000067370485,0.000035986446,0.00013232391,0.00020067612,0.0000069473167],"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":[0.00031499052,0.0001751358,0.04640981,0.0003142503,0.0018029135,0.0000013907312,0.013810013,0.8436254,0.08571836,0.0012017402,0.003903727,0.002722229],"study_design_scores_gemma":[0.00056353345,0.00021775717,0.03786153,0.00016817439,0.0007111945,0.00001185161,0.0012029893,0.906251,0.04606702,0.005111002,0.00081640744,0.0010175064],"about_ca_topic_score_codex":0.000025261661,"about_ca_topic_score_gemma":0.00082226825,"teacher_disagreement_score":0.32397166,"about_ca_system_score_codex":0.000037776208,"about_ca_system_score_gemma":0.00006385877,"threshold_uncertainty_score":0.99991226},"labels":[],"label_agreement":null},{"id":"W1987109029","doi":"10.1016/j.jtbi.2011.01.020","title":"Molecular distributions in gene regulatory dynamics","year":2011,"lang":"en","type":"article","venue":"Journal of Theoretical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":52,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; McGill University Health Centre","funders":"Komitet Badań Naukowych","keywords":"Bursting; Statistical physics; Stationary distribution; Stochastic dynamics; Noise (video); Stochastic modelling; Context (archaeology); Stochastic process; Dimensionless quantity; Stationary state; Biological system; Mathematics; Computer science; Physics; Biology; Statistics; Mechanics; Artificial intelligence","score_opus":0.005989977224988442,"score_gpt":0.2294081427101428,"score_spread":0.22341816548515434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987109029","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":[0.96530247,0.0008362461,0.03254916,0.00015305285,0.00014624643,0.000045997604,0.000012946423,0.0000028581496,0.00095100194],"genre_scores_gemma":[0.9968391,0.00010537053,0.0027776335,0.00008762527,0.00012309621,0.0000019470892,0.000040017752,0.000013321952,0.000011883166],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987724,0.00023033081,0.00046485776,0.0001854967,0.00008337062,0.00026357538],"domain_scores_gemma":[0.99921477,0.00001714334,0.00019647177,0.00030621735,0.00013878747,0.00012661485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052191294,0.00013359371,0.0002700812,0.000109097724,0.000025778125,0.0000045337215,0.0003167673,0.00025141978,0.00009224434],"category_scores_gemma":[0.00016887646,0.000110622874,0.00024170696,0.00015404048,0.0005368064,0.00000263909,0.00010675457,0.00017362327,0.0000043985847],"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":[0.00026856334,0.00020714167,0.016283419,0.0000040117493,0.0002182892,0.000062453255,0.000024833222,0.00011953852,0.46512884,0.51514924,0.00013951115,0.002394142],"study_design_scores_gemma":[0.0011177806,0.0012213927,0.018256413,0.000024586132,0.0001951196,0.0004455869,0.00007366033,0.00089261093,0.8143227,0.16237967,0.0006600514,0.000410417],"about_ca_topic_score_codex":0.0000020133343,"about_ca_topic_score_gemma":0.0000052722276,"teacher_disagreement_score":0.35276958,"about_ca_system_score_codex":0.000045313125,"about_ca_system_score_gemma":0.00006639908,"threshold_uncertainty_score":0.451107},"labels":[],"label_agreement":null},{"id":"W1988024270","doi":"10.1111/j.1742-4658.2005.05043.x","title":"Optimal observability of sustained stochastic competitive inhibition oscillations at organellar volumes","year":2005,"lang":"en","type":"article","venue":"FEBS Journal","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"Natural Sciences and Engineering Research Council of Canada; Western Canada Research Grid","keywords":"Observability; Randomness; Stochastic resonance; Stochastic differential equation; Ordinary differential equation; Limit (mathematics); Mathematics; Physics; Action (physics); Control theory (sociology); Mathematical analysis; Noise (video); Differential equation; Applied mathematics; Computer science; Statistics; Quantum mechanics","score_opus":0.008336452959750367,"score_gpt":0.22836311880066523,"score_spread":0.22002666584091488,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988024270","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":[0.98772913,0.0005555507,0.011036808,0.00030669844,0.0000574439,0.00008289467,0.00001550657,0.000005955691,0.00020999106],"genre_scores_gemma":[0.99625766,0.00004123483,0.0023769767,0.00004059919,0.00053329376,0.0000018566866,0.00006912064,0.000014161934,0.0006650701],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989697,0.00010349661,0.0003307786,0.00019169718,0.00019324759,0.0002110855],"domain_scores_gemma":[0.9990579,0.000016037724,0.00021375447,0.00021812784,0.00037942582,0.00011474048],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027593193,0.00012386413,0.00017754266,0.000057587986,0.00018740649,0.000018773077,0.0000964574,0.0001025142,0.00021034897],"category_scores_gemma":[0.00010190948,0.00012101033,0.00016925405,0.00014043861,0.00011458396,0.0000072573403,0.0000959747,0.00010313264,0.0000117915715],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023797306,0.00019869483,0.023348369,0.000024016137,0.00035051987,0.0000072791026,0.00027164494,0.462681,0.5065628,0.00014259967,0.005245627,0.0009294694],"study_design_scores_gemma":[0.006784165,0.002012546,0.17387933,0.00018238237,0.0011405639,0.0015516228,0.0034736146,0.06435772,0.69360757,0.00068871694,0.050379056,0.0019427353],"about_ca_topic_score_codex":0.0000019846227,"about_ca_topic_score_gemma":0.000055430348,"teacher_disagreement_score":0.39832327,"about_ca_system_score_codex":0.00010223289,"about_ca_system_score_gemma":0.00011598493,"threshold_uncertainty_score":0.49346578},"labels":[],"label_agreement":null},{"id":"W1988441309","doi":"10.1063/1.1786683","title":"Evolving complex dynamics in electronic models of genetic networks","year":2004,"lang":"en","type":"article","venue":"Chaos An Interdisciplinary Journal of Nonlinear Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Limit cycle; Ordinary differential equation; Limit (mathematics); Computer science; Piecewise; Nonlinear system; Class (philosophy); Piecewise linear function; Differential equation; Mathematics; Applied mathematics; Theoretical computer science; Artificial intelligence; Physics; Mathematical analysis","score_opus":0.01264251861869335,"score_gpt":0.29092156096688304,"score_spread":0.2782790423481897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988441309","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":[0.91989225,0.00097113685,0.07878073,0.00008889241,0.00010345372,0.000066210996,0.00000272662,0.0000023377445,0.00009224982],"genre_scores_gemma":[0.98942536,0.00017870171,0.010092663,0.00002389097,0.0002420498,0.0000010213303,0.000008942476,0.00001705305,0.000010297192],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982577,0.000047033802,0.00063720683,0.00030280137,0.00033204077,0.0004232059],"domain_scores_gemma":[0.9986619,0.0000071970912,0.00041499938,0.00038458983,0.00037686966,0.00015447673],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007794328,0.00015880824,0.000293555,0.0003025893,0.00013470564,0.000031918597,0.0008694492,0.00008475553,0.00000908722],"category_scores_gemma":[0.000020284222,0.00014418982,0.00016847107,0.000615329,0.0004407461,0.00004713799,0.00047851936,0.0002160803,5.943114e-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":[0.00008365336,0.00020523756,0.0030597597,0.000009034201,0.00003304512,0.000017884404,0.00022758696,0.9411267,0.053301122,0.00015563419,0.000011137959,0.0017692224],"study_design_scores_gemma":[0.0006293713,0.0012401731,0.010817291,0.00009384427,0.000030326937,0.0002830808,0.0007016773,0.9793799,0.004132693,0.0024789034,0.000009492289,0.00020326122],"about_ca_topic_score_codex":0.000007216032,"about_ca_topic_score_gemma":0.00027165658,"teacher_disagreement_score":0.069533125,"about_ca_system_score_codex":0.00026640546,"about_ca_system_score_gemma":0.0005159182,"threshold_uncertainty_score":0.58798903},"labels":[],"label_agreement":null},{"id":"W1988639283","doi":"10.1007/s00285-007-0098-2","title":"Graph-theoretic methods for the analysis of chemical and biochemical networks. II. Oscillations in networks with delays","year":2007,"lang":"en","type":"article","venue":"Journal of Mathematical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":32,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Bipartite graph; Ode; Digraph; Mathematics; Jacobian matrix and determinant; Ordinary differential equation; Graph; Differential equation; Applied mathematics; Combinatorics; Mathematical analysis","score_opus":0.009440451422541518,"score_gpt":0.3052648319752823,"score_spread":0.2958243805527408,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988639283","genre_codex":"methods","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":[0.4615685,0.001967491,0.53623986,0.000098021235,0.000019803636,0.00008652901,0.0000014558458,0.0000012233747,0.000017117522],"genre_scores_gemma":[0.9386518,0.00022730199,0.06089379,0.000059736463,0.00013117354,0.000005134416,0.00001364214,0.000012253672,0.000005145526],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99856794,0.0001267574,0.0007386026,0.00020042878,0.00008254051,0.00028375676],"domain_scores_gemma":[0.9981836,0.0008561758,0.00040246308,0.0002599094,0.00019473056,0.00010313141],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023600333,0.00015588243,0.0005786849,0.00021720331,0.000048408707,0.000006967331,0.0002296898,0.00026803528,0.000013593219],"category_scores_gemma":[0.00033351284,0.00009178164,0.0003235093,0.00067508896,0.00048783928,0.0000029416285,0.000093947674,0.00017093627,5.249459e-8],"study_design_candidate":"simulation_or_modeling","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":[0.003595339,0.0011000374,0.043659773,0.00015655077,0.018407812,0.000011528388,0.0003702087,0.14424509,0.70104307,0.05311334,0.000650372,0.0336469],"study_design_scores_gemma":[0.005478953,0.0036434089,0.01686726,0.00020389308,0.017891834,0.00063883985,0.0005609723,0.7615287,0.14008304,0.049627,0.0021238923,0.0013522466],"about_ca_topic_score_codex":9.220859e-7,"about_ca_topic_score_gemma":0.000005790958,"teacher_disagreement_score":0.6172836,"about_ca_system_score_codex":0.000013648938,"about_ca_system_score_gemma":0.0000286971,"threshold_uncertainty_score":0.37427467},"labels":[],"label_agreement":null},{"id":"W1988791304","doi":"10.1038/nature01258","title":"Control, exploitation and tolerance of intracellular noise","year":2002,"lang":"en","type":"review","venue":"Nature","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1032,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Cancer Institute; Canadian Institutes of Health Research","keywords":"Noise (video); Sensitivity (control systems); Function (biology); Computer science; Biological system; Biology; Cell biology; Engineering; Artificial intelligence; Electronic engineering","score_opus":0.009270949303984779,"score_gpt":0.2569257365399309,"score_spread":0.2476547872359461,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988791304","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005637936,0.9988715,0.00011981605,0.000013669994,0.00009195845,0.00021434961,0.000030136936,0.0000046123,0.000090163776],"genre_scores_gemma":[0.007837465,0.99100155,0.00020792059,0.000047912326,0.00030870797,0.000019474632,0.00017263838,0.000030621497,0.00037368582],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99901766,0.00009486129,0.00028526757,0.0003435185,0.00012581157,0.00013287082],"domain_scores_gemma":[0.99922657,0.000015702826,0.00026389878,0.0003580041,0.00008518291,0.000050614868],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00011089577,0.00023115514,0.0007174977,0.00006280784,0.00002520228,0.000009315618,0.00015068155,0.002029556,0.000017471855],"category_scores_gemma":[0.000041837182,0.00019828543,0.00028217954,0.00014004111,0.00004991446,0.0000016764809,0.000035739366,0.00059351185,0.000003396119],"study_design_candidate":"not_applicable","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":[0.000014526803,0.000049446488,0.000027271723,0.005377498,0.00066344277,0.000006315646,0.000013735485,0.00008457141,0.0019169225,0.000076347875,0.0064155166,0.9853544],"study_design_scores_gemma":[0.0001782154,0.000038978666,0.0000062638933,0.0006194067,0.0006084799,0.000012461392,0.0000021212468,0.000053033553,0.00025123204,0.000007605843,0.9980367,0.00018549898],"about_ca_topic_score_codex":6.446096e-7,"about_ca_topic_score_gemma":0.0000019849451,"teacher_disagreement_score":0.9916212,"about_ca_system_score_codex":0.000009166284,"about_ca_system_score_gemma":0.000034475994,"threshold_uncertainty_score":0.999266},"labels":[],"label_agreement":null},{"id":"W1989202466","doi":"10.1038/ng0606-610","title":"Predictable trends in protein noise","year":2006,"lang":"en","type":"letter","venue":"Nature Genetics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Biology; Gene expression; Noise (video); Gene; Computational biology; Genetics; Protein expression; Expression (computer science); Evolutionary biology; Cell biology; Computer science; Artificial intelligence","score_opus":0.0041228507975498456,"score_gpt":0.2200913209014485,"score_spread":0.21596847010389866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989202466","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":[0.6998221,0.10902361,0.0003502328,0.16630416,0.0021910644,0.0018554255,0.0007410447,0.00015984927,0.019552475],"genre_scores_gemma":[0.47741145,0.00050665106,0.0059265625,0.27919084,0.03103479,0.00033260297,0.02789174,0.0006482539,0.17705712],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9973073,0.00013116549,0.00044405216,0.00095506007,0.0004755451,0.00068689644],"domain_scores_gemma":[0.99843985,0.0000052895666,0.0002097512,0.0011562952,0.00012370922,0.000065101674],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00015893561,0.0005320309,0.00045975286,0.0003882359,0.000051460833,0.000045429493,0.0006096718,0.0048651826,0.000076309836],"category_scores_gemma":[0.000014337673,0.00054816523,0.00032226826,0.0005528757,0.00008333454,0.0000015341145,0.00020114217,0.002268784,0.000015982103],"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":[0.000010193584,0.00003207041,0.002399508,0.000046510384,0.00010251229,0.000077832985,0.000003281856,0.0012662038,0.009033667,5.237625e-7,0.9853177,0.0017100158],"study_design_scores_gemma":[0.00038713042,0.000100430116,0.0029745316,0.000036766236,0.00011113777,0.000009599766,0.0000012581432,0.00017102514,0.017750628,0.0000651543,0.9778279,0.0005644459],"about_ca_topic_score_codex":0.000016206348,"about_ca_topic_score_gemma":0.00017932348,"teacher_disagreement_score":0.2224107,"about_ca_system_score_codex":0.00006480584,"about_ca_system_score_gemma":0.00012990714,"threshold_uncertainty_score":0.99969697},"labels":[],"label_agreement":null},{"id":"W1989982492","doi":"10.1016/j.shpsc.2013.06.002","title":"Systems biology and the integration of mechanistic explanation and mathematical explanation","year":2013,"lang":"en","type":"article","venue":"Studies in History and Philosophy of Science Part C Studies in History and Philosophy of Biological and Biomedical Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":103,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Mathematical and theoretical biology; Mechanism (biology); Systems biology; Computer science; Mathematical model; Robustness (evolution); Dynamical systems theory; Cognitive science; Mathematical structure; Epistemology; Management science; Biology; Mathematics; Computational biology; Psychology; Physics; Bioinformatics; Mathematics education","score_opus":0.11460572188930042,"score_gpt":0.3178195920510064,"score_spread":0.203213870161706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989982492","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":[0.8669362,0.13109116,0.00004189587,0.0007444068,0.00032679157,0.00025831535,0.0000064217156,0.0000025910301,0.000592199],"genre_scores_gemma":[0.9816463,0.017952804,0.00021132408,0.00005280669,0.000085644904,0.000038433627,0.0000029154714,0.0000017773142,0.000008020382],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99839145,0.00020739126,0.00053963036,0.0004685898,0.00021723709,0.00017568271],"domain_scores_gemma":[0.99908495,0.00034009357,0.0002754937,0.00010279819,0.00012650693,0.00007016392],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001994274,0.00016578207,0.0005298724,0.0002141542,0.00021184656,0.000004093961,0.0001603948,0.00011325654,0.000005145331],"category_scores_gemma":[0.00061040214,0.00009442165,0.000032656335,0.00023778145,0.037440374,0.00003053236,0.00024646678,0.00008242647,1.0451357e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00069144054,0.00055958144,0.026911722,0.002206967,0.00045441947,0.0000055311234,0.023674987,0.000023761091,0.13085923,0.7994768,0.0007892709,0.014346314],"study_design_scores_gemma":[0.0026451661,0.004507577,0.0078108823,0.001117475,0.00016224002,0.000060983817,0.014755083,0.002552252,0.0012937478,0.9611792,0.0031400379,0.00077535165],"about_ca_topic_score_codex":0.000030131088,"about_ca_topic_score_gemma":0.000007459528,"teacher_disagreement_score":0.16170242,"about_ca_system_score_codex":0.000050103994,"about_ca_system_score_gemma":0.00003620584,"threshold_uncertainty_score":0.96517915},"labels":[],"label_agreement":null},{"id":"W1990039203","doi":"10.1038/msb4100185","title":"Accurate prediction of gene feedback circuit behavior from component properties","year":2007,"lang":"en","type":"article","venue":"Molecular Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":77,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Institute of General Medical Sciences","keywords":"Biology; Synthetic biology; Electronic circuit; Computational biology; Gene regulatory network; Repressor; Gene; Component (thermodynamics); Biological system; Regulation of gene expression; Negative feedback; Systems biology; Genetics; Gene expression; Physics","score_opus":0.02158925266562783,"score_gpt":0.22994043685656934,"score_spread":0.2083511841909415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990039203","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":[0.93307245,0.007264602,0.058469605,0.0000107409105,0.00050501036,0.00038507223,0.00010486688,0.000023401111,0.00016425725],"genre_scores_gemma":[0.9984522,0.000052444353,0.00020436483,0.000038498823,0.00030282812,0.000050568386,0.00075671246,0.000034978155,0.00010739809],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9981235,0.00021468026,0.00061866944,0.0005229121,0.00015363168,0.00036658588],"domain_scores_gemma":[0.9987592,0.000008736681,0.00028699968,0.0006474799,0.00018839868,0.00010917842],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040171464,0.00023957415,0.00038575797,0.00010239845,0.00005951675,0.000014031957,0.00028062574,0.0003760632,0.00001045005],"category_scores_gemma":[0.000026285112,0.00021722996,0.00019598592,0.00014872127,0.00015839972,0.0000030865504,0.000098166456,0.00008652831,0.000013093883],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005287621,0.00007397663,0.017053869,0.000018311976,0.00029009394,0.000011991978,0.000030973508,0.000745872,0.9810094,0.00006044391,0.000084073865,0.00056807423],"study_design_scores_gemma":[0.0005559785,0.0002721643,0.034814328,0.000026792091,0.00018987269,0.000038609604,0.00009768546,0.00046008851,0.9594915,0.00001290172,0.0037874342,0.00025264185],"about_ca_topic_score_codex":0.00034075917,"about_ca_topic_score_gemma":0.00003408881,"teacher_disagreement_score":0.06537976,"about_ca_system_score_codex":0.000034870907,"about_ca_system_score_gemma":0.00005008777,"threshold_uncertainty_score":0.8858381},"labels":[],"label_agreement":null},{"id":"W1990370362","doi":"10.1142/s0129183108012091","title":"EVIDENCE OF SCALE-FREE TOPOLOGY IN GENE REGULATORY NETWORK OF HUMAN TISSUES","year":2008,"lang":"en","type":"article","venue":"International Journal of Modern Physics C","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"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 Calgary","funders":"","keywords":"Gene regulatory network; Scale-free network; Topology (electrical circuits); Blueprint; Network topology; Scale (ratio); Computational biology; Regulator gene; Computer science; Gene; Regulation of gene expression; Biology; Complex network; Mathematics; Genetics; Computer network; Gene expression; Physics; Engineering; Combinatorics","score_opus":0.024857879323279115,"score_gpt":0.2884122880677767,"score_spread":0.2635544087444976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990370362","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":[0.9881966,0.004324275,0.007083061,0.000091159716,0.00016714062,0.000033524873,0.000003867075,0.0000012920272,0.000099058554],"genre_scores_gemma":[0.9962799,0.0006282829,0.0020782226,0.000033324308,0.0008746424,9.758288e-7,0.000007734278,0.00001301365,0.0000839151],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9986755,0.00007935534,0.0005765487,0.00014246975,0.00039855434,0.0001275508],"domain_scores_gemma":[0.9984002,0.000024543495,0.0006341074,0.00030310624,0.00059610285,0.000041956442],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026177638,0.00010560804,0.00029067698,0.00006220944,0.000021245141,0.0000031826937,0.0006471807,0.00008332634,0.000010165369],"category_scores_gemma":[0.000043091415,0.000106285326,0.00020850828,0.00009018932,0.0001819906,0.000013605332,0.00016963518,0.000097768774,4.2621937e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020407913,0.00016388575,0.07355098,0.000010335649,0.0003549732,0.000023222541,0.00018947224,0.051350195,0.8659477,0.00028876768,0.0008644182,0.007051959],"study_design_scores_gemma":[0.0010301506,0.00042551427,0.050415076,0.0002797716,0.00006805008,0.0001539902,0.000020623846,0.0012841523,0.92715526,0.018858843,0.000116960546,0.00019158925],"about_ca_topic_score_codex":0.000015730504,"about_ca_topic_score_gemma":0.000027931408,"teacher_disagreement_score":0.061207563,"about_ca_system_score_codex":0.000030837182,"about_ca_system_score_gemma":0.000102234946,"threshold_uncertainty_score":0.433419},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.02244454250510567,"score_gpt":0.2457764000152073,"score_spread":0.22333185751010165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990514789","genre_codex":"methods","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":[0.42817318,0.007466561,0.56312793,0.0000024103497,0.0006975388,0.00036908442,0.000004896706,0.000040547326,0.00011785107],"genre_scores_gemma":[0.99177843,0.000017829016,0.0027676162,0.0001122468,0.004448751,0.00016633223,0.00045760794,0.00008578888,0.00016538754],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966453,0.00057176664,0.00061366044,0.0008766911,0.00016459469,0.0011280391],"domain_scores_gemma":[0.99781257,0.000021899834,0.00018976469,0.0012496979,0.00013938543,0.00058669614],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0011953262,0.0004313032,0.0005406706,0.0001471275,0.000203244,0.0000389492,0.0004834568,0.00059570064,0.0000038933463],"category_scores_gemma":[0.00004182168,0.00040137282,0.00022144882,0.0003018046,0.00009032014,0.000006414644,0.0002655031,0.00015707276,0.000019816525],"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":[0.00006481321,0.00013312683,0.0026712923,0.000013178387,0.0001174214,1.9446203e-7,0.000043606484,0.98503953,0.010975055,0.00043176458,0.0002667931,0.00024319213],"study_design_scores_gemma":[0.00031372323,0.00015511947,0.0007923373,0.000016383601,0.000096414995,0.000058138427,0.00017596653,0.99718636,0.00022208292,0.0000031381105,0.00047324132,0.0005071098],"about_ca_topic_score_codex":0.000049636594,"about_ca_topic_score_gemma":0.000016276335,"teacher_disagreement_score":0.56360525,"about_ca_system_score_codex":0.00007055623,"about_ca_system_score_gemma":0.000061011055,"threshold_uncertainty_score":0.99984384},"labels":[],"label_agreement":null},{"id":"W1990853262","doi":"10.1142/s0219525909002040","title":"DELAY-INDEPENDENT STABILITY OF GENETIC REGULATORY NETWORKS WITH TIME DELAYS","year":2009,"lang":"en","type":"article","venue":"Advances in Complex Systems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Stability (learning theory); Gene regulatory network; Genetic network; Computer science; Complement (music); Biology; Control theory (sociology); Gene; Genetics; Mutant; Control (management); Artificial intelligence; Gene expression","score_opus":0.008600920377295209,"score_gpt":0.23277299678168226,"score_spread":0.22417207640438705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990853262","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":[0.95101213,0.02172479,0.025734881,0.000011868679,0.00008614729,0.0003840055,0.000007991398,0.000018345783,0.0010198284],"genre_scores_gemma":[0.9979626,0.00027080564,0.001390063,0.0000328369,0.00017756931,0.000018167057,0.000060889564,0.000021289365,0.00006580087],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9980895,0.00018932822,0.00056461454,0.00051420566,0.00028971283,0.00035263505],"domain_scores_gemma":[0.9986641,0.000020601501,0.0002774789,0.00080706406,0.00013767046,0.00009311271],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000327745,0.00023500776,0.0004311908,0.00006904604,0.000050544175,0.000014106586,0.0003132911,0.00013941959,0.00002346729],"category_scores_gemma":[0.000010587298,0.00021052331,0.000101040074,0.00026896593,0.00012764298,0.000010185754,0.000054764725,0.000093171635,0.00000348877],"study_design_candidate":"simulation_or_modeling","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":[0.00022682239,0.00014257184,0.08686329,0.00005908085,0.000100843696,0.000014155971,0.000030887863,0.86150265,0.04561409,0.00011356517,0.00024503242,0.0050870143],"study_design_scores_gemma":[0.005203363,0.0043357913,0.5555644,0.00043928463,0.00035875625,0.00046595524,0.0005354718,0.36158574,0.027052194,0.0004909484,0.04123115,0.0027369314],"about_ca_topic_score_codex":0.000019113915,"about_ca_topic_score_gemma":0.00013937209,"teacher_disagreement_score":0.4999169,"about_ca_system_score_codex":0.00005119077,"about_ca_system_score_gemma":0.000052260562,"threshold_uncertainty_score":0.85848916},"labels":[],"label_agreement":null},{"id":"W1990918714","doi":"10.1109/tnb.2012.2214231","title":"Robust and Global Delay-Dependent Stability for Genetic Regulatory Networks With Parameter Uncertainties","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on NanoBioscience","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"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 Saskatchewan","funders":"","keywords":"Stability (learning theory); Gene regulatory network; Linear matrix inequality; Computer science; Genetic network; Nonlinear system; Control theory (sociology); Mathematical optimization; Mathematics; Biology; Gene; Genetics; Physics; Control (management); Artificial intelligence","score_opus":0.017138304677534077,"score_gpt":0.22701812240738722,"score_spread":0.20987981772985315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990918714","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":[0.5462358,0.00039395486,0.45294708,0.000021341668,0.00017234424,0.00018632332,0.000019614457,0.000011828072,0.000011733372],"genre_scores_gemma":[0.99173266,0.00008851223,0.0077692703,0.000121430574,0.000081768754,0.00007451491,0.0000040077416,0.000015395131,0.00011241402],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985733,0.00006554914,0.00019440531,0.00049774087,0.00019648588,0.00047253649],"domain_scores_gemma":[0.99915457,0.000030010448,0.000072827774,0.00046084257,0.00008878567,0.00019299386],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028520072,0.00020772514,0.0001666634,0.000036197973,0.00028062795,0.000038868846,0.00017533294,0.00013793066,0.000011384604],"category_scores_gemma":[0.0000062958657,0.00017440885,0.00010108882,0.00023449422,0.00038477714,0.00001631442,0.000004604245,0.00006644454,0.0000012265625],"study_design_candidate":"simulation_or_modeling","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":[0.0008218414,0.0006996641,0.04386817,0.00007365317,0.00037048315,0.0000021881697,0.00015142464,0.82663935,0.10376286,0.00006744022,0.00031717942,0.023225715],"study_design_scores_gemma":[0.004017259,0.0038853053,0.107504405,0.000102508966,0.0012183576,0.00041478683,0.0010053455,0.08802407,0.7874992,0.00014906807,0.0032605056,0.0029191903],"about_ca_topic_score_codex":0.000018989915,"about_ca_topic_score_gemma":0.0001737028,"teacher_disagreement_score":0.73861533,"about_ca_system_score_codex":0.000061813065,"about_ca_system_score_gemma":0.00007361436,"threshold_uncertainty_score":0.71121866},"labels":[],"label_agreement":null},{"id":"W1991118948","doi":"10.1088/0305-4470/39/46/l01","title":"A simple method for reverse engineering causal networks","year":2006,"lang":"en","type":"article","venue":"Journal of Physics A Mathematical and General","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"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 Calgary","funders":"","keywords":"Simple (philosophy); Reverse engineering; Computer science; Epistemology; Programming language; Philosophy","score_opus":0.0070235075478783625,"score_gpt":0.24923100474950555,"score_spread":0.24220749720162718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1991118948","genre_codex":"methods","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":[0.31899664,0.00028477388,0.6805594,0.000050203118,0.000034336736,0.00004982896,0.0000026282946,0.000002007507,0.000020200867],"genre_scores_gemma":[0.8025529,0.00003267753,0.19326195,0.00011441875,0.003594413,0.000007366849,0.000020780975,0.00003183393,0.00038367178],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931955,0.000022009386,0.00028357183,0.00011159644,0.00009664306,0.00016662668],"domain_scores_gemma":[0.9995544,0.000028993798,0.00014155693,0.00010693353,0.0000970541,0.00007107785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000260911,0.00011255713,0.00023865259,0.000020417274,0.00003615602,0.00002167456,0.00007322191,0.000068022826,0.000004463325],"category_scores_gemma":[0.000023282106,0.00009090093,0.00019994374,0.00005979768,0.000018878658,0.0000044859453,0.000035694833,0.000063498264,3.356635e-7],"study_design_candidate":"simulation_or_modeling","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":[0.0001287062,0.00028746284,0.0005042968,0.0001671957,0.00061633077,0.00001143727,0.00003794097,0.4514017,0.4670769,0.050763953,0.021813212,0.007190861],"study_design_scores_gemma":[0.0014388281,0.00048495072,0.0005577633,0.00004149749,0.00046435092,0.00017558852,0.000021684127,0.86037034,0.05284943,0.06843903,0.014729401,0.00042711353],"about_ca_topic_score_codex":0.000002266206,"about_ca_topic_score_gemma":0.0000014127855,"teacher_disagreement_score":0.48729742,"about_ca_system_score_codex":0.0000069333105,"about_ca_system_score_gemma":0.00001940733,"threshold_uncertainty_score":0.37068325},"labels":[],"label_agreement":null},{"id":"W1991932257","doi":"10.1016/j.bpj.2012.12.015","title":"Physical Constraints on Biological Integral Control Design for Homeostasis and Sensory Adaptation","year":2013,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":103,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; College of Family Physicians of Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Control engineering; Robustness (evolution); Computer science; Adaptation (eye); Control theory (sociology); Controller (irrigation); Realization (probability); Variety (cybernetics); Process (computing); Control (management); Set (abstract data type); Feedback control; Synthetic biology; Control system; Sensory Adaptation; Sensory system; Engineering; Mathematics; Artificial intelligence; Neuroscience; Biology","score_opus":0.027271503305385168,"score_gpt":0.25269221217126675,"score_spread":0.22542070886588159,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1991932257","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":[0.91310704,0.00007730441,0.0861358,0.00028964388,0.0000674539,0.0002718688,0.000015880056,0.000009075735,0.000025946918],"genre_scores_gemma":[0.99596274,0.0000802721,0.00257138,0.00027312472,0.0010194983,0.00003498573,0.000017168655,0.000016493586,0.000024365843],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99892926,0.00017753219,0.0001898407,0.00028903663,0.0001312697,0.00028305073],"domain_scores_gemma":[0.9993017,0.00010128276,0.00011104193,0.00013397404,0.00015479879,0.00019723614],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014969826,0.00018894905,0.000249802,0.000043132088,0.00014035188,0.000069999965,0.000108836386,0.00012378978,0.000021720238],"category_scores_gemma":[0.000096810545,0.00013744185,0.00022793928,0.000057297773,0.00026679196,0.000006963894,0.000023099436,0.0001465979,0.000020275142],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021529723,0.000146761,0.00008239003,0.000002805541,0.00018817642,0.0000025127863,0.000027793014,0.00091934047,0.92219067,0.00023046443,0.0010408977,0.07495291],"study_design_scores_gemma":[0.009813636,0.01161627,0.021649878,0.00007848925,0.0004711104,0.0003864974,0.0012101496,0.18846701,0.7557135,0.0055077113,0.0032445872,0.001841141],"about_ca_topic_score_codex":0.0000016849037,"about_ca_topic_score_gemma":3.2558265e-7,"teacher_disagreement_score":0.18754767,"about_ca_system_score_codex":0.000017216698,"about_ca_system_score_gemma":0.000037469566,"threshold_uncertainty_score":0.5604716},"labels":[],"label_agreement":null},{"id":"W1992263379","doi":"10.4137/sti.s3534","title":"Network Robustness Due to Multiple Positive Feedback Loops: A Systematic Study of a Th Cell Differentiation Model","year":2010,"lang":"en","type":"article","venue":"Signal Transduction Insights","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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; Genome Canada","funders":"","keywords":"Positive feedback; Robustness (evolution); Negative feedback; Bistability; In silico; Feedback control; Computer science; Control theory (sociology); Systems biology; Boolean network; Biological system; Biology; Physics; Bioinformatics; Control (management); Artificial intelligence; Engineering; Genetics; Gene","score_opus":0.00928493496427499,"score_gpt":0.21018207082895185,"score_spread":0.20089713586467686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992263379","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":[0.8743271,0.00012785064,0.12434839,0.000014309557,0.00022340055,0.0008892092,0.0000057971065,0.000015503827,0.000048406808],"genre_scores_gemma":[0.9983643,0.000004301836,0.0009051756,0.000022358654,0.00034146957,0.00010622808,0.00006149867,0.000032505708,0.0001621148],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983588,0.00019969852,0.00047251457,0.00046231967,0.00027778026,0.00022889375],"domain_scores_gemma":[0.99896836,0.000020651907,0.00019386367,0.00042829182,0.0002692244,0.000119626995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016177393,0.00023761364,0.0004087821,0.000105424144,0.00014523572,0.000024852965,0.00019170318,0.00017197052,0.000022593204],"category_scores_gemma":[0.000009772223,0.00020962021,0.00015457331,0.00033814335,0.000037294674,0.000010595374,0.00003162044,0.00014001876,0.0000042908387],"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":[0.000118362565,0.00041382262,0.00024797235,0.00029374837,0.00016123845,0.0000013626259,0.0008605115,0.51234955,0.48546496,0.000012774775,0.000048312915,0.000027357197],"study_design_scores_gemma":[0.0033548982,0.0016124797,0.0054206178,0.00042163426,0.0013110315,0.000030273011,0.0020759602,0.35184166,0.6326643,0.0002817564,0.000016006952,0.00096939225],"about_ca_topic_score_codex":0.000021099062,"about_ca_topic_score_gemma":0.00054173626,"teacher_disagreement_score":0.16050792,"about_ca_system_score_codex":0.000014491576,"about_ca_system_score_gemma":0.00004406566,"threshold_uncertainty_score":0.8548064},"labels":[],"label_agreement":null},{"id":"W1992306462","doi":"10.1089/cmb.2008.21tt","title":"How to Synchronize Biological Clocks","year":2009,"lang":"en","type":"article","venue":"Journal of Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":47,"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":"Institute of Genetics; European Commission","keywords":"Biological clock; Construct (python library); Computer science; Biological network; Synchronization (alternating current); Set (abstract data type); Distributed computing; Theoretical computer science; Computer network; Biology; Computational biology; Programming language; Neuroscience","score_opus":0.01107651730193498,"score_gpt":0.2620000061672376,"score_spread":0.25092348886530264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992306462","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":[0.8918534,0.001001917,0.10212451,0.004678157,0.00016613195,0.000055890938,0.000004343385,0.00000442644,0.00011122147],"genre_scores_gemma":[0.9840327,0.000044911627,0.013616773,0.0013533533,0.000823672,7.559965e-7,0.000037465303,0.0000050833223,0.000085293104],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991299,0.000110110836,0.00029361137,0.00017638429,0.000106996755,0.00018301049],"domain_scores_gemma":[0.9991841,0.00003262989,0.00021676,0.000111809,0.00032208537,0.00013262648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024126479,0.00011890902,0.00023517097,0.000110655674,0.00004647966,0.000021535672,0.00022770427,0.00014678286,0.000014598947],"category_scores_gemma":[0.00013032554,0.00009176267,0.00018785917,0.00014081804,0.0000518706,0.0000033088138,0.00003912904,0.00009179422,0.000006104042],"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":[0.0005608269,0.00033361808,0.018903876,0.000005373292,0.00066400476,0.000041688952,0.000054152613,0.16927595,0.6862335,0.0043897526,0.031703413,0.0878338],"study_design_scores_gemma":[0.0043333326,0.020530479,0.27102512,0.00005763143,0.0002305407,0.0022558453,0.00017616541,0.0027011,0.057538144,0.08058719,0.5590666,0.0014978367],"about_ca_topic_score_codex":2.3603994e-7,"about_ca_topic_score_gemma":6.608795e-7,"teacher_disagreement_score":0.62869537,"about_ca_system_score_codex":0.0000213203,"about_ca_system_score_gemma":0.0000935352,"threshold_uncertainty_score":0.37419727},"labels":[],"label_agreement":null},{"id":"W1992673504","doi":"10.1109/tnb.2011.2178429","title":"Stability and Bifurcation Analysis of Models for Zebrafish Somitogenesis","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on NanoBioscience","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"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 Saskatchewan","funders":"","keywords":"Somitogenesis; Bifurcation; Zebrafish; Bifurcation theory; Stability (learning theory); Paraxial mesoderm; Oscillation (cell signaling); Computer science; Control theory (sociology); Nonlinear system; Mathematics; Physics; Somite; Artificial intelligence; Biology; Mesoderm","score_opus":0.03351465030413041,"score_gpt":0.23982597124947588,"score_spread":0.2063113209453455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992673504","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":[0.54016894,0.000040663763,0.45956057,0.000008287801,0.0000446201,0.000097435666,0.00004190581,0.0000049282435,0.000032642227],"genre_scores_gemma":[0.9967283,0.00007092662,0.0030573353,0.000034412515,0.000008436004,0.0000357242,0.0000064285737,0.0000072992225,0.000051155133],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990993,0.00003775354,0.00020591587,0.0003951238,0.000111180074,0.00015070503],"domain_scores_gemma":[0.9993317,0.000017592909,0.0000858428,0.00037210577,0.00012810773,0.00006461176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024661486,0.00010295442,0.00017440287,0.00018715647,0.00011700729,0.0000076203432,0.00014821485,0.00008245578,0.0000187946],"category_scores_gemma":[0.000005558387,0.00009971006,0.00020116755,0.00070145854,0.00018407586,0.0000108299755,0.0000021063192,0.00002268376,3.1557522e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008613015,0.00018693283,0.000766847,0.000013680898,0.0003492795,5.328464e-8,0.00016992698,0.015802886,0.9796006,0.00004747361,0.000009755351,0.0029664012],"study_design_scores_gemma":[0.00014957893,0.00015527084,0.0025399916,0.0000024035376,0.00059161015,5.01478e-7,0.000059678,0.031858847,0.9644183,0.00008515052,0.000024917124,0.00011374388],"about_ca_topic_score_codex":0.00004073303,"about_ca_topic_score_gemma":0.00019518583,"teacher_disagreement_score":0.45655933,"about_ca_system_score_codex":0.000012344508,"about_ca_system_score_gemma":0.000049289283,"threshold_uncertainty_score":0.4066058},"labels":[],"label_agreement":null},{"id":"W1993256693","doi":"10.1016/j.jbiotec.2010.06.018","title":"Synchronized populations of Escherichia coli using simplified self-cycling fermentation","year":2010,"lang":"en","type":"article","venue":"Journal of Biotechnology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Biological system; Exponential growth; Growth rate; Fermentation; Escherichia coli; Volume (thermodynamics); Cycling; Bacterial growth; Carbon cycle; Temperature cycling; Biology; Chemistry; Environmental science; Biophysics; Mathematics; Biochemistry; Thermodynamics; Thermal; Physics; Ecology; Genetics","score_opus":0.013718367705498256,"score_gpt":0.2774631982377024,"score_spread":0.2637448305322041,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993256693","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":[0.99007344,0.00028150762,0.008979081,0.00028030263,0.00028910468,0.00006651775,0.0000019793904,0.000009801391,0.0000182824],"genre_scores_gemma":[0.96377903,0.000076316275,0.035902,0.000032082702,0.00017733464,7.0689407e-7,0.0000060273355,0.000014451409,0.000012034617],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990637,0.000042785992,0.0004909908,0.00013446731,0.00011592538,0.00015213061],"domain_scores_gemma":[0.9988497,0.0000065685654,0.0006494748,0.00026322482,0.00018439366,0.000046669913],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002495845,0.00010432897,0.00024590318,0.0001973906,0.00006106465,0.000007937234,0.00020678282,0.0004175401,0.000015869218],"category_scores_gemma":[0.000095798365,0.000100195684,0.00015612433,0.0002536891,0.00009277271,0.0000056279523,0.000062566345,0.00024334092,7.336415e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032326247,0.000059048547,0.002516459,0.000006924579,0.00014909338,0.0000019446989,0.000014465673,0.0014700646,0.9948117,0.00032410136,0.000053921995,0.0005599435],"study_design_scores_gemma":[0.0006142527,0.00019133044,0.003712558,0.000009775893,0.00018859054,0.0000877984,0.000113119706,0.0019487744,0.9918681,0.000556898,0.0005965034,0.00011234559],"about_ca_topic_score_codex":0.0000125514825,"about_ca_topic_score_gemma":0.000045557783,"teacher_disagreement_score":0.026922919,"about_ca_system_score_codex":0.00002769103,"about_ca_system_score_gemma":0.0001276673,"threshold_uncertainty_score":0.40858614},"labels":[],"label_agreement":null},{"id":"W1994540622","doi":"10.1016/j.jtbi.2006.10.027","title":"Robustness and evolvability in genetic regulatory networks","year":2006,"lang":"en","type":"article","venue":"Journal of Theoretical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":281,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"National Institute of General Medical Sciences; Consejo Nacional de Ciencia y Tecnología; National Institutes of Health; National Science Foundation","keywords":"Evolvability; Robustness (evolution); Gene regulatory network; Organism; Biology; Gene; Attractor; Biological network; Computer science; Genetics; Computational biology; Mathematics; Gene expression","score_opus":0.0029198431140574645,"score_gpt":0.2149901533059086,"score_spread":0.21207031019185113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994540622","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":[0.97407323,0.004636323,0.02075785,0.00018866532,0.0001263543,0.00005712323,9.707203e-7,0.0000024574802,0.00015700146],"genre_scores_gemma":[0.9970184,0.0001802479,0.0021629655,0.0000654514,0.000532722,0.0000017491403,0.0000066834805,0.000012673954,0.00001913937],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985603,0.00031875522,0.0005335836,0.00023789231,0.000080971426,0.00026849267],"domain_scores_gemma":[0.99929404,0.00005531032,0.00019322905,0.0002548157,0.00011241918,0.000090155045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071097515,0.00014429563,0.00032470323,0.00009064083,0.00003023856,0.000010528272,0.00019313075,0.0002850866,0.000041827283],"category_scores_gemma":[0.00010221457,0.0001150695,0.00014102366,0.00012475952,0.00074502116,0.0000027021479,0.000099774334,0.00017325043,4.0416546e-7],"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":[0.001068794,0.00037450017,0.5686189,0.000031300016,0.00023305081,0.0000543626,0.000012472502,0.2591322,0.10770906,0.051904272,0.0013880127,0.009473064],"study_design_scores_gemma":[0.0033925306,0.0019222746,0.83057314,0.00006743293,0.00030661433,0.0009261185,0.000063620486,0.057578046,0.015022551,0.08631745,0.0029122105,0.0009180167],"about_ca_topic_score_codex":0.0000043710593,"about_ca_topic_score_gemma":0.000018123008,"teacher_disagreement_score":0.26195422,"about_ca_system_score_codex":0.00002367658,"about_ca_system_score_gemma":0.000044931585,"threshold_uncertainty_score":0.4692398},"labels":[],"label_agreement":null},{"id":"W1995759967","doi":"10.1109/tnb.2003.820283","title":"A genetic circuit amplifier: design and simulation","year":2003,"lang":"en","type":"article","venue":"IEEE Transactions on NanoBioscience","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"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":"Discrete circuit; Linear circuit; Amplifier; Circuit extraction; Computer science; Equivalent circuit; Electronic circuit simulation; RL circuit; Electronic engineering; Circuit design; Capacitor; Electrical element; Electronic circuit; RC circuit; Electrical engineering; Engineering; Voltage; CMOS","score_opus":0.018979006545935685,"score_gpt":0.24031110375729234,"score_spread":0.22133209721135666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995759967","genre_codex":"methods","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":[0.2916642,0.00012692375,0.7078968,0.000008672878,0.00010912068,0.0001196264,0.000001981749,0.0000108413915,0.000061770625],"genre_scores_gemma":[0.9948081,0.000095724565,0.004497787,0.00012041173,0.000017520186,0.000017891385,5.550873e-7,0.0000124227645,0.0004295869],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99897105,0.0001085361,0.0001431775,0.000418608,0.00014196266,0.00021665041],"domain_scores_gemma":[0.99948037,0.000027297214,0.000042857384,0.0003031539,0.00004752564,0.00009882022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001929476,0.00012857954,0.00009423916,0.00008103257,0.00022974859,0.000033801665,0.000109038214,0.000091374546,0.000024877749],"category_scores_gemma":[0.000011442209,0.0001285888,0.00006294227,0.0002992468,0.00013469931,0.0000058021965,9.628918e-7,0.000051422023,0.000011388624],"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":[0.000010052742,0.000042131483,0.00009001565,0.0000028412119,0.000015380556,8.2464436e-7,0.000020691337,0.5688409,0.4263466,0.000014208496,0.000020808384,0.0045955284],"study_design_scores_gemma":[0.0005705106,0.00045299236,0.0014977263,0.000013358762,0.00009119902,0.000048571426,0.00003858773,0.049606793,0.9423107,0.00027998083,0.0046089045,0.00048070055],"about_ca_topic_score_codex":0.000003092593,"about_ca_topic_score_gemma":0.0000058819464,"teacher_disagreement_score":0.70339906,"about_ca_system_score_codex":0.00001644186,"about_ca_system_score_gemma":0.000069802205,"threshold_uncertainty_score":0.5243699},"labels":[],"label_agreement":null},{"id":"W1996507148","doi":"10.1159/000106145","title":"The Realistic Modeling of Biological Systems: A Workshop Synopsis","year":2006,"lang":"en","type":"article","venue":"Complexus","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Metabolomics Innovation Centre; Health Sciences Centre; University of Alberta","funders":"","keywords":"Biomedicine; Field (mathematics); Theme (computing); Computer science; Diversity (politics); Management science; Data science; Representation (politics); Engineering ethics; Scale (ratio); Modelling biological systems; Interdisciplinarity; Key (lock); Systems biology; Biology; Sociology; Engineering; Social science; Bioinformatics; Mathematics; World Wide Web; Political science","score_opus":0.034472905316399974,"score_gpt":0.25770154901864967,"score_spread":0.2232286437022497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996507148","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":[0.9608466,0.0118504595,0.02472979,0.00007583122,0.0001386236,0.00014935256,0.0000143033985,0.000018228853,0.0021767977],"genre_scores_gemma":[0.99883896,0.00010644966,0.00019944798,0.0000132324785,0.00027179296,0.000015029464,0.00009051434,0.000011188474,0.00045337813],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907154,0.00009869134,0.00028814038,0.00022426914,0.00010614579,0.00021123771],"domain_scores_gemma":[0.9992764,0.000040976374,0.00009522074,0.00045018567,0.000102941936,0.00003427652],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002166508,0.000111404916,0.00017145016,0.000021611779,0.00013398641,0.000023531446,0.00024807657,0.00009690687,0.000003882709],"category_scores_gemma":[0.000054842327,0.00007582581,0.00011806433,0.00012861153,0.00011398058,7.5351016e-7,0.0000996751,0.0000444247,0.000003428927],"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":[0.00009127396,0.000080741906,0.004356124,0.00002875317,0.00023236229,0.0000043509217,0.000011327112,0.8933906,0.08113838,0.0084133595,0.011313358,0.00093939196],"study_design_scores_gemma":[0.0006029759,0.00018860103,0.0035380404,0.00005779229,0.00017248256,0.000047438698,0.00038208283,0.95098156,0.003457444,0.003012751,0.036997113,0.00056172867],"about_ca_topic_score_codex":0.000116196185,"about_ca_topic_score_gemma":0.00008831476,"teacher_disagreement_score":0.07768093,"about_ca_system_score_codex":0.000011129551,"about_ca_system_score_gemma":0.00002280154,"threshold_uncertainty_score":0.3092087},"labels":[],"label_agreement":null},{"id":"W1997272672","doi":"10.1038/sj.ijo.0801904","title":"Regulation and the ponderostat","year":2001,"lang":"en","type":"review","venue":"International Journal of Obesity","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":38,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Set point; Diagram; Set (abstract data type); Control theory (sociology); Work (physics); Medicine; Endocrinology; Internal medicine; Mathematics; Control (management); Computer science; Physics; Thermodynamics; Statistics; Engineering; Artificial intelligence","score_opus":0.016398882625037123,"score_gpt":0.2990911841435087,"score_spread":0.2826923015184716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997272672","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010877515,0.9972258,0.00090899883,0.00009983111,0.0003851927,0.00008964251,0.000006240166,0.0000013591539,0.0001951705],"genre_scores_gemma":[0.0032861219,0.9946816,0.00017012464,0.000048660288,0.00115475,0.0000017862436,0.000045143395,0.00001458836,0.0005972421],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987829,0.00019824234,0.00048490165,0.00014023753,0.00030832234,0.00008543667],"domain_scores_gemma":[0.99864393,0.00004342648,0.00076696795,0.00017436934,0.00032285965,0.00004845224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057424925,0.0001566632,0.0004924508,0.00010126369,0.00004242786,0.00005278601,0.0004297467,0.00014752701,0.000026877313],"category_scores_gemma":[0.00009057852,0.000096309326,0.000502994,0.00007846613,0.00011466586,0.0000048409215,0.00013636038,0.00016000164,0.0000037344182],"study_design_candidate":"not_applicable","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":[0.00014649428,0.00006314202,0.0002863075,0.00020106406,0.002641399,0.000034557317,0.000025924532,0.000095434974,0.00004072105,0.00048215679,0.005796365,0.99018645],"study_design_scores_gemma":[0.000455765,0.000026169433,0.00016225672,0.0004405114,0.00050626684,0.0008388237,0.000005577117,0.0000133338135,0.0000129715545,0.00027140588,0.99717116,0.000095729265],"about_ca_topic_score_codex":0.0000040574887,"about_ca_topic_score_gemma":0.0000063912457,"teacher_disagreement_score":0.99137485,"about_ca_system_score_codex":0.00003994868,"about_ca_system_score_gemma":0.00011943424,"threshold_uncertainty_score":0.392738},"labels":[],"label_agreement":null},{"id":"W1998099667","doi":"10.1049/iet-syb.2013.0060","title":"Properties of sparse penalties on inferring gene regulatory networks from time‐course gene expression data","year":2014,"lang":"en","type":"article","venue":"IET Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Gene expression; Computational biology; Gene regulatory network; Gene; Regulation of gene expression; Gene expression profiling; Biology; Genetics; Computer science","score_opus":0.02443517666078463,"score_gpt":0.2377035775370188,"score_spread":0.21326840087623417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998099667","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":[0.98350066,0.011052081,0.004416154,0.000024228402,0.0005292427,0.00023432955,0.000079071535,0.000031241743,0.00013296673],"genre_scores_gemma":[0.99621123,0.00018773902,0.00042557038,0.000062556814,0.0015438643,0.000026047142,0.0011499419,0.00004590594,0.00034715552],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9975174,0.00056551973,0.0005655503,0.00080940884,0.00016065837,0.00038142776],"domain_scores_gemma":[0.99722004,0.000033874418,0.00036947854,0.0021453241,0.00011826587,0.00011303432],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006529251,0.00030791402,0.00056558935,0.00007085674,0.000102667545,0.000021119138,0.0007595194,0.00044731214,0.000018092003],"category_scores_gemma":[0.000071891605,0.00024826822,0.00011927842,0.00009088134,0.00021604817,0.000008173993,0.0005364918,0.00012405068,0.000027169086],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010794887,0.00005566534,0.0071861697,0.000020253676,0.00022277613,0.0000010098912,0.000020786485,0.018282183,0.9709158,0.000022263366,0.002491306,0.00067386066],"study_design_scores_gemma":[0.00068117306,0.00036220797,0.003814372,0.00021841431,0.00017295049,0.0000152333005,0.000055654193,0.040898245,0.9429547,0.000026394422,0.01027814,0.0005225172],"about_ca_topic_score_codex":0.00012957574,"about_ca_topic_score_gemma":0.000027288394,"teacher_disagreement_score":0.027961077,"about_ca_system_score_codex":0.000016895701,"about_ca_system_score_gemma":0.0000597765,"threshold_uncertainty_score":0.99999696},"labels":[],"label_agreement":null},{"id":"W1998811148","doi":"10.1049/iet-syb.2012.0051","title":"M‐matrix‐based stability conditions for genetic regulatory networks with time‐varying delays and noise perturbations","year":2013,"lang":"en","type":"article","venue":"IET Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"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 Saskatchewan","funders":"National Natural Science Foundation of China","keywords":"Stability (learning theory); Control theory (sociology); Gene regulatory network; Linear matrix inequality; Noise (video); Lyapunov function; Function (biology); Matrix (chemical analysis); Mathematics; Mathematical optimization; Computer science; Genetics; Gene; Physics; Biology; Nonlinear system","score_opus":0.008427456623912281,"score_gpt":0.2279552410640889,"score_spread":0.21952778444017662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998811148","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":[0.9487153,0.0031413443,0.04669505,0.0001143333,0.00012474533,0.0010232091,0.00007905441,0.00003391103,0.000073040814],"genre_scores_gemma":[0.9960442,0.000026735635,0.0019625695,0.00010280828,0.00032124342,0.0005759128,0.00066020724,0.000036055088,0.00027025427],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99843764,0.00020913976,0.0003534915,0.00055799965,0.000066820496,0.00037488787],"domain_scores_gemma":[0.9987597,0.000093626426,0.0001649927,0.0005668312,0.00026538878,0.00014945824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021324598,0.00023698188,0.00032760177,0.000068756824,0.00023456351,0.000041181087,0.00014679405,0.0003125852,0.000045433157],"category_scores_gemma":[0.00003511303,0.00019816634,0.00011029796,0.00012413911,0.00024825183,0.0000062954045,0.000046540383,0.000071667084,0.000011412764],"study_design_candidate":"simulation_or_modeling","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":[0.00015444477,0.00015540396,0.14821309,0.00019351898,0.00082541024,0.0000022052122,0.00005671313,0.15720738,0.68262595,0.00032351355,0.009702263,0.0005401299],"study_design_scores_gemma":[0.003658291,0.001873902,0.07725655,0.00009813686,0.0006623892,0.00017714087,0.00020593869,0.8915329,0.010063721,0.0003103022,0.012581105,0.0015796405],"about_ca_topic_score_codex":0.000058057096,"about_ca_topic_score_gemma":0.000028565864,"teacher_disagreement_score":0.73432547,"about_ca_system_score_codex":0.000029910318,"about_ca_system_score_gemma":0.00009583156,"threshold_uncertainty_score":0.8080989},"labels":[],"label_agreement":null},{"id":"W1999029348","doi":"10.1016/j.semcancer.2014.03.003","title":"Cancer systems biology and modeling: Microscopic scale and multiscale approaches","year":2014,"lang":"en","type":"review","venue":"Seminars in Cancer Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":57,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"","keywords":"Multiscale modeling; Cellular automaton; Systems biology; Rotation formalisms in three dimensions; Mesoscopic physics; Computer science; Scale (ratio); Complex system; Modeling and simulation; Cancer; Biology; Biological system; Statistical physics; Computational biology; Bioinformatics; Physics; Artificial intelligence; Mathematics; Simulation","score_opus":0.049897785214475604,"score_gpt":0.3489319452013307,"score_spread":0.2990341599868551,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1999029348","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016494637,0.98187274,0.00034399002,0.000028055729,0.000485589,0.0005504085,0.00016553354,0.000011580905,0.000047469897],"genre_scores_gemma":[0.010328575,0.9872037,0.00027992768,0.0000361947,0.00065542787,0.00069662253,0.00042832483,0.00007128274,0.00029991084],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9969803,0.00044751543,0.00066389603,0.0012920019,0.000050426886,0.0005658457],"domain_scores_gemma":[0.99892604,0.000044384193,0.00031754983,0.0005357845,0.000042056057,0.0001341819],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00038006945,0.0005834979,0.0018373837,0.00020305607,0.000083787585,0.000024968249,0.0003230951,0.0013243352,0.0000067738],"category_scores_gemma":[0.000020382244,0.0004948585,0.00018976507,0.00019237334,0.00043527718,0.0000026191258,0.0003845503,0.0003020812,0.0000016970147],"study_design_candidate":"not_applicable","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":[0.000021202128,0.000042305157,0.012084387,0.005853092,0.00055685535,0.0000016011414,0.000049517108,0.0008699622,0.0014703743,0.00005662507,0.00038582154,0.97860825],"study_design_scores_gemma":[0.00043858067,0.00017818972,0.000017441946,0.003549172,0.0006483046,0.00005103267,0.000039636212,0.006233275,0.00009146553,0.000053069478,0.9878659,0.00083390553],"about_ca_topic_score_codex":0.0007947589,"about_ca_topic_score_gemma":0.0011852966,"teacher_disagreement_score":0.9874801,"about_ca_system_score_codex":0.00008867104,"about_ca_system_score_gemma":0.00020168557,"threshold_uncertainty_score":0.99997216},"labels":[],"label_agreement":null},{"id":"W2000260940","doi":"10.1371/journal.pone.0027559","title":"The Bacterial Nanorecorder: Engineering E. coli to Function as a Chemical Recording Device","year":2011,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; National Institute for Nanotechnology","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Synthetic biology; Chemical biology; Function (biology); Biological system; Green fluorescent protein; Chemical genetics; Computational biology; Cell function; Chemical agents; Biophysics; Computer science; Biology; Nanotechnology; Chemistry; Cell; Small molecule; Biochemical engineering; Cell biology; Genetics; Materials science; Gene","score_opus":0.021254218987868185,"score_gpt":0.19125467030310214,"score_spread":0.17000045131523395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000260940","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":[0.9987043,0.0001501179,0.00030181126,0.000070562666,0.00013390603,0.0001343571,0.0000013558318,0.000021289565,0.00048225618],"genre_scores_gemma":[0.99631923,0.000056134257,0.0024977322,0.00009253988,0.0006047385,0.000051956587,0.000023236704,0.00002593925,0.00032849787],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992432,0.000023361912,0.00015199144,0.00024019847,0.000114416514,0.00022680427],"domain_scores_gemma":[0.99947584,0.000010592965,0.000043015367,0.00029823792,0.0000760005,0.00009633262],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012676974,0.00011385279,0.00012066126,0.000024548644,0.00008099187,0.000022775026,0.00015768052,0.00009350446,0.00007613161],"category_scores_gemma":[0.000103733786,0.00010037615,0.000066088374,0.00012425649,0.000015340102,0.0000025343772,0.000101023026,0.000057906764,0.000063071435],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001885516,0.000077281526,0.0003702394,0.000007943914,0.0002861407,4.6141525e-7,0.000025207872,0.000012436,0.9977041,0.000025502572,0.00034826176,0.00095386885],"study_design_scores_gemma":[0.00018364018,0.0002467144,0.0005707258,0.000026451038,0.0001768362,0.0000025131158,0.000023422375,0.00031288102,0.987555,0.00003632175,0.010668827,0.00019664025],"about_ca_topic_score_codex":0.000019519692,"about_ca_topic_score_gemma":0.00003595324,"teacher_disagreement_score":0.010320566,"about_ca_system_score_codex":0.000018430612,"about_ca_system_score_gemma":0.00002685356,"threshold_uncertainty_score":0.40932205},"labels":[],"label_agreement":null},{"id":"W2000692739","doi":"10.1089/cmb.2008.0087","title":"Heuristic Approach to Sparse Approximation of Gene Regulatory Networks","year":2008,"lang":"en","type":"article","venue":"Journal of Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"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 Calgary","funders":"","keywords":"Heuristic; Gene regulatory network; Computational biology; Computer science; Gene; Biology; Mathematics; Artificial intelligence; Mathematical optimization; Genetics; Gene expression","score_opus":0.014543373137551462,"score_gpt":0.2369159129839828,"score_spread":0.22237253984643132,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000692739","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":[0.5804891,0.0007389241,0.41842705,0.000035220288,0.0000981481,0.000057791407,0.0000032875303,0.000002057379,0.00014840765],"genre_scores_gemma":[0.94517714,0.000051109113,0.054009467,0.00013375386,0.0004682367,0.0000023917612,0.00010642947,0.000012065473,0.000039379178],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9987767,0.00014308431,0.000577858,0.00017802524,0.00016955467,0.00015477864],"domain_scores_gemma":[0.99872816,0.00003475576,0.00048977666,0.0001657923,0.0004754418,0.0001060497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034066263,0.00012353134,0.00030632238,0.00015955091,0.000055909382,0.0000034216341,0.00020494607,0.00013898428,0.000005634755],"category_scores_gemma":[0.000065248765,0.00011163518,0.00018472249,0.00019956472,0.00012674156,0.000004207802,0.000044883698,0.00008819644,0.0000020442387],"study_design_candidate":"simulation_or_modeling","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":[0.0001371209,0.00012711539,0.003829286,0.0000069280177,0.00020084852,0.0000026357766,0.000039894254,0.95031214,0.041586895,0.00045175053,0.0021487495,0.0011566551],"study_design_scores_gemma":[0.0064451904,0.0052756015,0.5110301,0.00010389972,0.0006628055,0.006029307,0.00020142614,0.33164713,0.11418789,0.011203293,0.011402236,0.0018111485],"about_ca_topic_score_codex":0.0000011832219,"about_ca_topic_score_gemma":3.3252775e-7,"teacher_disagreement_score":0.618665,"about_ca_system_score_codex":0.000019687854,"about_ca_system_score_gemma":0.0001290954,"threshold_uncertainty_score":0.45523506},"labels":[],"label_agreement":null},{"id":"W2001183149","doi":"10.1021/jp062739m","title":"Extracting Biochemical Parameters for Cellular Modeling:  A Mean-Field Approach","year":2006,"lang":"en","type":"article","venue":"The Journal of Physical Chemistry B","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"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":"Ribosome; Polymerase; Gene; RNA polymerase; Translation (biology); Gene expression; RNA; Biology; Function (biology); Messenger RNA; Computational biology; Physics; Genetics","score_opus":0.013178112627988977,"score_gpt":0.2348283189986562,"score_spread":0.2216502063706672,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001183149","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":[0.937595,0.0005689027,0.061306212,0.00009031723,0.000018220933,0.00006666254,0.00000219336,0.0000041988283,0.00034825888],"genre_scores_gemma":[0.9963565,0.000009749002,0.0018351118,0.000036585312,0.0015767073,0.000004471408,0.000022922417,0.000022906772,0.00013503198],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99900836,0.000035762343,0.00032597905,0.0001709,0.00021902134,0.00023999132],"domain_scores_gemma":[0.99912655,0.00007535404,0.00026785,0.0002989869,0.00015492203,0.00007633883],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003423939,0.00016849328,0.0002398317,0.000012617356,0.00007842217,0.000020051133,0.00035991738,0.00011785447,0.0000025170032],"category_scores_gemma":[0.00007578379,0.000119958735,0.0004263369,0.00008728019,0.000057051653,0.000004805774,0.00005688103,0.00020495491,5.4342985e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014082217,0.0001370233,0.000014418334,0.000028184055,0.00010676329,7.109823e-7,0.00002419878,0.060591888,0.93767166,0.000006655763,0.0011480264,0.00012966603],"study_design_scores_gemma":[0.000329651,0.00008518214,0.0000016869137,0.000009851273,0.00021213901,0.000032490745,0.000109566136,0.08070716,0.91761595,0.000424002,0.0003354233,0.00013689684],"about_ca_topic_score_codex":0.000006038158,"about_ca_topic_score_gemma":2.4650578e-7,"teacher_disagreement_score":0.0594711,"about_ca_system_score_codex":0.000018767167,"about_ca_system_score_gemma":0.000047706068,"threshold_uncertainty_score":0.48917753},"labels":[],"label_agreement":null},{"id":"W2001249982","doi":"10.11145/150","title":"On the Distribution of Transcription Times","year":2013,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Lethbridge","funders":"","keywords":"Transcription (linguistics); Limiting; Gaussian; Mathematics; Physics; Statistical physics; Quantum mechanics; Engineering","score_opus":0.09271175219794832,"score_gpt":0.4490821712689985,"score_spread":0.3563704190710502,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001249982","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":[0.9909692,0.006168316,0.0010207404,0.00028793866,0.00012993613,0.00031710128,0.000032852233,0.000005513672,0.0010684482],"genre_scores_gemma":[0.9964253,0.0027166673,0.00002746551,0.00014941269,0.00011813346,0.000033801032,0.000098445395,0.000021432195,0.000409345],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984367,0.00023918206,0.00048789984,0.00027661715,0.000345287,0.00021432045],"domain_scores_gemma":[0.99859184,0.000057500045,0.0004515863,0.0005138911,0.00028758944,0.00009761811],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00059948064,0.00018995408,0.00033557718,0.00011569593,0.00013084196,0.00021224188,0.0012183371,0.00011676796,0.004449039],"category_scores_gemma":[0.000115676135,0.00013730476,0.00026159658,0.0003916799,0.00013254193,0.00005040395,0.00020943888,0.00013444593,0.000014304231],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007366956,0.00012353637,0.023877604,0.000019845413,0.00026997834,6.247274e-7,0.000016847593,0.0013969286,0.8765944,0.00023781123,0.09322442,0.0041643335],"study_design_scores_gemma":[0.00030509257,0.00003527117,0.3126924,0.000104274484,0.00013991722,0.000004006724,0.000046358902,0.00038103043,0.67263776,0.0053363247,0.008047146,0.0002703933],"about_ca_topic_score_codex":0.0002021636,"about_ca_topic_score_gemma":0.000013482403,"teacher_disagreement_score":0.28881478,"about_ca_system_score_codex":0.000023991977,"about_ca_system_score_gemma":0.000053103708,"threshold_uncertainty_score":0.99646103},"labels":[],"label_agreement":null},{"id":"W2001477533","doi":"10.1145/1389095.1389150","title":"Evolution of discrete gene regulatory models","year":2008,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"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 Calgary","funders":"","keywords":"Boolean network; Gene regulatory network; Attractor; Computer science; Crossover; Graph; Entropy (arrow of time); Random graph; Boolean function; Gene; Theoretical computer science; Topology (electrical circuits); Mathematics; Biology; Genetics; Algorithm; Artificial intelligence; Physics; Gene expression; Combinatorics","score_opus":0.010125134313496525,"score_gpt":0.2084462078822069,"score_spread":0.1983210735687104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001477533","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":[0.93694156,0.0015713222,0.05866071,0.000015425523,0.00003374402,0.000055356286,0.0000034435661,0.000010435257,0.002707987],"genre_scores_gemma":[0.9942307,0.00013896785,0.0029161968,0.000022792077,0.00012423415,0.000004376289,0.000035376124,0.000013973643,0.0025134056],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99926484,0.000033265835,0.00018604464,0.00022865123,0.00014030765,0.00014686977],"domain_scores_gemma":[0.99934137,0.000002047736,0.00006957971,0.00044848342,0.00008104076,0.000057507128],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008332831,0.00009736576,0.0001313604,0.000042564523,0.000053954067,0.0000015453487,0.00012082175,0.00010001754,0.000023863622],"category_scores_gemma":[0.0000059947183,0.00008982993,0.00014211843,0.00010955942,0.00010701474,0.0000028913043,0.00006770587,0.000026347183,0.0000045013007],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027310345,0.000027151815,0.0039837565,0.0000044206167,0.00008444018,0.0000013101106,0.000017351123,0.037704274,0.954484,0.00089858385,0.002557184,0.00021025156],"study_design_scores_gemma":[0.00035279454,0.000107425796,0.020389346,0.0000045772053,0.000050828516,0.000038940736,0.000031660657,0.016549967,0.960528,0.0008589365,0.0008501821,0.00023731009],"about_ca_topic_score_codex":0.000022505214,"about_ca_topic_score_gemma":0.0000126321065,"teacher_disagreement_score":0.0572891,"about_ca_system_score_codex":0.000017035118,"about_ca_system_score_gemma":0.00006191725,"threshold_uncertainty_score":0.36631584},"labels":[],"label_agreement":null},{"id":"W2002390431","doi":"10.1007/s002850000072","title":"Numerical bifurcation analysis of delay differential equations arising from physiological modeling","year":2001,"lang":"en","type":"article","venue":"Journal of Mathematical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":121,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Delay differential equation; Bifurcation; Stability (learning theory); Mathematics; Continuation; Numerical continuation; Applied mathematics; Differential equation; Control theory (sociology); Numerical analysis; Steady state (chemistry); Hopf bifurcation; Numerical stability; Mathematical analysis; Computer science; Nonlinear system; Physics","score_opus":0.02989874975439959,"score_gpt":0.29101200424257345,"score_spread":0.26111325448817385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002390431","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":[0.53216463,0.00019816717,0.46750754,0.00004682696,0.000029846578,0.000022348504,0.0000037640718,0.0000019560978,0.000024953755],"genre_scores_gemma":[0.994072,0.00010443972,0.00540696,0.000036866753,0.00026462963,0.0000017977133,0.000092989154,0.000008727426,0.000011585441],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984699,0.00019791942,0.00079866766,0.00019956905,0.0001520087,0.00018196733],"domain_scores_gemma":[0.9988365,0.000117463605,0.00046657253,0.00025579956,0.0002287842,0.000094860676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002595321,0.0001378631,0.0006052948,0.00019855794,0.000043985747,0.000009611786,0.0002314012,0.00022291183,0.00023254029],"category_scores_gemma":[0.0003352421,0.00010025671,0.000531849,0.00038892488,0.00008532766,0.00000505317,0.000060379465,0.00012701061,0.000004414018],"study_design_candidate":"simulation_or_modeling","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":[0.00017316188,0.00052764826,0.005954357,0.000009283633,0.004266485,0.0000047976646,0.00008054661,0.16170406,0.8242857,0.0013107978,0.000072325114,0.0016108212],"study_design_scores_gemma":[0.0005628864,0.00049922406,0.0040183696,0.000025079928,0.0030424471,0.000026318412,0.00008660572,0.9677631,0.010047827,0.013580229,0.00009981108,0.0002481031],"about_ca_topic_score_codex":0.0000068634627,"about_ca_topic_score_gemma":0.0000030569245,"teacher_disagreement_score":0.8142379,"about_ca_system_score_codex":0.000017383472,"about_ca_system_score_gemma":0.000038218284,"threshold_uncertainty_score":0.408835},"labels":[],"label_agreement":null},{"id":"W2004289452","doi":"10.1016/j.ymeth.2013.05.013","title":"Using evolutionary computations to understand the design and evolution of gene and cell regulatory networks","year":2013,"lang":"en","type":"review","venue":"Methods","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":47,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"British Columbia Institute of Technology","funders":"National Institute of General Medical Sciences","keywords":"Computer science; Gene regulatory network; Context (archaeology); Systems biology; In silico; Evolutionary computation; Evolutionary algorithm; Field (mathematics); Computational biology; Theoretical computer science; Biology; Artificial intelligence; Gene; Genetics","score_opus":0.08751894512917092,"score_gpt":0.36885134896224464,"score_spread":0.28133240383307373,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004289452","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00014610557,0.5094068,0.49004197,0.0000035629237,0.00004310358,0.00034309705,0.0000030241492,0.0000027923945,0.000009501695],"genre_scores_gemma":[0.0003016768,0.5755189,0.42388234,0.0000110488245,0.00013111637,0.000017313514,0.000024723517,0.000030848933,0.00008202652],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9972956,0.001575802,0.00039756537,0.0004237425,0.000105965075,0.00020129689],"domain_scores_gemma":[0.99889463,0.00017598289,0.00028107964,0.00044976117,0.00009809138,0.000100445715],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010536505,0.0002698236,0.00063405663,0.00011263894,0.00016853551,0.000021721487,0.00016055217,0.00031718,0.000003838284],"category_scores_gemma":[0.000034237444,0.00020431468,0.00017760698,0.00030203766,0.00018461504,0.000003223794,0.00017752394,0.00011912991,5.119123e-7],"study_design_candidate":"design_other","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":[0.0000179938,0.00004938392,0.00004248719,0.0022022082,0.0009191427,0.0000010604721,0.00008812138,0.19229062,0.0050623305,0.00018319217,0.002246189,0.7968973],"study_design_scores_gemma":[0.00086710375,0.0005755726,0.00090989174,0.0027974867,0.011166656,0.000382384,0.00058009016,0.29658377,0.001772243,0.0019074096,0.67985344,0.0026039341],"about_ca_topic_score_codex":0.0000132047135,"about_ca_topic_score_gemma":0.0000012078516,"teacher_disagreement_score":0.79429334,"about_ca_system_score_codex":0.00007796362,"about_ca_system_score_gemma":0.00018542413,"threshold_uncertainty_score":0.8331711},"labels":[],"label_agreement":null},{"id":"W2004685163","doi":"10.1016/j.mimet.2010.03.016","title":"Perspective: Time scales in scientific research with an emphasis on microbial cellular and molecular research","year":2010,"lang":"en","type":"article","venue":"Journal of Microbiological Methods","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Data science; Living cell; Computer science; Perspective (graphical); Scale (ratio); Biology; Computational biology; Biological system; Physics; Artificial intelligence","score_opus":0.05671077448973546,"score_gpt":0.42719877169321663,"score_spread":0.3704879972034812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004685163","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":[0.99758834,0.000892979,0.0006116287,0.00049246417,0.00009529202,0.00015508657,0.0000044392114,0.0000027295566,0.00015703091],"genre_scores_gemma":[0.9118821,0.00007385019,0.08761509,0.00003573311,0.0002401421,0.000003353894,0.0000063967723,0.000020352716,0.00012300808],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9950113,0.003202758,0.000369637,0.00060836395,0.00028979866,0.0005181244],"domain_scores_gemma":[0.99776316,0.00019053501,0.00016295427,0.00059412787,0.0010722657,0.00021695219],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014090679,0.00017893543,0.00035810462,0.0004904894,0.00037073164,0.0001960221,0.0006607411,0.00036450385,0.000035686655],"category_scores_gemma":[0.0009957615,0.00012247673,0.00012767689,0.00052529055,0.001732848,0.000011266286,0.00030070002,0.0011911691,0.0000057519164],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004853054,0.0002380903,0.0012932013,0.000004087612,0.000059427817,0.000054637178,0.00004543387,0.00004421937,0.9941584,0.0001621539,0.0002753311,0.0031797052],"study_design_scores_gemma":[0.0006836619,0.0022437414,0.0046826666,0.000028283008,0.000019657598,0.00017910247,0.00023944638,0.00004167039,0.98517734,0.001160755,0.005356808,0.00018685801],"about_ca_topic_score_codex":0.00001188908,"about_ca_topic_score_gemma":0.00006898141,"teacher_disagreement_score":0.08700346,"about_ca_system_score_codex":0.00005690563,"about_ca_system_score_gemma":0.00014719901,"threshold_uncertainty_score":0.63847506},"labels":[],"label_agreement":null},{"id":"W2006766679","doi":"10.1145/2330784.2330867","title":"Bézier control parameterization for evolutionary optimization in disease models","year":2012,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Mennonite University","funders":"","keywords":"Mathematical optimization; Piecewise; Evolutionary computation; Computer science; Evolutionary algorithm; Optimal control; Computation; Optimization problem; Mathematics; Applied mathematics; Algorithm","score_opus":0.010532858261792427,"score_gpt":0.2287247327875803,"score_spread":0.21819187452578787,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2006766679","genre_codex":"methods","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":[0.14781348,0.001126411,0.850537,0.000084607025,0.000054157543,0.00025002766,0.000013224526,0.0000080176615,0.00011308895],"genre_scores_gemma":[0.9871085,0.00003092177,0.011696694,0.0001516947,0.00017276117,0.00009379423,0.00045614917,0.000013383317,0.0002760783],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999431,0.00003907472,0.00013282386,0.00015225013,0.000060858674,0.00018397454],"domain_scores_gemma":[0.9996483,0.000007392247,0.000036627473,0.00016448864,0.000052929332,0.000090275054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010996508,0.000077519195,0.00007738705,0.00004135753,0.000032122683,0.000006475053,0.000050253144,0.00006571709,0.000022311377],"category_scores_gemma":[0.000029781282,0.0000757877,0.00006883592,0.00007837078,0.000016749793,0.000009952771,0.000016493044,0.000014487431,0.0000014751846],"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":[0.00008784863,0.000059881382,0.014482692,0.0000058288265,0.000025764868,6.901667e-8,0.000006927231,0.98071724,0.0037472122,0.0003322329,0.00035522124,0.00017910871],"study_design_scores_gemma":[0.0005707648,0.000024024726,0.005975445,0.000002676486,0.000046397876,5.823618e-7,0.000007710285,0.9914032,0.0005755901,0.00026559594,0.0010033934,0.00012457675],"about_ca_topic_score_codex":0.0000021529959,"about_ca_topic_score_gemma":0.0000020040627,"teacher_disagreement_score":0.839295,"about_ca_system_score_codex":0.000016525815,"about_ca_system_score_gemma":0.000027137583,"threshold_uncertainty_score":0.30905327},"labels":[],"label_agreement":null},{"id":"W2007224179","doi":"10.1021/jp111112s","title":"Modeling Stochastic Dynamics in Biochemical Systems with Feedback Using Maximum Caliber","year":2011,"lang":"en","type":"article","venue":"The Journal of Physical Chemistry B","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":33,"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":"National Institute of General Medical Sciences; National Institutes of Health; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Bistability; Dynamical systems theory; Computer science; Stochastic modelling; Statistical physics; Control theory (sociology); Mathematics; Physics; Statistics; Artificial intelligence; Control (management)","score_opus":0.014573465451885922,"score_gpt":0.22145149558086458,"score_spread":0.20687803012897865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007224179","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":[0.9791723,0.00037212714,0.020234006,0.000011896522,0.000021002661,0.000051376028,0.0000028917716,0.0000027245364,0.00013168564],"genre_scores_gemma":[0.99928004,0.000007239028,0.00021423059,0.000009168075,0.000420204,0.0000012015195,0.0000060190764,0.00002650539,0.000035368543],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990157,0.000052362913,0.00030817636,0.00015355015,0.00023077222,0.0002394241],"domain_scores_gemma":[0.99924195,0.000013037389,0.00019436739,0.00029969306,0.00014619673,0.00010478233],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022343459,0.00017899927,0.00027619264,0.000021113667,0.0000390708,0.000012070091,0.00032882905,0.00010017358,0.000004755858],"category_scores_gemma":[0.000019021254,0.000117660005,0.00013142795,0.00015717401,0.00011126314,0.0000058540627,0.000078249825,0.00024926235,8.988318e-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":[0.00024302695,0.00010969503,0.00012763421,0.000027764754,0.00013129704,0.0000068984587,0.00008544571,0.50142646,0.49779582,0.000003887297,0.000015043854,0.00002702457],"study_design_scores_gemma":[0.00053508824,0.00010572452,0.000024824592,0.000101273974,0.00024609445,0.0002744684,0.00055125216,0.8687454,0.12903489,0.00015819361,0.0000036184974,0.00021919736],"about_ca_topic_score_codex":0.000035587367,"about_ca_topic_score_gemma":0.0000050220056,"teacher_disagreement_score":0.36876094,"about_ca_system_score_codex":0.000090047004,"about_ca_system_score_gemma":0.0000905378,"threshold_uncertainty_score":0.47980356},"labels":[],"label_agreement":null},{"id":"W2007233544","doi":"10.1063/1.4913417","title":"Chaotic dynamics and diffusion in a piecewise linear equation","year":2015,"lang":"en","type":"article","venue":"Chaos An Interdisciplinary Journal of Nonlinear Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Universita degli Studi di Bari Aldo Moro; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Piecewise linear function; Nonlinear system; Chaotic; Eigenvalues and eigenvectors; Piecewise; Differential equation; Flow (mathematics); Delay differential equation; Statistical physics; Applied mathematics; Mathematical analysis; Control theory (sociology); Physics; Computer science","score_opus":0.022651011934738563,"score_gpt":0.314373105475303,"score_spread":0.29172209354056444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007233544","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":[0.9918712,0.00035319995,0.0071615283,0.00029197152,0.00019898867,0.000060802395,0.0000024663782,0.0000025967868,0.000057239806],"genre_scores_gemma":[0.9942527,0.00006159303,0.00521658,0.000030403522,0.00034757712,9.375493e-7,0.000010758616,0.000010985694,0.00006846285],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99874943,0.000059324644,0.0003790132,0.00026395696,0.00033379465,0.00021449428],"domain_scores_gemma":[0.998889,0.000007727343,0.00023721556,0.0002487599,0.00033862388,0.0002786153],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012656179,0.00012228354,0.00018761444,0.00028622063,0.00011488338,0.000041733503,0.00038089752,0.000069741574,0.000003409122],"category_scores_gemma":[0.00010231592,0.00010227838,0.00006117404,0.00039885743,0.00031561445,0.00004736848,0.00053172826,0.00013385268,0.0000021445674],"study_design_candidate":"simulation_or_modeling","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":[0.001818679,0.0021736778,0.14948545,0.00009348125,0.0001377703,0.00031112507,0.012465667,0.06669006,0.6768785,0.00035522573,0.00033062982,0.089259684],"study_design_scores_gemma":[0.0011064891,0.0019242404,0.01692284,0.000098127486,0.00003280894,0.00042406592,0.003229212,0.9698026,0.00557671,0.00052718254,0.00009730036,0.0002584055],"about_ca_topic_score_codex":0.0000031421034,"about_ca_topic_score_gemma":0.000082535356,"teacher_disagreement_score":0.90311253,"about_ca_system_score_codex":0.0000868024,"about_ca_system_score_gemma":0.0002582544,"threshold_uncertainty_score":0.41707915},"labels":[],"label_agreement":null},{"id":"W2008217290","doi":"10.1063/1.4711143","title":"An adaptive stepsize method for the chemical Langevin equation","year":2012,"lang":"en","type":"article","venue":"The Journal of Chemical Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Stochastic differential equation; Langevin equation; Applied mathematics; Adaptive stepsize; Noise (video); Multiplicative function; Langevin dynamics; Computer science; Brownian dynamics; Differential equation; Multiplicative noise; Mathematical optimization; Statistical physics; Mathematics; Numerical analysis; Physics; Brownian motion; Mathematical analysis","score_opus":0.030173945706528114,"score_gpt":0.30297891565553486,"score_spread":0.27280496994900677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008217290","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":[0.6120505,0.001533353,0.38579127,0.00032458888,0.00010024755,0.0001316129,0.000005435417,0.0000034997695,0.00005955079],"genre_scores_gemma":[0.9879881,0.000034519464,0.008811887,0.00021319596,0.0028975166,0.0000045270667,0.000012311606,0.000017831217,0.000020107862],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992088,0.000120209304,0.0002165196,0.000075229334,0.00018440711,0.00019481665],"domain_scores_gemma":[0.9990263,0.00019259583,0.00024667467,0.00028058322,0.00016831652,0.00008555245],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008726844,0.000108006236,0.00015811104,0.000006886733,0.000046668305,0.000010043257,0.0003457935,0.000080039026,0.000004756148],"category_scores_gemma":[0.000073885814,0.000059571412,0.00020200972,0.000080301725,0.00006859929,0.000010387719,0.000047752677,0.00013954041,0.0000015912158],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022419039,0.00007136069,0.000040223855,0.000003264695,0.00018524665,3.937083e-8,0.00010703606,0.0008499916,0.9899339,0.00016547812,0.0019497509,0.006469525],"study_design_scores_gemma":[0.0002918221,0.00010628364,0.000046095458,0.0000051188313,0.0003737471,0.000014624199,0.00012272494,0.005616603,0.99014914,0.001265425,0.0019152227,0.0000931789],"about_ca_topic_score_codex":0.0000017599538,"about_ca_topic_score_gemma":2.0427122e-7,"teacher_disagreement_score":0.37697938,"about_ca_system_score_codex":0.000020990808,"about_ca_system_score_gemma":0.000034229757,"threshold_uncertainty_score":0.24292517},"labels":[],"label_agreement":null},{"id":"W2008326182","doi":"10.1007/s11538-005-9048-6","title":"Stochastic kinetics description of a simple transcription model","year":2006,"lang":"en","type":"article","venue":"Bulletin of Mathematical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Transcription (linguistics); RNA polymerase II; RNA polymerase; Transcription bubble; Polymerase; Master equation; Elongation; Abortive initiation; Biology; RNA; DNA; Physics; Genetics; Computational biology; Biological system; Promoter; Gene; Gene expression; Quantum mechanics","score_opus":0.014205640809260381,"score_gpt":0.22971921449904825,"score_spread":0.21551357368978788,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008326182","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":[0.6398,0.0002970715,0.358772,0.000121187935,0.000016826201,0.00012271992,0.000017120146,0.0000074770214,0.0008455654],"genre_scores_gemma":[0.98829865,0.00001137291,0.011085545,0.000030513016,0.00006728351,0.000012806976,0.000115073926,0.000015744987,0.00036302113],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99894875,0.000067876,0.00047554294,0.00022503387,0.0000928517,0.0001899163],"domain_scores_gemma":[0.9993714,0.000026064108,0.00016888809,0.0002862609,0.00011032278,0.000037059526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018768302,0.00013506183,0.00030429836,0.000052636322,0.000018054767,0.000002843521,0.0001435473,0.00020289146,0.00014284387],"category_scores_gemma":[0.00007101426,0.00012176342,0.00016993626,0.000062922496,0.00020733834,5.9598904e-7,0.000042837506,0.000044476834,0.000011723877],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058459464,0.00023444562,0.00009392503,0.000067599736,0.000043869135,1.444327e-7,0.000010154614,0.017396787,0.97300965,0.0065856013,0.0022760727,0.00022329958],"study_design_scores_gemma":[0.0025817659,0.0020080456,0.0012453864,0.0001013805,0.0006304934,0.000042459465,0.000100001416,0.07962311,0.69335765,0.20912114,0.01030076,0.00088779465],"about_ca_topic_score_codex":0.000014102888,"about_ca_topic_score_gemma":0.0000070584697,"teacher_disagreement_score":0.3484986,"about_ca_system_score_codex":0.000007665557,"about_ca_system_score_gemma":0.000016517452,"threshold_uncertainty_score":0.4965368},"labels":[],"label_agreement":null},{"id":"W2008811315","doi":"10.1109/ita.2013.6502959","title":"Inferring causality in networks of WSS processes by pairwise estimation methods","year":2013,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Waterloo","funders":"","keywords":"Pairwise comparison; Causality (physics); Granger causality; Computer science; Context (archaeology); Interdependence; Set (abstract data type); Process (computing); Stochastic process; Econometrics; Variety (cybernetics); Relation (database); Artificial intelligence; Data mining; Machine learning; Mathematics; Statistics","score_opus":0.009099408656961735,"score_gpt":0.29191871050377555,"score_spread":0.2828193018468138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008811315","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":[0.7159679,0.0010620268,0.28223038,0.00003929791,0.000020926784,0.00013628892,8.1714774e-7,0.000009320207,0.0005330456],"genre_scores_gemma":[0.9781905,0.00008677362,0.021301256,0.000052374,0.00002986264,0.000033942953,0.00005998639,0.000010634938,0.00023469956],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99916506,0.00011989093,0.0002660256,0.00021478988,0.00006980899,0.00016441185],"domain_scores_gemma":[0.9994731,0.000022930626,0.00009316354,0.00024770387,0.000115485615,0.000047615984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032871106,0.000103687635,0.00016112588,0.000036729198,0.000018541039,0.000012607946,0.00010697409,0.00011935573,0.00006003649],"category_scores_gemma":[0.00011424843,0.00009418236,0.000044971483,0.00024203691,0.000040087994,0.000006040241,0.00006770921,0.000045783836,0.0000020689902],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021901255,0.00018126862,0.12583312,0.00018613241,0.00016742862,4.2180355e-7,0.000054877197,0.26027903,0.5533306,0.0000652551,0.004777455,0.055102535],"study_design_scores_gemma":[0.0005257505,0.00012608468,0.045670904,0.00003805318,0.00006427236,0.0000028289116,0.000105281906,0.25947812,0.6912824,0.00069879706,0.0015682668,0.0004392653],"about_ca_topic_score_codex":0.000279839,"about_ca_topic_score_gemma":0.00019179114,"teacher_disagreement_score":0.2622226,"about_ca_system_score_codex":0.000010701762,"about_ca_system_score_gemma":0.00003958902,"threshold_uncertainty_score":0.38406453},"labels":[],"label_agreement":null},{"id":"W2008882415","doi":"10.1142/s0218127405012636","title":"ROBUST DEPENDENCIES AND STRUCTURES IN STEM CELL DIFFERENTIATION","year":2005,"lang":"en","type":"article","venue":"International Journal of Bifurcation and Chaos","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"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":"Pairwise comparison; Mutual information; Functional dependency; Computer science; Observable; Entropy (arrow of time); Robustness (evolution); Perturbation (astronomy); Bayesian network; Mathematics; Transfer entropy; Correlation; Dependency (UML); Gene regulatory network; Theoretical computer science; Data mining; Algorithm; Gene; Principle of maximum entropy; Biology; Artificial intelligence; Genetics; Gene expression; Physics","score_opus":0.009421300753979848,"score_gpt":0.22132328002488189,"score_spread":0.21190197927090204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008882415","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":[0.99580604,0.0016144713,0.0018985581,0.00049885886,0.00008961852,0.00002463198,0.0000019712625,0.000001095911,0.00006473197],"genre_scores_gemma":[0.9981935,0.0008164489,0.00042697368,0.00009749449,0.00029964774,8.42004e-7,0.00001096118,0.0000042891975,0.00014985236],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99949276,0.000025622805,0.00019914308,0.00008493762,0.0001461326,0.00005141871],"domain_scores_gemma":[0.9996209,0.000005800178,0.00015912691,0.00004528732,0.00013427256,0.000034624733],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010147132,0.00005732936,0.00006948335,0.00011103885,0.00001698581,0.000029821704,0.00008382737,0.00004797683,0.000012274997],"category_scores_gemma":[0.0000061765013,0.000050848015,0.000030697203,0.000029583574,0.000019532336,0.000011543158,0.000029607547,0.00004738762,4.507467e-7],"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":[0.0003095637,0.00022783603,0.26467615,0.000030756524,0.000397641,0.000009507268,0.0013548465,0.024663318,0.4853405,0.00089426513,0.0013044083,0.22079119],"study_design_scores_gemma":[0.0029463102,0.00022600823,0.7017043,0.000052974206,0.00008756183,0.00029669804,0.001195323,0.010584214,0.26734468,0.0006381095,0.014559147,0.00036462265],"about_ca_topic_score_codex":0.0000028832264,"about_ca_topic_score_gemma":0.000064992906,"teacher_disagreement_score":0.4370282,"about_ca_system_score_codex":0.000017474926,"about_ca_system_score_gemma":0.00002087578,"threshold_uncertainty_score":0.20735219},"labels":[],"label_agreement":null},{"id":"W2009163705","doi":"10.1038/ng1348","title":"Just-in-time transcription program in metabolic pathways","year":2004,"lang":"en","type":"article","venue":"Nature Genetics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":489,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"National Institutes of Health","keywords":"Biology; Synthetic biology; Transcription (linguistics); Gene; Computational biology; Transcription factor; Promoter; Gene expression; Regulation of gene expression; Reporter gene; Metabolic pathway; Systems biology; Genetics; Metabolic engineering","score_opus":0.0073190992040908205,"score_gpt":0.24205933999534782,"score_spread":0.234740240791257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2009163705","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":[0.98111224,0.01797547,0.00012905296,0.00009842035,0.00012367324,0.00032151502,0.0000070162578,0.000021258802,0.00021137098],"genre_scores_gemma":[0.99431753,0.0009461214,0.003949544,0.00022841957,0.0002607336,0.000040769188,0.00013496217,0.000032298205,0.00008963136],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99865824,0.000055944252,0.00026812768,0.000431714,0.0002222902,0.00036368024],"domain_scores_gemma":[0.99945116,0.000002362034,0.000053690717,0.00035907925,0.000054413536,0.0000792916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019111639,0.00020164068,0.00022422941,0.00013926822,0.00002795305,0.000023087241,0.00026995546,0.0006231436,0.000010829021],"category_scores_gemma":[0.000016688165,0.00020697946,0.00013764406,0.00045064153,0.00004508209,0.0000025751624,0.000046122343,0.00031897498,0.000015523987],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000097071716,0.0006889083,0.03434654,0.000032946144,0.000116702264,0.000033817803,0.00019579867,0.04537688,0.8901574,0.00022428189,0.00028265524,0.02844697],"study_design_scores_gemma":[0.0041306377,0.0005180911,0.26632488,0.000054911034,0.00018221559,0.000028709952,0.00007703288,0.0013550624,0.64575934,0.00092430046,0.07966352,0.0009813128],"about_ca_topic_score_codex":0.0000062188656,"about_ca_topic_score_gemma":0.00029645962,"teacher_disagreement_score":0.24439812,"about_ca_system_score_codex":0.00003374224,"about_ca_system_score_gemma":0.00008878592,"threshold_uncertainty_score":0.8440378},"labels":[],"label_agreement":null},{"id":"W2009483875","doi":"10.1007/s00285-007-0099-1","title":"Graph-theoretic methods for the analysis of chemical and biochemical networks. I. Multistability and oscillations in ordinary differential equation models","year":2007,"lang":"en","type":"article","venue":"Journal of Mathematical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":98,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Ordinary differential equation; Ode; Multistability; Mathematics; Jacobian matrix and determinant; Digraph; Graph; Differential equation; Chemical reaction; Bipartite graph; Stability (learning theory); Applied mathematics; Statistical physics; Mathematical analysis; Discrete mathematics; Physics; Nonlinear system; Chemistry; Computer science; Quantum mechanics","score_opus":0.022836320958913376,"score_gpt":0.3318286292229171,"score_spread":0.30899230826400376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2009483875","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":[0.5100253,0.0009937194,0.4888306,0.00005446401,0.000014894432,0.00007352744,0.0000024426338,7.088527e-7,0.000004325175],"genre_scores_gemma":[0.95625275,0.00019497696,0.0434487,0.000013886324,0.00006322602,0.0000039846714,0.000014575605,0.0000064330347,0.0000014652999],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987473,0.00016449271,0.0006663159,0.00018193712,0.00006609459,0.00017389285],"domain_scores_gemma":[0.99835265,0.0009636927,0.00028700006,0.00018188993,0.00014075123,0.000074041964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019381933,0.0001143121,0.00044957027,0.0001623091,0.000029793922,0.000006876534,0.00012156723,0.00020711243,0.0000088512625],"category_scores_gemma":[0.0005041466,0.00007455747,0.000234803,0.00029025634,0.00041339616,0.000004102521,0.000082971,0.00010530598,2.2973465e-8],"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":[0.00080367137,0.00034751842,0.009434499,0.00010067191,0.0023935218,8.9514674e-7,0.00018076597,0.006523299,0.93684787,0.019427722,0.00003092284,0.023908656],"study_design_scores_gemma":[0.0012416121,0.00036116075,0.011199356,0.000026788284,0.0028379983,0.000045924768,0.00014240903,0.82074904,0.045994468,0.11711964,0.00003647763,0.0002451423],"about_ca_topic_score_codex":0.0000018028618,"about_ca_topic_score_gemma":0.0000034440318,"teacher_disagreement_score":0.8908534,"about_ca_system_score_codex":0.000012279706,"about_ca_system_score_gemma":0.000016753414,"threshold_uncertainty_score":0.30403653},"labels":[],"label_agreement":null},{"id":"W2009980816","doi":"10.1038/nrg2556","title":"Non-genetic heterogeneity — a mutation-independent driving force for the somatic evolution of tumours","year":2009,"lang":"en","type":"review","venue":"Nature Reviews Genetics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":512,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Air Force Office of Scientific Research; National Institutes of Health","keywords":"Biology; Somatic cell; Gene; Genetics; Somatic evolution in cancer; Genetic heterogeneity; Mutation; Natural selection; Mutation Accumulation; Selection (genetic algorithm); Germline mutation; Phenotype; Mutation rate","score_opus":0.015469040350537646,"score_gpt":0.31412778902021926,"score_spread":0.2986587486696816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2009980816","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00043486184,0.9804809,0.015034436,0.000014642547,0.0003249099,0.0036409101,0.000038996477,0.000009698679,0.00002066078],"genre_scores_gemma":[0.0045972937,0.9891228,0.0043677734,0.000049638264,0.0008244029,0.00043969744,0.0003127773,0.00010813464,0.00017744511],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99620736,0.00036293082,0.0016064132,0.0008722099,0.00043180562,0.00051927735],"domain_scores_gemma":[0.9960858,0.00011302902,0.0016793201,0.0016882989,0.00029588994,0.00013763382],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009396309,0.00077807927,0.0021149921,0.00016373677,0.00019296512,0.000043515494,0.0010677763,0.0012737145,0.0000056551603],"category_scores_gemma":[0.00022658629,0.0005446361,0.0022992913,0.0005322114,0.0000992965,0.000003383039,0.00018352574,0.0005180928,0.000010039797],"study_design_candidate":"not_applicable","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":[0.00000577818,0.000067836874,0.00010575255,0.009470358,0.0006515475,0.0000016894558,0.000011232431,0.0010931767,0.00029267537,0.000013546976,0.0013422335,0.9869442],"study_design_scores_gemma":[0.0002621402,0.00024524645,0.00040075195,0.004033927,0.00615798,0.00009999733,0.000008765401,0.000776245,0.00048657993,0.000098992234,0.98674726,0.00068212743],"about_ca_topic_score_codex":0.0000017545607,"about_ca_topic_score_gemma":0.000082703205,"teacher_disagreement_score":0.986262,"about_ca_system_score_codex":0.00014897918,"about_ca_system_score_gemma":0.00046714031,"threshold_uncertainty_score":0.9997005},"labels":[],"label_agreement":null},{"id":"W2010321157","doi":"10.1016/j.mbs.2012.05.007","title":"Turing-Hopf instability in biochemical reaction networks arising from pairs of subnetworks","year":2012,"lang":"en","type":"article","venue":"Mathematical Biosciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Turing; Eigenvalues and eigenvectors; Mathematics; Instability; Graph; Reaction–diffusion system; Hopf bifurcation; Physics; Combinatorics; Computer science; Mathematical analysis; Bifurcation; Quantum mechanics; Nonlinear system","score_opus":0.01299894975031186,"score_gpt":0.24312976344435216,"score_spread":0.23013081369404031,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010321157","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":[0.9908892,0.00097442034,0.0073728086,0.00004994341,0.00012963524,0.000103543614,0.0000025791724,0.000011349458,0.00046650216],"genre_scores_gemma":[0.99719584,0.000048176677,0.00243133,0.000030221181,0.00024196274,0.000007989874,0.000021162476,0.00000922849,0.0000140965285],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984993,0.00010110459,0.00042272065,0.0003390166,0.00023689262,0.0004010173],"domain_scores_gemma":[0.99924254,0.00007659128,0.0001390597,0.00037456938,0.000035071404,0.00013218024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008282277,0.00015350946,0.00026281943,0.00005759743,0.00005096107,0.00001761175,0.0002420266,0.00021637486,0.000029643912],"category_scores_gemma":[0.00019595756,0.00012699458,0.00012280172,0.00031937027,0.00034490903,0.000014196328,0.00013965528,0.000117156116,0.000004492443],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006303615,0.00075966667,0.21553849,0.00006538874,0.000065859065,9.234724e-7,0.0003287928,0.0015094745,0.7767776,0.00042420233,0.00027288502,0.0041936687],"study_design_scores_gemma":[0.0007685817,0.0002343374,0.29436943,0.00023329334,0.00019581102,0.000014553074,0.0010904418,0.046867948,0.64801,0.0063501294,0.0008348056,0.0010306862],"about_ca_topic_score_codex":0.00003060788,"about_ca_topic_score_gemma":0.000026693077,"teacher_disagreement_score":0.12876762,"about_ca_system_score_codex":0.000025743122,"about_ca_system_score_gemma":0.000025798585,"threshold_uncertainty_score":0.5178689},"labels":[],"label_agreement":null},{"id":"W2011097028","doi":"10.1088/1478-3975/3/4/005","title":"Validation of an algorithm for delay stochastic simulation of transcription and translation in prokaryotic gene expression","year":2006,"lang":"en","type":"article","venue":"Physical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":116,"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 Calgary; University of Lethbridge","funders":"","keywords":"Transcription (linguistics); Gene; Ribosome; Translation (biology); Gene expression; Stochastic modelling; Computational biology; Biology; Computer science; RNA; Algorithm; Genetics; Messenger RNA; Mathematics; Statistics","score_opus":0.012107327676316072,"score_gpt":0.2692699784733006,"score_spread":0.2571626507969845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011097028","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":[0.66182685,0.00011203733,0.33787104,0.0000046452233,0.000009706081,0.00015587178,0.000015694754,0.0000023441658,0.0000018036493],"genre_scores_gemma":[0.9931457,0.0000034236512,0.005988575,0.000002287349,0.00011821621,0.000019592982,0.00071154314,0.000007732253,0.000002917883],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99938595,0.00007438347,0.00020317374,0.00020320246,0.000041421794,0.00009188391],"domain_scores_gemma":[0.99970114,0.00003102756,0.00009396797,0.00010017712,0.000056634548,0.00001706375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000093584174,0.00007775236,0.00016139924,0.00005248269,0.000015749263,0.0000016748149,0.00003789882,0.00009407719,6.833968e-7],"category_scores_gemma":[0.000008073036,0.00007312397,0.000055898872,0.00007387802,0.000055384004,0.0000064383744,0.00000606797,0.00002182775,6.93022e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005693895,0.00010403184,0.00020959311,0.000012190435,0.000008153476,2.2297655e-8,0.000030554864,0.17351902,0.8123029,0.000021652173,4.949843e-7,0.013734461],"study_design_scores_gemma":[0.00044600456,0.000289663,0.001214488,0.000004947195,0.0000295758,3.373383e-7,0.000005475673,0.36122653,0.6351038,0.0016179741,0.000005238384,0.00005595322],"about_ca_topic_score_codex":0.000013920984,"about_ca_topic_score_gemma":0.000008537289,"teacher_disagreement_score":0.33188245,"about_ca_system_score_codex":0.000004850523,"about_ca_system_score_gemma":0.000010706096,"threshold_uncertainty_score":0.2981909},"labels":[],"label_agreement":null},{"id":"W2012381389","doi":"10.4236/am.2013.41a036","title":"Automatic Simulation of the Chemical Langevin Equation","year":2013,"lang":"en","type":"article","venue":"Applied Mathematics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Langevin equation; Langevin dynamics; Applied mathematics; Stochastic process; Computer science; Statistical physics; Brownian dynamics; Stochastic simulation; Stochastic differential equation; Mathematical optimization; Biological system; Mathematics; Physics; Brownian motion; Statistics","score_opus":0.011977062045785228,"score_gpt":0.2274006713066152,"score_spread":0.21542360926082998,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2012381389","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":[0.98376477,0.00003352868,0.014326471,0.000042509815,0.000018536644,0.00027418422,8.732996e-7,0.000010973708,0.0015281569],"genre_scores_gemma":[0.9911052,0.0000020916445,0.008630759,0.00004290082,0.00005472742,0.000032956003,0.000015550362,0.000013498825,0.000102315316],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99942863,0.000010480499,0.00021679273,0.00010739064,0.00014058044,0.00009614227],"domain_scores_gemma":[0.9993653,0.000026965557,0.00014942372,0.0003862353,0.00004922794,0.000022798444],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009636594,0.00008128802,0.00011371475,0.000014565086,0.000025655794,0.000008890246,0.00015081823,0.00008015172,0.00007081671],"category_scores_gemma":[0.00004477631,0.000058178368,0.000070812945,0.00010153171,0.00004201113,0.0000015492876,0.00007492297,0.000031743544,0.000036914935],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012421272,0.00006769699,0.0001279495,0.00008520564,0.000061862425,1.8537618e-8,0.00011388203,0.014535813,0.97838825,0.0013032145,0.0008646475,0.004450224],"study_design_scores_gemma":[0.00026152047,0.000016127015,0.0009818559,0.000022563345,0.00010541267,0.0000013771622,0.00012962044,0.42655548,0.5637676,0.007652346,0.0003308994,0.00017516436],"about_ca_topic_score_codex":0.0000017893942,"about_ca_topic_score_gemma":9.581828e-7,"teacher_disagreement_score":0.41462064,"about_ca_system_score_codex":0.0000084531475,"about_ca_system_score_gemma":0.000016023854,"threshold_uncertainty_score":0.2372445},"labels":[],"label_agreement":null},{"id":"W2012655105","doi":"10.1007/s13752-013-0136-9","title":"Synthetic Biology and Synthetic Knowledge","year":2013,"lang":"en","type":"article","venue":"Biological Theory","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Zentrum für interdisziplinäre Forschung, Universität Bielefeld; Universität Bielefeld","keywords":"Synthetic biology; Philosophy of biology; Epistemology; Computer science; Computational biology; Cognitive science; Biology; Psychology; Philosophy of science; Philosophy","score_opus":0.013192632870397228,"score_gpt":0.2505087961689851,"score_spread":0.23731616329858785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2012655105","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":[0.98526615,0.008266339,0.0013824871,0.000099398756,0.000094376344,0.00018809758,0.0000046100463,0.000033860157,0.0046646865],"genre_scores_gemma":[0.99776226,0.0005298001,0.0003255106,0.00018753861,0.0002110856,0.00006173509,0.000028710097,0.000015489279,0.0008778623],"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9984636,0.00045229724,0.00019544677,0.0005264219,0.000033882694,0.00032838833],"domain_scores_gemma":[0.9992461,0.00009948277,0.000056071134,0.00040684355,0.000054905973,0.00013659963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041259627,0.00019915604,0.00023156358,0.00004287221,0.0000937227,0.000019644052,0.00021725995,0.0003031233,0.00041289482],"category_scores_gemma":[0.00021772113,0.00013685603,0.00012351637,0.00008629166,0.00048735607,0.0000020339512,0.00024797482,0.00008059562,0.00023967121],"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":[0.00006393125,0.00015463629,0.012397357,0.0000138735195,0.00022242984,0.0000016518585,0.000032540018,0.000010819921,0.8682347,0.03332769,0.0011910157,0.08434935],"study_design_scores_gemma":[0.0021080477,0.003491244,0.11802223,0.00008914852,0.00035561272,0.00029467046,0.00071539823,0.00090593094,0.19694018,0.3395909,0.33425635,0.0032302772],"about_ca_topic_score_codex":0.000003377062,"about_ca_topic_score_gemma":0.0000013445965,"teacher_disagreement_score":0.6712945,"about_ca_system_score_codex":0.000007871157,"about_ca_system_score_gemma":0.00001661162,"threshold_uncertainty_score":0.5580827},"labels":[],"label_agreement":null},{"id":"W2013275477","doi":"10.1186/1754-1611-4-17","title":"Introduction of customized inserts for streamlined assembly and optimization of BioBrick synthetic genetic circuits","year":2010,"lang":"en","type":"article","venue":"Journal of Biological Engineering","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":29,"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 Alberta","funders":"King Abdullah University of Science and Technology; W. M. Keck Foundation; National Science Foundation","keywords":"Synthetic biology; Green fluorescent protein; Cloning (programming); Computer science; Electronic circuit; Computational biology; Process (computing); Biology; Engineering; Genetics; Gene; Electrical engineering","score_opus":0.0062884421525451414,"score_gpt":0.20641843395052709,"score_spread":0.20012999179798194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013275477","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":[0.8834217,0.0004486045,0.11588097,0.000043030348,0.00013002088,0.00006839776,0.0000028413144,0.000002474267,0.0000019335594],"genre_scores_gemma":[0.97314584,0.0002379061,0.026194455,0.0000036859947,0.0003935076,0.0000020608388,0.000008839611,0.0000086881855,0.0000050134113],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99929947,0.000021866028,0.00039211856,0.00012123757,0.00006674655,0.000098588396],"domain_scores_gemma":[0.99930245,0.00003157198,0.00029705832,0.0001158715,0.00020054124,0.000052512765],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027181016,0.00009232714,0.0002638336,0.00008741549,0.000013174218,0.0000045789347,0.0000864845,0.00014924043,0.000007083683],"category_scores_gemma":[0.00041689526,0.00007150384,0.00012596429,0.000092111746,0.000039059796,0.000003695646,0.00002401552,0.000071308525,4.75268e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051585088,0.000026164622,0.00044303446,0.000019290961,0.00006794001,2.7503256e-7,0.000004358384,0.2390362,0.75813,0.000010127496,0.000023100318,0.0021878842],"study_design_scores_gemma":[0.0014686955,0.0010568136,0.0076107043,0.00002817292,0.00018603868,0.00011851188,0.000018598488,0.10576295,0.88222414,0.00003219194,0.0012819609,0.00021120433],"about_ca_topic_score_codex":6.877948e-7,"about_ca_topic_score_gemma":5.352517e-7,"teacher_disagreement_score":0.13327326,"about_ca_system_score_codex":0.000004940036,"about_ca_system_score_gemma":0.000021003423,"threshold_uncertainty_score":0.2915842},"labels":[],"label_agreement":null},{"id":"W2014036889","doi":"10.1007/s11538-009-9469-8","title":"Dynamics of Notch Activity in a Model of Interacting Signaling Pathways","year":2010,"lang":"en","type":"article","venue":"Bulletin of Mathematical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Notch signaling pathway; Hes3 signaling axis; Hopf bifurcation; Signal transduction; Dynamics (music); Bifurcation; Retinoic acid; Biology; Physics; Biological system; Cell biology; Genetics; Gene","score_opus":0.013686150707336458,"score_gpt":0.2476790226944498,"score_spread":0.23399287198711335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2014036889","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":[0.98434824,0.000024926921,0.014680169,0.00015986184,0.000025794707,0.00008629277,0.000017075492,0.000002942455,0.00065467117],"genre_scores_gemma":[0.98300904,0.000008127834,0.016884346,0.000010613408,0.000023404611,0.000006051592,0.000015673735,0.000011933297,0.000030813786],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99899614,0.00008280288,0.00046471148,0.0002141757,0.0000723909,0.00016978041],"domain_scores_gemma":[0.9990787,0.00015208423,0.00031367422,0.0003228278,0.000096624215,0.00003612111],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053744315,0.00011835315,0.0004118045,0.000066490815,0.000010672517,0.0000014054292,0.00020595329,0.00024455314,0.000105903084],"category_scores_gemma":[0.0004687293,0.00010622347,0.0001506503,0.00006824783,0.0001938221,7.424431e-7,0.0001521704,0.00014976016,0.0000024257547],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006405381,0.00019631206,0.0011667501,0.00011094645,0.000046075733,2.65326e-7,0.000039007467,0.0015867101,0.9917337,0.0041738036,0.000018939969,0.000863484],"study_design_scores_gemma":[0.00031819806,0.00016273124,0.00011607702,0.000052283896,0.000034560184,0.0000046173323,0.00006688177,0.0746472,0.9168432,0.0075718034,0.00004838884,0.00013408839],"about_ca_topic_score_codex":0.000016590408,"about_ca_topic_score_gemma":0.00003554372,"teacher_disagreement_score":0.07489049,"about_ca_system_score_codex":0.0000062207564,"about_ca_system_score_gemma":0.00003853322,"threshold_uncertainty_score":0.43316674},"labels":[],"label_agreement":null},{"id":"W2014681825","doi":"10.1007/s10867-007-9043-2","title":"Simplification of Stochastic Chemical Reaction Models with Fast and Slow Dynamics","year":2007,"lang":"en","type":"article","venue":"Journal of Biological Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"College of Family Physicians of Canada; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Stochastic modelling; Representation (politics); Cascade; Computer science; Stochastic process; Complex system; Reduction (mathematics); Process (computing); Biological system; Systems biology; Statistical physics; Work (physics); Mathematics; Chemistry; Artificial intelligence; Computational biology; Biology; Physics","score_opus":0.013837678466925536,"score_gpt":0.2340005545516531,"score_spread":0.22016287608472757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2014681825","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":[0.66751176,0.00012635776,0.3322565,0.000017621018,0.0000142090075,0.000028335875,0.0000021448625,0.0000013881903,0.00004165442],"genre_scores_gemma":[0.99755627,0.000058142326,0.002097584,0.000020014635,0.00022905222,4.1883237e-7,0.000024410343,0.0000066685534,0.0000074331733],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993471,0.000022630567,0.00027212166,0.00012630457,0.00011633607,0.00011554248],"domain_scores_gemma":[0.99923927,0.000022948017,0.00035315313,0.00011791016,0.00019732109,0.000069383066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023911952,0.000093361945,0.00019187205,0.000023659148,0.000021103873,0.0000046743176,0.00008455371,0.00011847211,4.9797586e-7],"category_scores_gemma":[0.000022630546,0.00006349585,0.00008303282,0.0001005016,0.000119778495,0.0000061055903,0.0000287631,0.00009826824,1.6390256e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003702644,0.000112050686,0.0009146003,0.0000069093207,0.000114452494,0.0000013853705,0.000015450554,0.009588638,0.9707007,0.0006228946,0.00002689914,0.017525788],"study_design_scores_gemma":[0.0037250037,0.006217261,0.035058025,0.00015607447,0.00076464005,0.0005841747,0.0009892436,0.09935261,0.81974983,0.032013364,0.0002196916,0.0011700806],"about_ca_topic_score_codex":0.0000010994023,"about_ca_topic_score_gemma":0.0000016031478,"teacher_disagreement_score":0.33015892,"about_ca_system_score_codex":0.000021252095,"about_ca_system_score_gemma":0.000022887853,"threshold_uncertainty_score":0.25892857},"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,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.03275598549327609,"score_gpt":0.2741752154003971,"score_spread":0.241419229907121,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015271344","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":[0.96361524,0.018325398,0.01704893,0.000005585104,0.00054595777,0.00018450247,0.00003921326,0.000010285542,0.00022488061],"genre_scores_gemma":[0.9949336,0.00011919251,0.0028985639,0.000011308772,0.001362467,0.000023879544,0.0005902442,0.000011500835,0.000049257098],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977116,0.0010882535,0.00046470098,0.00037741536,0.00006558309,0.0002924333],"domain_scores_gemma":[0.99859667,0.00010767882,0.0002693674,0.0009277545,0.000049514852,0.000049013506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001044071,0.00017538869,0.00031886811,0.00005015602,0.00006131005,0.000011859584,0.0005837065,0.0003748856,0.000017649221],"category_scores_gemma":[0.00009724979,0.000111484645,0.00007867611,0.00013194105,0.00025870898,0.00001143899,0.00033547202,0.000116821844,0.0000073340807],"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":[0.00008971916,0.00006759165,0.50239563,0.00001440953,0.000052764313,3.259213e-7,0.0000856901,0.00028925284,0.49457318,0.0006432552,0.00076788926,0.0010203104],"study_design_scores_gemma":[0.0041157077,0.0015543501,0.66084373,0.0011046752,0.00047557248,0.0006636364,0.012909306,0.044339653,0.1735106,0.00075083016,0.09691454,0.002817394],"about_ca_topic_score_codex":0.000076041004,"about_ca_topic_score_gemma":0.00007080084,"teacher_disagreement_score":0.32106256,"about_ca_system_score_codex":0.000013922687,"about_ca_system_score_gemma":0.000044187484,"threshold_uncertainty_score":0.4546212},"labels":[],"label_agreement":null},{"id":"W2015789031","doi":"10.1049/ip-syb:20050006","title":"Inferring gene regulatory networks with time delays using a genetic algorithm","year":2005,"lang":"en","type":"article","venue":"Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; Wilfrid Laurier University","funders":"University of Saskatchewan","keywords":"Gene regulatory network; Computer science; Bayesian network; Boolean network; Probabilistic logic; Gene; Dynamic Bayesian network; Algorithm; Gene expression; Biology; Machine learning; Genetics; Artificial intelligence; Boolean function","score_opus":0.006733777485137406,"score_gpt":0.21682829275949425,"score_spread":0.21009451527435685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015789031","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":[0.7667746,0.009266339,0.22325845,0.00001585527,0.00018155485,0.00026768408,0.00001031418,0.00004289854,0.00018227632],"genre_scores_gemma":[0.9732128,0.00008878298,0.023669943,0.00009803619,0.0021829836,0.000033110795,0.00014187899,0.00006776643,0.00050470605],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979581,0.00024028424,0.00043603257,0.000657683,0.000118764234,0.000589113],"domain_scores_gemma":[0.998729,0.000011873466,0.00022687191,0.0007362611,0.00013296823,0.00016305748],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00028706968,0.00032669332,0.000415192,0.00011053682,0.00014896005,0.00002981632,0.00027214197,0.000425101,0.000021962347],"category_scores_gemma":[0.000008035028,0.00028469146,0.00013316468,0.00021414063,0.00016041132,0.0000050165427,0.00014615836,0.000121292134,0.000034498178],"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":[0.000041823485,0.000041429703,0.007173074,0.000011459872,0.00049369544,0.000011484943,0.00001943583,0.65260196,0.32142884,0.000022927785,0.0003843618,0.017769543],"study_design_scores_gemma":[0.0012738244,0.00057386723,0.004971267,0.00006603535,0.0003092574,0.0010390814,0.000042177264,0.9338448,0.025585419,0.000011659862,0.031139588,0.0011429952],"about_ca_topic_score_codex":0.00006305036,"about_ca_topic_score_gemma":0.000022152864,"teacher_disagreement_score":0.29584342,"about_ca_system_score_codex":0.000070877024,"about_ca_system_score_gemma":0.00009930888,"threshold_uncertainty_score":0.99996054},"labels":[],"label_agreement":null},{"id":"W2017162913","doi":"10.1103/physreve.77.011901","title":"Mutual information in random Boolean models of regulatory networks","year":2008,"lang":"en","type":"article","venue":"Physical Review E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":108,"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 Calgary","funders":"National Science Foundation","keywords":"Boolean network; Pairwise comparison; Mutual information; Measure (data warehouse); Boolean model; Boolean function; Mathematics; Discontinuity (linguistics); Complex network; Function (biology); Series (stratigraphy); Statistical physics; Computer science; Theoretical computer science; Topology (electrical circuits); Discrete mathematics; Combinatorics; Data mining; Statistics; Physics; Mathematical analysis","score_opus":0.010995637523807899,"score_gpt":0.2442452278315796,"score_spread":0.2332495903077717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017162913","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":[0.9627499,0.030216727,0.0053789904,0.0000508032,0.00003125958,0.00028889984,0.0000028738432,0.000008110237,0.0012724454],"genre_scores_gemma":[0.9813637,0.018027151,0.00007766825,0.00027162593,0.00013097792,0.000019607327,0.00006735762,0.000008369283,0.0000335296],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99912447,0.00008475665,0.00033432973,0.00014313473,0.0001568801,0.00015640365],"domain_scores_gemma":[0.9993823,0.000012486117,0.00013961829,0.000344591,0.00006601852,0.00005495703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001829494,0.00011806307,0.0003535625,0.000029695566,0.00002404728,0.0000022251145,0.0001341848,0.00004748519,0.0000057941993],"category_scores_gemma":[0.000037788555,0.00010513301,0.000218338,0.00019125866,0.00007255429,0.000013495124,0.000059607166,0.00007164686,0.000008137937],"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":[0.00071242405,0.00094517943,0.0054062903,0.0025011979,0.00066992873,0.000011808162,0.000560574,0.8103314,0.041727077,0.0049403645,0.042317905,0.08987584],"study_design_scores_gemma":[0.008575999,0.00077756867,0.019254869,0.0029104596,0.00075380085,0.00007039184,0.00005764612,0.8328598,0.040135115,0.0032956551,0.089171536,0.0021371383],"about_ca_topic_score_codex":0.000005654772,"about_ca_topic_score_gemma":0.000002872102,"teacher_disagreement_score":0.0877387,"about_ca_system_score_codex":0.000010688477,"about_ca_system_score_gemma":0.000048478338,"threshold_uncertainty_score":0.42872},"labels":[],"label_agreement":null},{"id":"W2017886758","doi":"10.1126/science.1202142","title":"Real-Time Observation of Transcription Initiation and Elongation on an Endogenous Yeast Gene","year":2011,"lang":"en","type":"article","venue":"Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":723,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"National Institute of General Medical Sciences; U.S. Public Health Service; Howard Hughes Medical Institute","keywords":"Yeast; Elongation; Gene; Transcription (linguistics); Gene expression; Biology; Endogeny; Transcription factor; TAF4; Genetics; Saccharomyces cerevisiae; Elongation factor; Cell biology; Promoter; RNA; Biochemistry","score_opus":0.03997113628275893,"score_gpt":0.23522419770318995,"score_spread":0.19525306142043103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017886758","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":[0.9986825,0.00002934663,0.000536215,0.000004943862,0.00002988913,0.00006503073,0.0000033470185,0.0000056846548,0.0006430686],"genre_scores_gemma":[0.9977667,0.00007036895,0.0020315903,0.000016757669,0.000036092515,0.0000031441323,0.000044200555,0.000004345043,0.00002685395],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999417,0.000033193,0.000106225976,0.00021428132,0.00013710542,0.000092216585],"domain_scores_gemma":[0.99959624,0.0000013760109,0.000069697206,0.00018578021,0.0001040305,0.00004289836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031882018,0.00005225858,0.000053550943,0.00005885813,0.00007482432,0.000008252165,0.00009170534,0.00003848375,0.000010679146],"category_scores_gemma":[0.000017517532,0.000052059488,0.000018198694,0.0001919554,0.00012855692,0.000016837426,0.000011638316,0.00001506995,0.0000029910996],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001720144,0.000025191082,0.0022510753,0.0000023837551,0.0000033440383,1.502729e-7,0.00022767198,0.000111286376,0.99521893,0.00007351356,0.0000016843543,0.0020675834],"study_design_scores_gemma":[0.00008210821,0.00018955933,0.17682761,0.000002808928,0.000010901519,0.0000027542778,0.000025238462,0.0010331078,0.8216595,0.000102727005,0.000013353006,0.00005030175],"about_ca_topic_score_codex":0.000022563727,"about_ca_topic_score_gemma":0.000011713266,"teacher_disagreement_score":0.17457654,"about_ca_system_score_codex":0.000010613949,"about_ca_system_score_gemma":0.000048478116,"threshold_uncertainty_score":0.21229243},"labels":[],"label_agreement":null},{"id":"W2017947558","doi":"10.1196/annals.1407.011","title":"Alternative Pathway Approach for Automating Analysis and Validation of Cell Perturbation Networks and Design of Perturbation Experiments","year":2007,"lang":"en","type":"article","venue":"Annals of the New York Academy of Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Ontario Genomics Institute; Genome Canada","keywords":"Computer science; Perturbation (astronomy); Bayesian network; Data mining; Network topology; Network analysis; Algorithm; Theoretical computer science; Artificial intelligence; Engineering; Physics","score_opus":0.060309692113851135,"score_gpt":0.3133165550163433,"score_spread":0.2530068629024922,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017947558","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":[0.7910916,0.0020626618,0.20655048,0.000058593432,0.000010011761,0.00017427617,0.0000028914212,0.0000013151407,0.00004816373],"genre_scores_gemma":[0.9848955,0.00015211337,0.014793053,0.000031935542,0.000042164902,0.0000027690269,0.000005598649,0.0000037217312,0.000073118725],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990096,0.0000820796,0.00035656555,0.00021614024,0.00021693364,0.00011864811],"domain_scores_gemma":[0.9990457,0.00008406978,0.00068026833,0.000073825926,0.00008149398,0.00003461992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013429726,0.000085848194,0.00020745656,0.00011914353,0.00007466177,0.0000068079667,0.0002012404,0.000096841744,8.233947e-7],"category_scores_gemma":[0.000067003166,0.00006329656,0.00010784588,0.00046327326,0.00026925633,0.000013653254,0.000059058497,0.000030088453,5.515887e-9],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058798843,0.000042704774,0.0061172056,0.000039193972,0.0002403979,3.409564e-9,0.00056301523,0.24354333,0.7458202,0.00018744518,0.000075839765,0.0033118238],"study_design_scores_gemma":[0.000118351076,0.0001175481,0.0040329406,0.000013670052,0.000102094906,1.9546377e-7,0.00022420702,0.14041717,0.8543453,0.00056983967,0.0000062809163,0.0000523948],"about_ca_topic_score_codex":0.000018950726,"about_ca_topic_score_gemma":4.32096e-7,"teacher_disagreement_score":0.19380392,"about_ca_system_score_codex":0.0000025055688,"about_ca_system_score_gemma":0.00002344378,"threshold_uncertainty_score":0.2581159},"labels":[],"label_agreement":null},{"id":"W2018111665","doi":"10.1063/1.4771660","title":"Variable time-stepping in the pathwise numerical solution of the chemical Langevin equation","year":2012,"lang":"en","type":"article","venue":"The Journal of Chemical Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Langevin equation; Stochastic differential equation; Randomness; Variable (mathematics); Applied mathematics; Mathematics; Statistical physics; Differential equation; Computer science; Mathematical optimization; Mathematical analysis; Physics","score_opus":0.012879844135480116,"score_gpt":0.2231653260013429,"score_spread":0.21028548186586277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018111665","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":[0.9929945,0.000629629,0.0057153446,0.0003280101,0.00005412467,0.000070646034,0.000001634861,0.0000013181668,0.00020477998],"genre_scores_gemma":[0.9986355,0.000014505163,0.00038474932,0.0001479094,0.00078620116,0.0000014236599,0.0000065096197,0.000008956736,0.000014287189],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99898875,0.00020556466,0.0002932786,0.00006078771,0.00027084458,0.0001807907],"domain_scores_gemma":[0.99922746,0.00007453207,0.00030285842,0.0002779391,0.000082003324,0.0000352118],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008269155,0.000091262205,0.00015953525,0.000009062879,0.000031977932,0.0000056744834,0.00039821796,0.00008064621,0.0000063957336],"category_scores_gemma":[0.00010983275,0.00004656589,0.00015302301,0.00022393557,0.00008556827,0.000009315162,0.00009563184,0.0002058948,0.0000025936504],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004250776,0.00010507639,0.0005933822,0.0000063078837,0.00004437635,6.899484e-8,0.00015717272,0.0007661081,0.99656117,0.00009030769,0.0011114161,0.0005221313],"study_design_scores_gemma":[0.0003025063,0.000032751406,0.0005132873,0.00003289673,0.00018240896,0.000026108792,0.000058880723,0.0028673443,0.9938439,0.0013044653,0.00074066524,0.00009476251],"about_ca_topic_score_codex":0.0000047477906,"about_ca_topic_score_gemma":1.0556367e-7,"teacher_disagreement_score":0.005640945,"about_ca_system_score_codex":0.00002814969,"about_ca_system_score_gemma":0.00004422505,"threshold_uncertainty_score":0.18989018},"labels":[],"label_agreement":null},{"id":"W2018151888","doi":"10.1063/1.1336498","title":"Symbolic dynamics and computation in model gene networks","year":2001,"lang":"en","type":"article","venue":"Chaos An Interdisciplinary Journal of Nonlinear Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":88,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Differential equation; Ordinary differential equation; Mathematical analysis","score_opus":0.012652865695958334,"score_gpt":0.3100851310552891,"score_spread":0.29743226535933076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018151888","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":[0.87702763,0.00037986893,0.12225849,0.00013640014,0.000095134375,0.000041695122,0.0000016329767,0.0000021978549,0.00005696333],"genre_scores_gemma":[0.9903833,0.00024656657,0.0089906985,0.000042531614,0.00026793045,7.4997007e-7,0.000011796188,0.000011127437,0.000045294593],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998914,0.000036445923,0.00035768596,0.00025659334,0.00020280333,0.00023244205],"domain_scores_gemma":[0.9992416,0.0000059851814,0.00020191626,0.00018021971,0.00020629838,0.00016399476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006822006,0.00011766237,0.00018115249,0.00022954027,0.00015925468,0.00005074949,0.00034083673,0.00006898201,0.0000022190022],"category_scores_gemma":[0.000014218136,0.00010508201,0.000066553876,0.00039504358,0.00029044584,0.00003652017,0.00036630672,0.00013516084,4.796146e-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":[0.00009659871,0.00011460936,0.00867086,0.000003685428,0.000016912936,0.0000386029,0.00026983576,0.95024437,0.029423632,0.000018414561,0.000021947835,0.0110805165],"study_design_scores_gemma":[0.0002660102,0.0003023762,0.007888531,0.000023648594,0.000013397401,0.0005317692,0.00026215325,0.9894454,0.0009385869,0.00020743754,0.00000602292,0.000114682014],"about_ca_topic_score_codex":0.0000013087908,"about_ca_topic_score_gemma":0.00006409274,"teacher_disagreement_score":0.11335569,"about_ca_system_score_codex":0.0000544926,"about_ca_system_score_gemma":0.00012473117,"threshold_uncertainty_score":0.42851198},"labels":[],"label_agreement":null},{"id":"W2018320249","doi":"10.1007/s10867-006-9005-0","title":"Systematic Reduction of a Stochastic Signalling Cascade Model","year":2006,"lang":"en","type":"article","venue":"Journal of Biological Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"College of Family Physicians of Canada; University of Toronto","funders":"","keywords":"Cascade; Reduction (mathematics); Stochastic modelling; Representation (politics); Computer science; Complex system; Systems biology; Work (physics); Biological system; Stochastic process; Mathematics; Artificial intelligence; Chemistry; Computational biology; Biology; Statistics; Engineering","score_opus":0.017479157316649858,"score_gpt":0.23818584364809212,"score_spread":0.22070668633144225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018320249","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":[0.7367416,0.0012406631,0.26187578,0.000009865244,0.000037341357,0.00006245833,0.0000019262832,0.0000020795887,0.00002826732],"genre_scores_gemma":[0.9977539,0.000038277245,0.0015563809,0.000010174481,0.00058893795,0.000001792892,0.00000810068,0.000007905521,0.00003449675],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989622,0.00008634441,0.0005470811,0.000120912955,0.00015563522,0.0001278148],"domain_scores_gemma":[0.9989558,0.00001770036,0.00064392516,0.00013091194,0.0002099602,0.00004172275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028365167,0.000110856425,0.00036406377,0.00003078432,0.000030407156,0.00000675144,0.00014687526,0.00011864702,0.000001639291],"category_scores_gemma":[0.000042922587,0.0000766705,0.00030936644,0.00011201184,0.000070792754,0.0000037695656,0.000031973326,0.000090485664,8.437883e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030559597,0.00006647935,0.000023300887,0.00010384673,0.00008912292,7.918502e-7,0.0000050765966,0.4071417,0.5922423,0.00014514697,0.00010711884,0.00004457028],"study_design_scores_gemma":[0.0013557149,0.0019403334,0.0003776177,0.0013752251,0.001023127,0.00033584185,0.00022320365,0.17317362,0.7772701,0.04221729,0.000017548462,0.0006903696],"about_ca_topic_score_codex":0.00000191147,"about_ca_topic_score_gemma":3.047018e-7,"teacher_disagreement_score":0.26101232,"about_ca_system_score_codex":0.000017339653,"about_ca_system_score_gemma":0.000041800893,"threshold_uncertainty_score":0.3126532},"labels":[],"label_agreement":null},{"id":"W2018475238","doi":"10.1016/j.biosystems.2005.05.008","title":"Phenomenological and molecular-level Petri net modeling and simulation of long-term potentiation","year":2005,"lang":"en","type":"article","venue":"Biosystems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Petri net; Computer science; Abstraction; Scope (computer science); Term (time); Systems biology; Biological system; Modeling and simulation; Theoretical computer science; Distributed computing; Computational biology; Simulation; Programming language; Biology; Physics","score_opus":0.020383846021399105,"score_gpt":0.24989119600567242,"score_spread":0.2295073499842733,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018475238","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":[0.96149254,0.0044442187,0.03383117,0.000040747713,0.0000261495,0.000112887596,0.00000599926,0.0000069199623,0.00003939359],"genre_scores_gemma":[0.9992377,0.000102219805,0.00037984262,0.000023304116,0.00014194995,0.0000033763868,0.000059471316,0.000010346405,0.000041758918],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926484,0.00004666845,0.0002224784,0.00024741705,0.000098537574,0.00012005249],"domain_scores_gemma":[0.9996129,0.000004853114,0.000095995696,0.00017040553,0.00006495364,0.000050883384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013740525,0.00010285015,0.00014603257,0.00005019239,0.000037596463,0.000016795957,0.000053229727,0.00012738149,0.0000031632617],"category_scores_gemma":[0.000014958844,0.00009644856,0.000042946627,0.00006637497,0.00002789245,0.0000045819643,0.00005965727,0.000027543398,7.973628e-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":[0.000038676288,0.000042358814,0.023959564,0.00007040781,0.00014311286,0.0000016497675,0.000055063625,0.48858953,0.4757401,0.000035904784,0.000010276824,0.01131336],"study_design_scores_gemma":[0.00053221406,0.00011668028,0.011449129,0.000021838217,0.00008169017,0.000015218755,0.000040705465,0.96655,0.02085533,0.000014887856,0.0001203312,0.0002019823],"about_ca_topic_score_codex":0.000005451608,"about_ca_topic_score_gemma":0.000013143763,"teacher_disagreement_score":0.47796047,"about_ca_system_score_codex":0.000009686364,"about_ca_system_score_gemma":0.000009612644,"threshold_uncertainty_score":0.3933058},"labels":[],"label_agreement":null},{"id":"W2018711905","doi":"10.1016/j.gde.2010.09.005","title":"Logical and symbolic analysis of robust biological dynamics","year":2010,"lang":"en","type":"review","venue":"Current Opinion in Genetics & Development","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Office of Naval Research; Natural Sciences and Engineering Research Council of Canada","keywords":"Biological network; Attractor; Computer science; State space; Asynchronous communication; Theoretical computer science; Boolean network; Statistical physics; Sequence (biology); State (computer science); Biological system; Topology (electrical circuits); Boolean function; Biology; Mathematics; Algorithm; Physics; Computational biology","score_opus":0.07642513460397526,"score_gpt":0.3479695721648884,"score_spread":0.2715444375609131,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018711905","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0060334257,0.991389,0.00125796,0.0000038970634,0.0008344336,0.00039959635,0.000051857813,0.000007795501,0.00002207174],"genre_scores_gemma":[0.00081351935,0.9924268,0.0027392819,0.0000032400128,0.00020362483,0.00009236385,0.0036723914,0.00003417256,0.0000146200055],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9969431,0.00021554975,0.0012398448,0.0009283875,0.0002645974,0.00040848684],"domain_scores_gemma":[0.998556,0.000040408097,0.00051146967,0.00061081676,0.00010917101,0.00017213752],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00044815932,0.000554381,0.0017425157,0.0006571107,0.0000580848,0.000025349209,0.00047212004,0.00081742124,0.00002265782],"category_scores_gemma":[0.000047318503,0.00046448954,0.00052225153,0.0010623788,0.00019999864,0.0000013899758,0.00057403377,0.00040593455,0.000004032227],"study_design_candidate":"not_applicable","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":[0.000005500879,0.00016686924,0.0060723997,0.0016255161,0.0012354376,4.3384594e-7,0.000023670871,0.0004655892,0.000013051493,0.00008591966,0.00009637227,0.9902092],"study_design_scores_gemma":[0.00015922128,0.00005587736,0.005156362,0.00088428386,0.0011491198,0.000006671228,0.000009465622,0.00070499786,0.000016629961,0.000011347463,0.99122584,0.0006201675],"about_ca_topic_score_codex":0.0000011699424,"about_ca_topic_score_gemma":0.000033366992,"teacher_disagreement_score":0.99112946,"about_ca_system_score_codex":0.000079371624,"about_ca_system_score_gemma":0.00037611308,"threshold_uncertainty_score":0.99978065},"labels":[],"label_agreement":null},{"id":"W2020313378","doi":"10.1109/bibm.2011.105","title":"Employing Machine Learning Techniques for Data Enrichment: Increasing the Number of Samples for Effective Gene Expression Data Analysis","year":2011,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"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 Calgary","funders":"","keywords":"Computer science; Process (computing); Data mining; Independence (probability theory); Set (abstract data type); Machine learning; Probabilistic logic; Sample (material); Expression (computer science); Domain (mathematical analysis); Genetic algorithm; Artificial intelligence; Statistics; Mathematics","score_opus":0.04933694332252949,"score_gpt":0.31669050554515177,"score_spread":0.2673535622226223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020313378","genre_codex":"methods","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":[0.30845594,0.0007697195,0.68963695,0.000015290287,0.000019126144,0.00063872576,0.0003208078,0.000025858755,0.00011761359],"genre_scores_gemma":[0.7878995,0.00010410419,0.20631589,0.00002548665,0.000104354025,0.00007775878,0.005376735,0.000023963834,0.00007220109],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99854106,0.00020093193,0.00029141747,0.0006376976,0.00011397897,0.00021490257],"domain_scores_gemma":[0.9975577,0.00016873726,0.0002358466,0.0018736402,0.00012160553,0.000042447704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014221203,0.00016790956,0.00029066618,0.00006495407,0.00019932976,0.000018097224,0.0009857718,0.00010398724,0.000030263067],"category_scores_gemma":[0.00032530894,0.00011643484,0.00016521628,0.00023356146,0.00006239642,0.0000130054195,0.0010963978,0.000055504872,3.5170774e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003018322,0.00008730799,0.19795363,0.000047096455,0.0024362071,1.9653294e-7,0.000083722494,0.000119393364,0.78703195,0.000038014932,0.0005103298,0.0113903005],"study_design_scores_gemma":[0.00028542336,0.00009461737,0.0037529452,0.000014424654,0.0019503487,0.000003667968,0.00008436206,0.016078118,0.96995366,0.00012601752,0.0074390373,0.00021740937],"about_ca_topic_score_codex":0.0004253135,"about_ca_topic_score_gemma":0.00015781989,"teacher_disagreement_score":0.48332104,"about_ca_system_score_codex":0.000008454665,"about_ca_system_score_gemma":0.000023884728,"threshold_uncertainty_score":0.47480753},"labels":[],"label_agreement":null},{"id":"W2021090852","doi":"10.1016/s0165-1684(02)00479-6","title":"Dynamics in high-dimensional model gene networks","year":2003,"lang":"en","type":"article","venue":"Signal Processing","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":38,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; University of Victoria","funders":"","keywords":"Attractor; Ordinary differential equation; Boolean network; Product (mathematics); Binary number; Function (biology); Set (abstract data type); Gene regulatory network; Mathematics; Boolean function; Boolean model; Class (philosophy); Dynamical systems theory; Statistical physics; Differential equation; Computer science; Topology (electrical circuits); Biological system; Gene; Algorithm; Physics; Discrete mathematics; Biology; Mathematical analysis; Artificial intelligence; Combinatorics; Genetics","score_opus":0.006683575202701154,"score_gpt":0.21715248840478948,"score_spread":0.21046891320208833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021090852","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":[0.7795766,0.0023636096,0.21739171,0.000040211366,0.000030127532,0.000068266454,0.000002138132,0.000011836225,0.0005154663],"genre_scores_gemma":[0.9926487,0.000018505969,0.006594409,0.00017368815,0.000101016616,0.000008575677,0.000095778574,0.00002904787,0.00033026573],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99888635,0.000059655133,0.00022302513,0.00036739293,0.00014697538,0.00031659153],"domain_scores_gemma":[0.9996024,0.0000043207892,0.0000784107,0.0001714426,0.00006762404,0.000075810036],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024954812,0.00016071113,0.00015950146,0.00006108871,0.00009464555,0.000026381818,0.000112922644,0.00016373683,0.000015017928],"category_scores_gemma":[0.000010068543,0.00016392836,0.00006808229,0.00020722237,0.00005125384,0.000005295229,0.00004454721,0.00011680467,0.000002459931],"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":[0.000021168666,0.00003852626,0.0028763425,0.000008117663,0.000019991912,0.000004551343,0.000005238397,0.95568246,0.037088774,0.00020336943,0.00007421987,0.003977247],"study_design_scores_gemma":[0.00031426875,0.000025745752,0.00019254691,0.000015671434,0.000022280668,0.000012347269,0.000014976765,0.9792275,0.01887469,0.001035542,0.000050104063,0.00021434261],"about_ca_topic_score_codex":0.0000058556775,"about_ca_topic_score_gemma":0.0000704834,"teacher_disagreement_score":0.21307208,"about_ca_system_score_codex":0.000060839528,"about_ca_system_score_gemma":0.00015716525,"threshold_uncertainty_score":0.66848046},"labels":[],"label_agreement":null},{"id":"W2022057243","doi":"10.1016/j.neunet.2015.03.005","title":"A biological mechanism for Bayesian feature selection: Weight decay and raising the LASSO","year":2015,"lang":"en","type":"article","venue":"Neural Networks","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria; Dalhousie University","funders":"Canadian Institutes of Health Research","keywords":"Prior probability; Lasso (programming language); Artificial intelligence; Bayesian probability; Feature selection; Computer science; Laplace operator; Machine learning; Feature (linguistics); Gaussian; Regularization (linguistics); Pattern recognition (psychology); Mathematics","score_opus":0.018121170303154136,"score_gpt":0.24643855237786344,"score_spread":0.2283173820747093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022057243","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":[0.76674044,0.0054761632,0.22195278,0.0042198556,0.0006863015,0.0005874172,0.0000057812863,0.00005982635,0.0002714292],"genre_scores_gemma":[0.99619746,0.000116031915,0.0009432735,0.00077438337,0.0015318153,0.00003358666,0.00004907176,0.000020329464,0.0003340231],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990215,0.00011437007,0.00012433025,0.0003514295,0.000087179615,0.00030124237],"domain_scores_gemma":[0.99944806,0.00003177361,0.00006907187,0.00020600064,0.0001149066,0.00013019246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023857247,0.00016887859,0.00015814058,0.00001844047,0.0001961245,0.0000507228,0.00014904515,0.00027417525,0.0000036029908],"category_scores_gemma":[0.00003455913,0.00010942459,0.00011447809,0.00014555886,0.00006932841,0.0000033775718,0.00009157033,0.0001391904,5.102124e-7],"study_design_candidate":"simulation_or_modeling","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":[0.002833172,0.00032690563,0.075565614,0.00006261456,0.0022597874,0.00003855169,0.0003737231,0.1752763,0.18562226,0.025641324,0.39092717,0.14107257],"study_design_scores_gemma":[0.00277193,0.001637626,0.002982497,0.000022588933,0.00036108962,0.00044190133,0.00013905605,0.82208234,0.03233531,0.007021152,0.12911975,0.0010847764],"about_ca_topic_score_codex":0.0000025173313,"about_ca_topic_score_gemma":0.0000494895,"teacher_disagreement_score":0.646806,"about_ca_system_score_codex":0.0000129497585,"about_ca_system_score_gemma":0.000021891714,"threshold_uncertainty_score":0.44622052},"labels":[],"label_agreement":null},{"id":"W2022058845","doi":"10.1016/j.physd.2012.12.006","title":"State transition graph and stability of singular equilibria for piecewise linear biological models","year":2012,"lang":"en","type":"article","venue":"Physica D Nonlinear Phenomena","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Piecewise linear function; Mathematics; Stability (learning theory); Lyapunov function; Biological network; Conjecture; Piecewise; Graph; Gene regulatory network; Applied mathematics; Nonlinear system; Discontinuity (linguistics); Computer science; Discrete mathematics; Combinatorics; Mathematical analysis; Physics","score_opus":0.02687857288237754,"score_gpt":0.2539754666269042,"score_spread":0.22709689374452663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022058845","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":[0.97428066,0.001287658,0.02385497,0.000045947865,0.000035726833,0.0002813602,0.00013695145,0.000013704619,0.00006301489],"genre_scores_gemma":[0.9915485,0.00016767213,0.007180524,0.000044543955,0.00067325484,0.00002497385,0.00032701044,0.00002535974,0.000008189812],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988847,0.000081367485,0.00026456348,0.00032966665,0.00010276015,0.00033697722],"domain_scores_gemma":[0.9992873,0.000025472502,0.00011048241,0.0003358319,0.00010813746,0.00013278493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029786598,0.00018470902,0.00029306582,0.000034489698,0.000057997953,0.000007118647,0.00010605534,0.00007843699,0.0000060197003],"category_scores_gemma":[0.000013557398,0.00016569575,0.00018812003,0.00012300626,0.00017334144,0.000014626379,0.000050416027,0.00005184632,9.796078e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026194405,0.00045976008,0.0006354861,0.00007049146,0.00020113804,8.194492e-8,0.00038679707,0.0016488291,0.99272007,0.00013478052,0.000031614283,0.0034490072],"study_design_scores_gemma":[0.0021414026,0.0011653657,0.0011481738,0.000023827666,0.00032665304,0.0000033388897,0.00020484402,0.16740501,0.81274354,0.009074518,0.004892657,0.00087067677],"about_ca_topic_score_codex":0.0000045697498,"about_ca_topic_score_gemma":0.0000015704396,"teacher_disagreement_score":0.17997654,"about_ca_system_score_codex":0.000008869152,"about_ca_system_score_gemma":0.00002390538,"threshold_uncertainty_score":0.6756877},"labels":[],"label_agreement":null},{"id":"W2022818603","doi":"10.1142/s0218127409025225","title":"AN ATLAS OF ROBUST, STABLE, HIGH-DIMENSIONAL LIMIT CYCLES","year":2009,"lang":"en","type":"article","venue":"International Journal of Bifurcation and Chaos","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Limit cycle; Attractor; Mathematics; Limit (mathematics); Hypercube; Differential equation; Dynamical systems theory; Delay differential equation; Curse of dimensionality; Applied mathematics; Mathematical analysis; Discrete mathematics; Physics","score_opus":0.00790539980559765,"score_gpt":0.24768395481647112,"score_spread":0.23977855501087347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022818603","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":[0.99505293,0.00073356566,0.0024925384,0.0014673842,0.00015315015,0.000027810274,0.00000678801,0.0000021573933,0.00006368185],"genre_scores_gemma":[0.99680865,0.00031019686,0.002039719,0.0002384834,0.00044965805,4.559059e-7,0.000049063026,0.0000055220758,0.000098282355],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991866,0.000038365888,0.0003128402,0.00011263516,0.0002776305,0.00007192769],"domain_scores_gemma":[0.99897003,0.0000071832123,0.00031478106,0.00010831779,0.00052672334,0.00007297278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017770445,0.00007841147,0.00012146455,0.00012086702,0.00002418766,0.000018933742,0.0001873626,0.00006312997,0.00003223304],"category_scores_gemma":[0.000022335482,0.000070008326,0.000076845725,0.000053840296,0.0000358739,0.0000150669375,0.000019372415,0.000051985582,9.605161e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041153282,0.00042250077,0.008802432,0.0000057997604,0.0004533436,0.000009543049,0.000099706216,0.04577651,0.8935812,0.0011902804,0.002862741,0.046384383],"study_design_scores_gemma":[0.0032252613,0.0020521549,0.37308457,0.00012652724,0.00022494985,0.0004603031,0.000250351,0.0111472,0.5892752,0.0025461223,0.0170918,0.00051559607],"about_ca_topic_score_codex":0.000006563221,"about_ca_topic_score_gemma":0.000007655236,"teacher_disagreement_score":0.36428213,"about_ca_system_score_codex":0.000013142393,"about_ca_system_score_gemma":0.000054582,"threshold_uncertainty_score":0.28548566},"labels":[],"label_agreement":null},{"id":"W2023403198","doi":"10.1038/nature04473","title":"A bottom-up approach to gene regulation","year":2006,"lang":"en","type":"article","venue":"Nature","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":330,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Institutes of Health","keywords":"Psychological repression; Gene regulatory network; Computational biology; Regulation of gene expression; Counterintuitive; Modular design; Construct (python library); Gene expression; Biological system; Gene; Computer science; Synthetic biology; Expression (computer science); Biology; Genetics; Physics; Computer network","score_opus":0.0038650817093694484,"score_gpt":0.21549595480242034,"score_spread":0.2116308730930509,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2023403198","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":[0.9819615,0.0028524206,0.006109571,0.00029737994,0.0005328471,0.00020522218,0.000009737945,0.000031074647,0.008000263],"genre_scores_gemma":[0.9840575,0.0000070663887,0.006009057,0.00047594032,0.002359954,0.000013719242,0.00043870913,0.000020337713,0.0066177007],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991506,0.00003136923,0.00011717169,0.00033793255,0.00017978871,0.0001831826],"domain_scores_gemma":[0.9994282,0.0000018102927,0.00004067648,0.0003786827,0.00009418348,0.000056441],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000111931724,0.000118744625,0.00010385116,0.000051713963,0.000057037418,0.000018671728,0.00014385486,0.0009850519,0.000008310204],"category_scores_gemma":[0.000014340789,0.00011302994,0.00009730522,0.00023294563,0.000016308963,0.0000015944458,0.000053540385,0.0003230317,0.000015540529],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030172387,0.000043097913,0.0012528513,0.0000060212824,0.00004195328,3.889197e-7,0.0000087000135,0.0068727215,0.7325703,0.00038986973,0.25812718,0.0006567534],"study_design_scores_gemma":[0.00050942245,0.00006894281,0.03822227,0.0000053195977,0.00007747248,0.000021947799,0.000016029864,0.0012001293,0.5339409,0.00048816486,0.42500564,0.0004437574],"about_ca_topic_score_codex":0.000009478274,"about_ca_topic_score_gemma":0.000016266631,"teacher_disagreement_score":0.19862938,"about_ca_system_score_codex":0.000016141088,"about_ca_system_score_gemma":0.000026809555,"threshold_uncertainty_score":0.7597622},"labels":[],"label_agreement":null},{"id":"W2023412226","doi":"10.1016/j.jtbi.2004.05.022","title":"Inferring models of gene expression dynamics","year":2004,"lang":"en","type":"article","venue":"Journal of Theoretical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":60,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computational biology; Gene expression; Dynamics (music); Expression (computer science); Biology; Gene; Computer science; Evolutionary biology; Genetics; Physics","score_opus":0.00649875981995066,"score_gpt":0.24344623054926076,"score_spread":0.2369474707293101,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2023412226","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":[0.81301904,0.0006954054,0.1855861,0.00015400846,0.000105150095,0.000029397737,0.000004836956,0.0000018505095,0.00040422735],"genre_scores_gemma":[0.9886054,0.00018370927,0.0109151555,0.00005933175,0.00020349205,6.510485e-7,0.000013255281,0.0000115313205,0.0000074876943],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990523,0.00009767557,0.0004416263,0.00013638115,0.000095842806,0.00017619264],"domain_scores_gemma":[0.99919397,0.000020198513,0.00028574426,0.00022683108,0.00017798117,0.00009526509],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035238187,0.00010935386,0.00028228154,0.00007756503,0.000025144496,0.000004040653,0.000258767,0.00021049475,0.000021957312],"category_scores_gemma":[0.0001035908,0.00008151498,0.00023463818,0.0000753311,0.00035915762,0.0000035738308,0.0000940509,0.000118560696,0.0000010146723],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015463654,0.000069363574,0.0010974763,0.0000063617085,0.00011271406,0.000004002114,0.000017962206,0.029075988,0.8440037,0.12483182,0.000020101565,0.00060588034],"study_design_scores_gemma":[0.0007120667,0.0006726,0.00013334246,0.000030815776,0.000075021504,0.00011538767,0.000037361915,0.0013595133,0.8180992,0.178548,0.000091917704,0.00012478037],"about_ca_topic_score_codex":0.0000012115477,"about_ca_topic_score_gemma":0.0000015984629,"teacher_disagreement_score":0.17558636,"about_ca_system_score_codex":0.000028264953,"about_ca_system_score_gemma":0.00007427504,"threshold_uncertainty_score":0.33240846},"labels":[],"label_agreement":null},{"id":"W2023873427","doi":"10.1016/j.biosystems.2012.01.004","title":"Computational simulation of a gene regulatory network implementing an extendable synchronous single-input delay flip-flop","year":2012,"lang":"en","type":"article","venue":"Biosystems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Modular design; Computer science; Function (biology); Finite-state machine; State (computer science); Algorithm; Biology; Genetics","score_opus":0.015228418083258097,"score_gpt":0.2603252809925863,"score_spread":0.2450968629093282,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2023873427","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":[0.96033263,0.0032804094,0.03559125,0.0000058478486,0.00031701243,0.000233386,0.000019165756,0.000027270988,0.00019300533],"genre_scores_gemma":[0.99225545,0.000005404086,0.005136902,0.000032313714,0.0019394967,0.00001234845,0.00048119368,0.000042675558,0.00009424583],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980765,0.00018505674,0.00055650395,0.00034916442,0.0002816133,0.00055118225],"domain_scores_gemma":[0.9987435,0.000022731463,0.0003728921,0.00049302704,0.00020104052,0.0001668302],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007735405,0.00021184991,0.00028715853,0.00006753212,0.00016576317,0.00002524959,0.00017449562,0.00017432348,0.00002926126],"category_scores_gemma":[0.000018647423,0.0002198378,0.00015596377,0.000218971,0.00004837603,0.000018224588,0.00008680118,0.000047466085,0.000008426311],"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":[0.00003547059,0.00015004593,0.028690394,0.000043309206,0.00025025933,9.497574e-7,0.00009853174,0.7123133,0.25453195,0.00006900576,0.00047235025,0.003344438],"study_design_scores_gemma":[0.0021530888,0.000969536,0.059467297,0.00019980832,0.00058463064,0.0001394665,0.0004940671,0.6164416,0.27170795,0.00009640873,0.0459986,0.0017475421],"about_ca_topic_score_codex":0.000023356964,"about_ca_topic_score_gemma":0.000026328078,"teacher_disagreement_score":0.09587169,"about_ca_system_score_codex":0.00005423152,"about_ca_system_score_gemma":0.00006394188,"threshold_uncertainty_score":0.8964726},"labels":[],"label_agreement":null},{"id":"W2024576792","doi":"10.1103/physreve.77.021919","title":"Plasmid-borne prokaryotic gene expression: Sources of variability and quantitative system characterization","year":2008,"lang":"en","type":"article","venue":"Physical Review E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; College of Family Physicians of Canada","funders":"Natural Sciences and Engineering Research Council of Canada; Florida State University","keywords":"Plasmid; Computational biology; Gene; Biology; Expression (computer science); Gene expression; Characterization (materials science); Genetics; Computer science; Physics","score_opus":0.014532996258134458,"score_gpt":0.2619171509113926,"score_spread":0.24738415465325816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024576792","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":[0.99289507,0.004710022,0.0020269428,0.00004880174,0.00001857797,0.0002220532,0.000009755871,0.0000078276225,0.000060953458],"genre_scores_gemma":[0.9953992,0.0038851253,0.0004081805,0.0000387832,0.00010397017,0.000027869293,0.000106395906,0.000009955825,0.000020551823],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990541,0.00021902789,0.00021880951,0.0002729394,0.00012313503,0.00011202157],"domain_scores_gemma":[0.9994292,0.000023739798,0.00012223123,0.0002755579,0.00009135202,0.000057911642],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002211831,0.00011434739,0.00033222258,0.0000120678515,0.000054811087,0.0000027916913,0.0000820548,0.000032935684,0.000004705483],"category_scores_gemma":[0.000080472855,0.00008195206,0.000103477185,0.000091103866,0.000100259895,0.0000042405445,0.00007392018,0.000036521928,0.0000043813234],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015134798,0.00007233264,0.0022492101,0.0010440358,0.000048187765,0.0000010606301,0.000048341022,0.00003459457,0.9959103,0.00020063994,0.000034067263,0.00034211084],"study_design_scores_gemma":[0.00017646926,0.00015374967,0.013827652,0.0005604496,0.00016817055,0.000021770757,0.000011199304,0.0015697653,0.98209673,0.000035717316,0.001184368,0.00019394107],"about_ca_topic_score_codex":0.0000010596073,"about_ca_topic_score_gemma":1.394525e-7,"teacher_disagreement_score":0.013813538,"about_ca_system_score_codex":0.000006893247,"about_ca_system_score_gemma":0.000022384243,"threshold_uncertainty_score":0.3341908},"labels":[],"label_agreement":null},{"id":"W2024882852","doi":"10.1063/1.1689451","title":"Dynamics and bistability in a reduced model of the <i>lac</i> operon","year":2004,"lang":"en","type":"article","venue":"Chaos An Interdisciplinary Journal of Nonlinear Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":90,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Bistability; lac operon; Permease; Operon; Lactose permease; Dynamics (music); L-arabinose operon; Function (biology); Biological system; Physics; Nonlinear system; Statistical physics; Chemistry; Biology; Transporter; Biochemistry; Genetics; Gene; Mutant; Quantum mechanics; Escherichia coli","score_opus":0.012484689520385086,"score_gpt":0.292222203535171,"score_spread":0.2797375140147859,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024882852","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":[0.9970756,0.00013891401,0.0018902783,0.0006990534,0.00008310165,0.00006477031,0.000006916967,9.622125e-7,0.00004038646],"genre_scores_gemma":[0.9961957,0.00003267518,0.0036542243,0.000025366624,0.00006317789,7.068294e-7,0.0000013990918,0.0000069468374,0.000019854122],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989416,0.000038975457,0.00038624753,0.00022898045,0.00023665652,0.0001675462],"domain_scores_gemma":[0.9990713,0.0000042075235,0.00024354967,0.0003704053,0.00021168962,0.00009884946],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008353133,0.00009949842,0.00017686139,0.00010109355,0.0001295269,0.000020448912,0.0006056808,0.000053836568,0.0000012197373],"category_scores_gemma":[0.00004458591,0.00006820367,0.00010194459,0.00034727002,0.00071485736,0.000027301752,0.0006466347,0.00013324118,1.2417513e-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":[0.0001262929,0.00023550006,0.0049931123,0.000015911712,0.000014662601,0.000002806494,0.00086198904,0.14506751,0.8474032,0.000082420695,0.000004261003,0.0011922771],"study_design_scores_gemma":[0.0014327107,0.0013684784,0.029861152,0.00023289457,0.000058672864,0.00030016672,0.002348889,0.6006379,0.36000955,0.0034007465,0.000008354255,0.0003404803],"about_ca_topic_score_codex":0.000004767369,"about_ca_topic_score_gemma":0.00016914876,"teacher_disagreement_score":0.4873937,"about_ca_system_score_codex":0.00007761888,"about_ca_system_score_gemma":0.00039127446,"threshold_uncertainty_score":0.2781265},"labels":[],"label_agreement":null},{"id":"W2026888821","doi":"10.1089/cmb.2006.13.1630","title":"A General Modeling Strategy for Gene Regulatory Networks with Stochastic Dynamics","year":2006,"lang":"en","type":"article","venue":"Journal of Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":127,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Fundação para a Ciência e a Tecnologia; Natural Sciences and Engineering Research Council of Canada; Government of Alberta","keywords":"Gene; Gene regulatory network; Genetic network; Stochastic modelling; Computer science; Computational biology; Translation (biology); Genetics; Transcription (linguistics); Regulation of gene expression; Stochastic process; Activator (genetics); Biology; Gene expression; Mathematics; Messenger RNA","score_opus":0.008581990317334634,"score_gpt":0.24164874193117683,"score_spread":0.2330667516138422,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026888821","genre_codex":"methods","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":[0.4606334,0.00065806793,0.5385266,0.00004286422,0.00006118115,0.00005508926,0.000007981071,0.0000024042204,0.000012413883],"genre_scores_gemma":[0.96784693,0.000008720351,0.030330008,0.00007156722,0.0012238389,0.0000051694624,0.00042708457,0.000022045295,0.00006464494],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989405,0.00006251858,0.0004534223,0.00020098485,0.00011847878,0.00022406178],"domain_scores_gemma":[0.9988934,0.000034025798,0.00035174767,0.0001183286,0.00053793925,0.00006456411],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002489635,0.00015521752,0.0002600973,0.00010063966,0.00007916208,0.000016747836,0.0001550168,0.00015336802,0.0000031277903],"category_scores_gemma":[0.000010633976,0.00012829245,0.0001757738,0.000096899734,0.00007801631,0.000005016901,0.000025705514,0.00009110387,3.2309094e-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":[0.00023430816,0.00003869008,0.00037717517,0.0000028019715,0.00018325353,0.0000020235666,0.0000016476355,0.99204516,0.004240029,0.0015606333,0.00024289258,0.0010713737],"study_design_scores_gemma":[0.0008796507,0.00061382784,0.00094812905,0.00000774219,0.00009213832,0.00019891644,0.000009432859,0.9898643,0.0002724205,0.0068944935,0.00006126077,0.00015768613],"about_ca_topic_score_codex":0.000005753833,"about_ca_topic_score_gemma":0.000028734297,"teacher_disagreement_score":0.5081966,"about_ca_system_score_codex":0.00004223203,"about_ca_system_score_gemma":0.00018780076,"threshold_uncertainty_score":0.5231615},"labels":[],"label_agreement":null},{"id":"W2027146421","doi":"10.1109/tcbb.2011.126","title":"Inference of Biological S-System Using the Separable Estimation Method and the Genetic Algorithm","year":2011,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Computational Biology and Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; East China Institute of Technology; Hebei University; East China University of Science and Technology; Northwestern Polytechnical University; Northwestern University","keywords":"Pruning; Algorithm; Nonlinear system; Computer science; Inference; System identification; Genetic algorithm; Identification (biology); Estimation theory; Ode; Biological data; Mathematics; Mathematical optimization; Artificial intelligence; Machine learning; Data mining; Measure (data warehouse); Applied mathematics","score_opus":0.03293658870511484,"score_gpt":0.2971496816110002,"score_spread":0.26421309290588535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2027146421","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":[0.14156154,0.00021034117,0.85790026,0.000038924412,0.00006665012,0.00015559784,0.00002768177,0.000007698366,0.00003132441],"genre_scores_gemma":[0.6727115,0.000089553054,0.3270763,0.0000712385,0.000016720724,0.00000911991,0.000017782377,0.0000031937689,0.0000046330188],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999144,0.00018956047,0.00033487755,0.00014054889,0.00006970992,0.00012131178],"domain_scores_gemma":[0.99928796,0.00021057807,0.00016495131,0.00020671786,0.000095223826,0.000034545024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037764598,0.00012759988,0.00017585004,0.00005305567,0.00025896178,0.000011932919,0.00015122592,0.00014238789,0.000005663586],"category_scores_gemma":[0.000020056481,0.00007149488,0.00007152327,0.00012596368,0.0004690855,0.000006755451,0.000015729976,0.00008944138,0.0000013122395],"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":[0.00040487453,0.00012751725,0.0026778684,0.0001063552,0.00092831935,8.67474e-7,0.0013650616,0.7114505,0.0022581937,0.0025942945,0.000025542278,0.27806056],"study_design_scores_gemma":[0.0005582309,0.00018040529,0.0021538585,0.000013092838,0.00011283265,0.000083000516,0.00030926857,0.98961806,0.0035778962,0.0032448207,0.000032456825,0.00011604907],"about_ca_topic_score_codex":0.000030718355,"about_ca_topic_score_gemma":0.0000039026404,"teacher_disagreement_score":0.5311499,"about_ca_system_score_codex":0.0000072924754,"about_ca_system_score_gemma":0.00004205037,"threshold_uncertainty_score":0.29154763},"labels":[],"label_agreement":null},{"id":"W2027606895","doi":"10.1109/iembs.2011.6090207","title":"Estimating parameters in genetic regulatory networks with SUM logic","year":2011,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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 Saskatchewan","funders":"","keywords":"Gene regulatory network; Inference; Computer science; Genetic network; Nonlinear system; Genetic algorithm; Stability (learning theory); Function (biology); Mathematical optimization; Mathematics; Artificial intelligence; Gene; Biology; Machine learning; Genetics","score_opus":0.014820118895956736,"score_gpt":0.2119057739521321,"score_spread":0.19708565505617534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2027606895","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":[0.94479334,0.00053089805,0.05295512,0.000012070492,0.00006011505,0.0001279525,3.739484e-7,0.00002051829,0.0014996206],"genre_scores_gemma":[0.87543076,0.000016310127,0.123996325,0.00017421148,0.00007564093,0.000019518568,0.00001547302,0.0000265042,0.00024525163],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9987862,0.00007086372,0.00024258296,0.00043234165,0.000110264875,0.0003577162],"domain_scores_gemma":[0.9992469,0.0000066411717,0.00008762461,0.0005192144,0.000045053745,0.00009458619],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016586666,0.00019127452,0.00018694822,0.00006678577,0.000043895037,0.000012374219,0.0001966859,0.00014845062,0.000046901332],"category_scores_gemma":[0.000013251547,0.00015769768,0.000076573706,0.00020790569,0.00010668412,0.0000027363963,0.00007739385,0.00008530636,0.000006725845],"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":[0.00016222129,0.00013980767,0.36108196,0.000018735202,0.00024765884,0.00005093203,0.00008331992,0.62535745,0.006055851,0.00011903953,0.0008308323,0.00585222],"study_design_scores_gemma":[0.0020126752,0.0012161464,0.71871835,0.000085953994,0.0002559817,0.00015047366,0.0002794579,0.23435657,0.040052123,0.00076249504,0.00042681696,0.0016829395],"about_ca_topic_score_codex":0.000093082504,"about_ca_topic_score_gemma":0.00043970608,"teacher_disagreement_score":0.39100087,"about_ca_system_score_codex":0.000016453332,"about_ca_system_score_gemma":0.000037087608,"threshold_uncertainty_score":0.6430725},"labels":[],"label_agreement":null},{"id":"W2027766652","doi":"10.3182/20131216-3-in-2044.00007","title":"Development of Toxicity Index to Evaluate the Level of Water Contamination by Using Cellular Responses","year":2013,"lang":"en","type":"article","venue":"IFAC Proceedings Volumes","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Health Services; University of Calgary; Alberta Health; University of Alberta","funders":"","keywords":"Toxicity; Contamination; Environmental science; Environmental chemistry; Index (typography); Toxicology; Chemistry; Biology; Computer science; Ecology","score_opus":0.03128032024158326,"score_gpt":0.2627843591400389,"score_spread":0.23150403889845564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2027766652","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":[0.9963035,0.00014759811,0.0031114256,0.000096490985,0.000025024316,0.0002582305,0.000005074006,0.000004329006,0.00004830611],"genre_scores_gemma":[0.9963689,0.000004363405,0.0026364757,0.000049123522,0.00003393768,0.00002650314,0.000014439242,0.00001461137,0.00085163495],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99898124,0.000021240277,0.0003267931,0.00022591681,0.000245777,0.00019902867],"domain_scores_gemma":[0.9992247,0.000005586524,0.000107412074,0.0001271157,0.00048558065,0.000049561615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047194408,0.00012812433,0.0001731343,0.00005912176,0.00008640534,0.00001992564,0.00020409466,0.00009276321,0.00003415728],"category_scores_gemma":[0.00006288029,0.00008763311,0.00006424277,0.000113595015,0.00007047252,0.0000086245855,0.00014993375,0.00003825091,0.000005829801],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003136813,0.000025035739,0.009534248,0.000022127879,0.000084233914,2.7783024e-8,0.00055285275,0.000051522504,0.98615026,0.000002885038,0.0008975061,0.0026479533],"study_design_scores_gemma":[0.00015077344,0.00005311384,0.009785824,0.00001535971,0.00003540903,9.64254e-7,0.00038499417,0.0014676838,0.98593944,0.000019792973,0.0020277945,0.000118834316],"about_ca_topic_score_codex":0.00004188063,"about_ca_topic_score_gemma":0.000011069973,"teacher_disagreement_score":0.002529119,"about_ca_system_score_codex":0.000026326743,"about_ca_system_score_gemma":0.00005696677,"threshold_uncertainty_score":0.35735744},"labels":[],"label_agreement":null},{"id":"W2028673254","doi":"10.1142/s0218339009002879","title":"NONLINEAR DYNAMICS OF CELL CYCLES WITH STOCHASTIC MATHEMATICAL MODELS","year":2009,"lang":"en","type":"article","venue":"Journal of Biological Systems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"Directorate for Biological Sciences","keywords":"Nonlinear system; Computer science; Parametric statistics; Stochastic modelling; Biological system; Phase portrait; Hierarchy; Gene regulatory network; Mathematical model; Dynamics (music); Biology; Mathematics; Physics; Gene; Gene expression","score_opus":0.014328109082579856,"score_gpt":0.23002184671654508,"score_spread":0.2156937376339652,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028673254","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":[0.8943511,0.0010922606,0.104118854,0.00005040005,0.00003906172,0.00008495977,0.0000058799087,0.0000031230434,0.00025433846],"genre_scores_gemma":[0.9966409,0.000060429855,0.00296542,0.0000193022,0.00023524037,9.1314456e-7,0.000011385756,0.0000073439232,0.000059062295],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988399,0.00009249435,0.0005473404,0.00014424317,0.00020317493,0.00017284624],"domain_scores_gemma":[0.9989695,0.000023707693,0.0004994768,0.00019281563,0.00020516518,0.0001093375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003334382,0.00013958421,0.0004330886,0.000049070935,0.000025505027,0.0000127639605,0.00022416157,0.00017996447,0.0000049660407],"category_scores_gemma":[0.00002569129,0.00008038375,0.0001879419,0.00010023261,0.000077751494,0.0000038332396,0.000025964933,0.00010128959,0.0000014449117],"study_design_candidate":"simulation_or_modeling","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":[0.00089738076,0.0012212672,0.0016004243,0.00011624217,0.0005599973,0.00004948002,0.000068280715,0.47512966,0.516503,0.0019736257,0.00032701762,0.001553669],"study_design_scores_gemma":[0.005318154,0.02733169,0.003465339,0.00085530645,0.0009606349,0.0026998085,0.001954325,0.8599292,0.08431958,0.010860084,0.000585677,0.0017201967],"about_ca_topic_score_codex":0.0000011650993,"about_ca_topic_score_gemma":0.0000011136489,"teacher_disagreement_score":0.43218338,"about_ca_system_score_codex":0.00002011297,"about_ca_system_score_gemma":0.00004182742,"threshold_uncertainty_score":0.32779542},"labels":[],"label_agreement":null},{"id":"W2028773706","doi":"10.1007/s10910-011-9817-4","title":"Linear conjugacy of chemical reaction networks","year":2011,"lang":"en","type":"article","venue":"Journal of Mathematical Chemistry","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":49,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Ordinary differential equation; Conjugacy class; Mathematics; Action (physics); Network dynamics; Polynomial; Reaction dynamics; Work (physics); Differential equation; Computer science; Statistical physics; Discrete mathematics; Physics; Mathematical analysis; Thermodynamics","score_opus":0.015038255910059467,"score_gpt":0.23561352175720285,"score_spread":0.22057526584714338,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028773706","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":[0.98885757,0.00037259347,0.007432768,0.000020175543,0.000040533967,0.000033271124,0.0000010985793,0.0000038383846,0.0032381318],"genre_scores_gemma":[0.9936068,0.000053578402,0.0056622657,0.000019136682,0.0004694123,0.0000011948352,0.0000056970953,0.000018565728,0.00016333141],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988429,0.000023833803,0.000625514,0.00013173504,0.0002138071,0.0001622033],"domain_scores_gemma":[0.9987912,0.000022718423,0.00051374955,0.0002906539,0.00024308609,0.00013856967],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035298077,0.00013441635,0.00033181894,0.000020277383,0.000013679321,0.000003953268,0.0002418342,0.00022062445,0.00021369585],"category_scores_gemma":[0.00019546175,0.00011314664,0.0003041495,0.00008907607,0.00011543681,0.0000049271243,0.00006445974,0.00018149061,0.0000033503404],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001266898,0.00020897755,0.0002684666,0.00008969956,0.00020237146,0.00000708636,0.000030618514,0.000057067675,0.9980227,0.000034985267,0.00065863965,0.0002927184],"study_design_scores_gemma":[0.00036130712,0.0000778383,0.0000921152,0.000059266633,0.00015172332,0.00025570503,0.000051416744,0.0007058758,0.9969564,0.0008013318,0.00036703653,0.00011997279],"about_ca_topic_score_codex":4.3019293e-7,"about_ca_topic_score_gemma":4.413935e-8,"teacher_disagreement_score":0.004749229,"about_ca_system_score_codex":0.000014662275,"about_ca_system_score_gemma":0.000054244676,"threshold_uncertainty_score":0.46139863},"labels":[],"label_agreement":null},{"id":"W2029885002","doi":"10.1016/j.ecocom.2011.07.006","title":"Process algebra-based computational tools in ecological modelling","year":2011,"lang":"en","type":"article","venue":"Ecological Complexity","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"McGill University","keywords":"Process (computing); Computer science; Process calculus; Algebra over a field; Ecology; Theoretical computer science; Mathematics; Programming language; Biology","score_opus":0.11796456492034327,"score_gpt":0.28726331597980614,"score_spread":0.16929875105946288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029885002","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":[0.9695741,0.00005119048,0.027874248,0.00008609445,0.000040823143,0.00021183591,0.000009489474,0.000032772066,0.0021194436],"genre_scores_gemma":[0.9837886,0.0000030052552,0.015263493,0.0006053216,0.00007213858,0.00004816823,0.00017984827,0.00001098493,0.000028405686],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99836165,0.00020915261,0.00036966385,0.0005197649,0.00016841982,0.00037137262],"domain_scores_gemma":[0.9994009,0.00005429363,0.00010656594,0.00022182002,0.000099758334,0.000116656876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003868559,0.00019175284,0.00028512595,0.000056656598,0.0001101743,0.000018487479,0.00031323984,0.00024493263,0.0007628303],"category_scores_gemma":[0.000092585746,0.00016646588,0.00014834238,0.00021281786,0.00023558445,0.0000056157005,0.0001117346,0.00016503241,0.00003190553],"study_design_candidate":"simulation_or_modeling","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":[0.0003036948,0.0018901008,0.12565018,0.000026879707,0.00008023303,0.000043691904,0.000056870602,0.8659165,0.0010354394,0.004066595,0.0004140361,0.0005157697],"study_design_scores_gemma":[0.0008230808,0.00054361223,0.6499793,0.0000061687765,0.00002287038,0.000007486255,0.000037516238,0.30543756,0.0017620517,0.040616933,0.00034910877,0.00041430473],"about_ca_topic_score_codex":0.000008059139,"about_ca_topic_score_gemma":0.00011896923,"teacher_disagreement_score":0.560479,"about_ca_system_score_codex":0.000038666552,"about_ca_system_score_gemma":0.00008695237,"threshold_uncertainty_score":0.83524567},"labels":[],"label_agreement":null},{"id":"W2030478059","doi":"10.4208/cicp.280110.070510a","title":"An Algorithm for the Stochastic Simulation of Gene Expression and Heterogeneous Population Dynamics","year":2010,"lang":"en","type":"article","venue":"Communications in Computational Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"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 Ottawa","funders":"","keywords":"Benchmark (surveying); Stochastic simulation; Population; Monte Carlo method; Expression (computer science); Stochastic modelling; Dynamics (music)","score_opus":0.016601811753011397,"score_gpt":0.30960069258946044,"score_spread":0.29299888083644904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030478059","genre_codex":"methods","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":[0.27672595,0.0001482641,0.72285587,0.000039385668,0.00002895746,0.00016655214,0.000029004736,0.0000039013735,0.0000021176554],"genre_scores_gemma":[0.8903466,0.000010276431,0.10820687,0.000017705524,0.00007274892,0.00003153307,0.0013005444,0.000011520156,0.0000022384615],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99945885,0.000054271342,0.00019015295,0.00014341109,0.00008410179,0.00006922959],"domain_scores_gemma":[0.9988714,0.0001906125,0.00011998424,0.00063457014,0.0001609212,0.000022524568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014426654,0.00007508286,0.00008432249,0.000028506185,0.00015272075,0.00001432098,0.00027660173,0.000060336442,6.038224e-7],"category_scores_gemma":[0.000024767774,0.000070180125,0.000042551015,0.00009874774,0.00010091558,0.000008228541,0.00008461704,0.00007298279,1.422702e-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":[0.0000061393052,0.00006403361,0.0007703783,0.0000024860244,0.000016117032,9.341663e-9,0.000028697954,0.94904023,0.010074249,0.0004967545,0.0000017381942,0.039499182],"study_design_scores_gemma":[0.00019785421,0.000030884523,0.00517999,0.0000037991617,0.00002105535,0.0000012137783,0.000017968534,0.9868715,0.0010499253,0.0065380586,0.000017199734,0.00007054334],"about_ca_topic_score_codex":0.000010352076,"about_ca_topic_score_gemma":0.00008994251,"teacher_disagreement_score":0.614649,"about_ca_system_score_codex":0.000010583434,"about_ca_system_score_gemma":0.000023830911,"threshold_uncertainty_score":0.28618625},"labels":[],"label_agreement":null},{"id":"W2030617701","doi":"10.1002/cjce.20025","title":"Systems Biology: The synergistic interplay between biology and mathematics","year":2008,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Systems biology; Domain (mathematical analysis); Data science; Field (mathematics); Process (computing); Computer science; Biology; Computational biology; Mathematics","score_opus":0.008658589638484274,"score_gpt":0.21872873347932648,"score_spread":0.21007014384084222,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030617701","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":[0.9930942,0.0033656799,0.0031139767,0.00022645284,0.00011837275,0.00004183702,0.0000063623283,0.0000023660755,0.000030735773],"genre_scores_gemma":[0.9991636,0.00002291135,0.00020550832,0.0000285188,0.0005352699,0.0000017301957,0.0000060800726,0.000013735223,0.00002263173],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993841,0.000028619193,0.00024996774,0.000084342355,0.000044774893,0.00020821388],"domain_scores_gemma":[0.9993939,0.000065067885,0.00010263701,0.00018880786,0.000061516854,0.00018807249],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026595156,0.00010754008,0.00019130432,0.000049947303,0.000082850805,0.000015870348,0.0002933017,0.000113597445,0.0000028839654],"category_scores_gemma":[0.00016858733,0.000063672145,0.00007763317,0.00008007365,0.00020469486,0.0000018690336,0.000031295902,0.00017823953,9.583043e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008114147,0.0000075819867,0.013070154,0.00004725135,0.00089195516,0.00002344365,0.00036386892,0.0130981505,0.9685217,0.0019555318,0.0015569351,0.00045531342],"study_design_scores_gemma":[0.0028392046,0.0009994501,0.007136428,0.00062841194,0.0020104104,0.009555729,0.00041645125,0.06441923,0.7819091,0.0026732427,0.12474821,0.0026641078],"about_ca_topic_score_codex":0.00018071542,"about_ca_topic_score_gemma":0.000040879542,"teacher_disagreement_score":0.18661258,"about_ca_system_score_codex":0.000030182382,"about_ca_system_score_gemma":0.00013201652,"threshold_uncertainty_score":0.2596475},"labels":[],"label_agreement":null},{"id":"W2030990090","doi":"10.1109/isb.2012.6314134","title":"New global stability conditions for genetic regulatory networks with time-varying delays","year":2012,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"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 Saskatchewan","funders":"","keywords":"Stability (learning theory); Linear matrix inequality; Lyapunov function; Function (biology); Control theory (sociology); Computer science; Matrix (chemical analysis); Gene regulatory network; Genetic algorithm; Mathematical optimization; Mathematics; Gene; Nonlinear system; Control (management); Biology; Genetics; Artificial intelligence; Physics","score_opus":0.008877458780960657,"score_gpt":0.23413831299525323,"score_spread":0.22526085421429257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030990090","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":[0.72692865,0.0017610561,0.26959363,0.00005214928,0.00008906997,0.00033882153,0.000022626284,0.00003435296,0.00117965],"genre_scores_gemma":[0.9701789,0.000014883742,0.027667226,0.00019098709,0.0007844773,0.000038479753,0.00026283565,0.000028514716,0.00083371054],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99870306,0.00005527383,0.00022703655,0.0003664098,0.00013198884,0.0005162013],"domain_scores_gemma":[0.99889386,0.00001590578,0.000086195454,0.0005826933,0.00010318654,0.00031817108],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018320898,0.00021089251,0.00019819666,0.000018675624,0.00014821798,0.000022004866,0.00016119693,0.00017593859,0.00026437195],"category_scores_gemma":[0.000013922351,0.000185506,0.0001641338,0.00016738079,0.000077319826,0.0000073465594,0.000071226226,0.000046277164,0.000016000127],"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":[0.00064814487,0.00043455506,0.59851825,0.00006743005,0.002038696,0.0000030635745,0.00006690873,0.15236329,0.09955371,0.0012168004,0.13438532,0.010703868],"study_design_scores_gemma":[0.008537182,0.0021905673,0.661531,0.00007955391,0.0030389694,0.00047630223,0.00027093862,0.08687337,0.14396328,0.0014055453,0.08703634,0.004596983],"about_ca_topic_score_codex":0.000016679418,"about_ca_topic_score_gemma":0.000054440337,"teacher_disagreement_score":0.24325025,"about_ca_system_score_codex":0.000049674698,"about_ca_system_score_gemma":0.0001272513,"threshold_uncertainty_score":0.75647146},"labels":[],"label_agreement":null},{"id":"W2031094314","doi":"10.1016/j.febslet.2008.07.028","title":"Delay stochastic simulation of single‐gene expression reveals a detailed relationship between protein noise and mean abundance","year":2008,"lang":"en","type":"article","venue":"FEBS Letters","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Messenger RNA; Scaling; Noise (video); Transcription (linguistics); Gene expression; Gene; Physics; Statistical physics; Biology; Statistics; Genetics; Mathematics; Computer science","score_opus":0.02279350151321172,"score_gpt":0.23928544350373374,"score_spread":0.21649194199052202,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031094314","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":[0.9155008,0.00029027014,0.08381885,0.000116453026,0.000015378931,0.00023306019,0.0000067717956,0.000010835167,0.000007548094],"genre_scores_gemma":[0.99700636,0.000002091893,0.0025309303,0.000088551824,0.0001625185,0.000016941396,0.000078586505,0.00002304042,0.00009096732],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989439,0.000119192395,0.00028504833,0.00031089026,0.000167755,0.00017319256],"domain_scores_gemma":[0.99929607,0.00004870194,0.00019816223,0.00032625516,0.000057200148,0.000073623276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001471071,0.00014307616,0.00019419564,0.000056313744,0.00012185506,0.0000074785607,0.0000970799,0.00011327384,0.0000035234932],"category_scores_gemma":[0.00011031542,0.00014378333,0.00007893229,0.00013521768,0.00011076721,0.000007701733,0.000054421333,0.000064611,0.0000023987025],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033221873,0.000013822289,0.11081379,0.000014101031,0.00002879057,0.0000016445526,0.00007587166,0.065181956,0.8237024,0.0000012366887,0.0000789217,0.000054269723],"study_design_scores_gemma":[0.0010691884,0.00021030579,0.3626202,0.00012723349,0.00015091714,0.000015036995,0.000018290992,0.0024736451,0.6326173,0.00010873545,0.00011032852,0.00047883697],"about_ca_topic_score_codex":0.0000033579704,"about_ca_topic_score_gemma":0.0000057832453,"teacher_disagreement_score":0.2518064,"about_ca_system_score_codex":0.000018957731,"about_ca_system_score_gemma":0.000017347047,"threshold_uncertainty_score":0.58633137},"labels":[],"label_agreement":null},{"id":"W2031318755","doi":"10.1016/j.semcancer.2013.06.003","title":"How to escape the cancer attractor: Rationale and limitations of multi-target drugs","year":2013,"lang":"en","type":"review","venue":"Seminars in Cancer Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":119,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Alberta Innovates","keywords":"Attractor; Cancer; Cancer cell; Computer science; Biology; Mathematics; Genetics","score_opus":0.06433403230232843,"score_gpt":0.33988038172998236,"score_spread":0.27554634942765394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031318755","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016484533,0.9964393,0.00008248175,0.00051474426,0.0002541955,0.00078608765,0.00023494221,0.0000037788507,0.000036044254],"genre_scores_gemma":[0.0014675647,0.9938753,0.0012483811,0.00012787746,0.0003207073,0.0012635861,0.00036786587,0.00003716005,0.0012915542],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99838656,0.00024975662,0.00040253942,0.0005911927,0.00008051686,0.00028940634],"domain_scores_gemma":[0.9988184,0.0001670276,0.0003318735,0.00048411472,0.00012256143,0.0000760394],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002331228,0.00031789692,0.0007885979,0.00013024348,0.000059599275,0.000019376139,0.0003965226,0.00044166727,0.000029263225],"category_scores_gemma":[0.00012688049,0.00022500835,0.00022196985,0.00029816598,0.00020959534,0.0000035291469,0.00020434146,0.00018118414,0.0000029223322],"study_design_candidate":"not_applicable","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":[0.000006411437,0.0000355791,0.0005271781,0.0005526419,0.00037667766,3.2979813e-7,0.00013612787,0.00018944625,0.0027057508,0.000022883867,0.0054226792,0.99002427],"study_design_scores_gemma":[0.000114981725,0.0000612364,0.000064278254,0.00058774557,0.00022314234,0.0000030321619,0.00008788417,0.000029557494,0.00055904326,0.000018101335,0.99800515,0.00024585112],"about_ca_topic_score_codex":0.00012984051,"about_ca_topic_score_gemma":0.0011702174,"teacher_disagreement_score":0.99258244,"about_ca_system_score_codex":0.00006974862,"about_ca_system_score_gemma":0.00034173724,"threshold_uncertainty_score":0.9175574},"labels":[],"label_agreement":null},{"id":"W2031430497","doi":"10.1088/1367-2630/8/8/148","title":"Mean-field model of genetic regulatory networks","year":2006,"lang":"en","type":"article","venue":"New Journal of Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"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 Calgary","funders":"","keywords":"Boolean network; Boolean model; Set (abstract data type); Gene regulatory network; Nonlinear system; Bridge (graph theory); Stochastic process; Psychological repression; Stochastic modelling","score_opus":0.008067791248244248,"score_gpt":0.21569333902122922,"score_spread":0.20762554777298498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031430497","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":[0.7021052,0.002972945,0.29442987,0.00003740804,0.00009355336,0.000033731623,0.0000010393188,0.0000023003122,0.0003238998],"genre_scores_gemma":[0.99101466,0.00016217779,0.006348266,0.00008100139,0.0019339226,3.480228e-7,0.000004878805,0.000022697617,0.0004320501],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989488,0.000035051024,0.00045962702,0.0001354247,0.0002424285,0.00017866373],"domain_scores_gemma":[0.99888974,0.000010760262,0.00048520984,0.00031914454,0.00020709446,0.00008805088],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013039925,0.0001363963,0.00026199225,0.000036047382,0.0000296973,0.000009107672,0.00023828146,0.00012658993,0.0000072600083],"category_scores_gemma":[0.0000083139685,0.00012827448,0.000321156,0.00012488509,0.000040862946,0.000005583332,0.000049882277,0.000116283685,7.4727853e-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":[0.00004553718,0.000051210387,0.0023468656,0.0000062165877,0.00011448874,0.0000016367866,0.000010883759,0.7906574,0.18579829,0.0003237981,0.01254264,0.008101029],"study_design_scores_gemma":[0.0018749298,0.0008238683,0.0063743927,0.000077605575,0.00062381994,0.000059804508,0.000036809142,0.13991056,0.83260393,0.013685655,0.0033669288,0.0005616892],"about_ca_topic_score_codex":0.000014631224,"about_ca_topic_score_gemma":0.00001731029,"teacher_disagreement_score":0.6507468,"about_ca_system_score_codex":0.000013648447,"about_ca_system_score_gemma":0.00016817576,"threshold_uncertainty_score":0.52308816},"labels":[],"label_agreement":null},{"id":"W2031818149","doi":"10.1039/c0ib00145g","title":"Dynamic modeling and analysis of cancer cellular network motifs","year":2011,"lang":"en","type":"review","venue":"Integrative Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada; Biotechnology Research Institute","funders":"","keywords":"Library science; Research council; Operations research; Political science; Computer science; Engineering; Philosophy","score_opus":0.02499295488753712,"score_gpt":0.32005199565174675,"score_spread":0.29505904076420963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031818149","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002337706,0.98146236,0.01551104,0.0000024271158,0.00014939609,0.00023998796,0.00019151565,0.000008025554,0.00009754566],"genre_scores_gemma":[0.0077839023,0.9894148,0.00066788006,0.0000144424575,0.0001309994,0.000087065244,0.0016279612,0.000044824366,0.00022813106],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976059,0.00043520302,0.00071995286,0.00081973214,0.000055969198,0.0003632031],"domain_scores_gemma":[0.9985283,0.000036170462,0.00055794156,0.0005933172,0.0001940233,0.000090231726],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00025770362,0.00054015924,0.0023440754,0.00034520245,0.000057293975,0.000007766339,0.00036756205,0.00079370494,0.000073112475],"category_scores_gemma":[0.000034025103,0.00038739882,0.0010857435,0.0007943735,0.0002639801,0.0000017744305,0.0002316829,0.00023494168,0.0000025457152],"study_design_candidate":"design_other","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":[0.00004697432,0.0000805407,0.0014853748,0.0012347824,0.049992952,0.0000034167297,0.00012210253,0.0071810186,0.0012651517,0.0008803059,0.00019403525,0.93751335],"study_design_scores_gemma":[0.00023873706,0.00043061565,0.00004467144,0.0018300846,0.049586333,0.000006474431,0.00007047212,0.057009354,0.00019683766,0.00045904244,0.8886609,0.0014664668],"about_ca_topic_score_codex":0.00021247166,"about_ca_topic_score_gemma":0.0011207359,"teacher_disagreement_score":0.9360469,"about_ca_system_score_codex":0.000044124863,"about_ca_system_score_gemma":0.00017681786,"threshold_uncertainty_score":0.9998578},"labels":[],"label_agreement":null},{"id":"W2033117533","doi":"10.1016/j.biosystems.2009.09.002","title":"A multi-objective differential evolutionary approach toward more stable gene regulatory networks","year":2009,"lang":"en","type":"article","venue":"Biosystems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Attractor; Gene regulatory network; Stability (learning theory); Chaotic; Computer science; Maxima and minima; Boolean network; Convergence (economics); Biological network; Differential evolution; Property (philosophy); Mathematics; Mathematical optimization; Boolean function; Artificial intelligence; Biology; Gene; Genetics; Machine learning; Algorithm","score_opus":0.011427207142275821,"score_gpt":0.22371803847108834,"score_spread":0.21229083132881252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033117533","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":[0.9173622,0.0092866635,0.071769215,0.000058008824,0.00045505186,0.00055891695,0.00003422027,0.00008438411,0.00039131293],"genre_scores_gemma":[0.99332994,0.00009079349,0.0035106055,0.00008893805,0.0013515552,0.00003687803,0.00046224208,0.000037447116,0.0010915988],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9979613,0.00015299002,0.00037268203,0.0007285221,0.0002825412,0.0005020108],"domain_scores_gemma":[0.9987564,0.000004620791,0.00017457947,0.0007363547,0.00014404552,0.00018398376],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018119256,0.00032969678,0.0003676282,0.00008941521,0.00016600506,0.00003952721,0.00031167126,0.00037389342,0.000012028398],"category_scores_gemma":[0.000014085469,0.00031199056,0.00029573962,0.00025461623,0.00007914131,0.000007064645,0.00010317786,0.00012580835,0.000008233785],"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":[0.00022220553,0.0005837901,0.0059384154,0.00005601267,0.00065582024,0.000010995494,0.00017983805,0.02477351,0.95438594,0.000059970265,0.011379136,0.0017543822],"study_design_scores_gemma":[0.004478575,0.00092730735,0.43137774,0.000120857076,0.0006102341,0.00028116896,0.0010361539,0.37904212,0.16614094,0.00003617273,0.013249837,0.0026988864],"about_ca_topic_score_codex":0.000026910842,"about_ca_topic_score_gemma":0.0000038033936,"teacher_disagreement_score":0.78824496,"about_ca_system_score_codex":0.00008379844,"about_ca_system_score_gemma":0.00007870932,"threshold_uncertainty_score":0.99993324},"labels":[],"label_agreement":null},{"id":"W2033277681","doi":"10.1006/jtbi.2000.2255","title":"Resonance in Periodic Chemotherapy: A Case Study of Acute Myelogenous Leukemia","year":2001,"lang":"en","type":"article","venue":"Journal of Theoretical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":70,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Chemotherapy; Context (archaeology); Cell cycle; Leukemia; Bone marrow; Medicine; Cell; Magnetic resonance imaging; Cancer research; Biology; Internal medicine; Radiology; Biochemistry","score_opus":0.006626171558395219,"score_gpt":0.2635991707825153,"score_spread":0.2569729992241201,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033277681","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":[0.99776334,0.0014864347,0.00031990462,0.00013092617,0.00007772333,0.000107799235,0.0000029744324,0.000001818292,0.00010910728],"genre_scores_gemma":[0.998648,0.0006638421,0.00032908274,0.00012783993,0.00018445755,0.000002841238,0.0000025760587,0.000014589436,0.000026812198],"study_design_codex":"bench_or_experimental","study_design_gemma":"case_report","domain_scores_codex":[0.9985223,0.00031235954,0.0005979214,0.00021389149,0.00010016179,0.0002534057],"domain_scores_gemma":[0.99914044,0.00003515006,0.00028549976,0.0003086165,0.00014148165,0.00008878604],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005918191,0.00014886528,0.000446099,0.00012784077,0.000034841705,0.0000057796783,0.00027665045,0.00020239665,0.00007216],"category_scores_gemma":[0.00006485389,0.0001145127,0.00018286625,0.00022339926,0.00039885638,0.0000024385554,0.00007953923,0.00018164546,0.0000012451751],"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":[0.004292858,0.0018784718,0.31146595,0.00001820213,0.0019871583,0.008727117,0.0017187127,0.0008063506,0.6296217,0.0037701873,0.0003660538,0.035347242],"study_design_scores_gemma":[0.06357057,0.10996206,0.12628677,0.00035311613,0.0048864437,0.28982812,0.024695307,0.0047359676,0.27806106,0.047345664,0.045568846,0.004706054],"about_ca_topic_score_codex":0.00002262705,"about_ca_topic_score_gemma":0.000050213133,"teacher_disagreement_score":0.35156062,"about_ca_system_score_codex":0.00004445338,"about_ca_system_score_gemma":0.00011835101,"threshold_uncertainty_score":0.46696925},"labels":[],"label_agreement":null},{"id":"W2033637309","doi":"10.1371/journal.pcbi.1002669","title":"Criticality Is an Emergent Property of Genetic Networks that Exhibit Evolvability","year":2012,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":139,"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":"Alberta Innovates; Alberta Innovates - Technology Futures; Harvard University","keywords":"Evolvability; Gene regulatory network; Boolean network; Phenotype; Biology; Biological network; Evolutionary dynamics; Robustness (evolution); Epistasis; Fitness landscape; Population; Evolutionary biology; Genetics; Gene; Topology (electrical circuits); Computational biology; Computer science; Gene expression; Mathematics","score_opus":0.03516046851715237,"score_gpt":0.27761700509741427,"score_spread":0.2424565365802619,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033637309","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":[0.9694162,0.0014382655,0.028460313,0.00019644023,0.00012677349,0.00018456117,0.000033407257,0.0000147627625,0.00012927744],"genre_scores_gemma":[0.9930728,0.00003821887,0.0055796807,0.00041563518,0.00039227668,0.000022985023,0.00042191215,0.000017898006,0.000038573944],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99836355,0.00032204282,0.00037367598,0.000413631,0.00015074821,0.00037635674],"domain_scores_gemma":[0.99899596,0.00003613251,0.00011819065,0.00041096646,0.00024990502,0.00018883187],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002759081,0.00018261091,0.00026766694,0.00004097426,0.000074899894,0.0000059674758,0.00020905475,0.0002120417,0.00024299085],"category_scores_gemma":[0.000055097305,0.00014102673,0.00015441717,0.000117197145,0.00025003284,0.0000068215513,0.0001397765,0.00008071596,0.00001067588],"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":[0.00010019076,0.0009739024,0.90054953,0.000047944668,0.0004468753,4.3138215e-7,0.00008732798,0.046470795,0.0463295,0.00049903756,0.0012613746,0.0032331005],"study_design_scores_gemma":[0.0007183649,0.00074007444,0.78702253,0.000014963999,0.00028127123,0.000020982034,0.00006942831,0.16372849,0.037156604,0.003171936,0.006332039,0.0007432845],"about_ca_topic_score_codex":0.000019351206,"about_ca_topic_score_gemma":0.0000078242,"teacher_disagreement_score":0.1172577,"about_ca_system_score_codex":0.000020167614,"about_ca_system_score_gemma":0.000058613867,"threshold_uncertainty_score":0.5750903},"labels":[],"label_agreement":null},{"id":"W2034044469","doi":"10.1016/j.chaos.2012.02.018","title":"Explicit construction of chaotic attractors in Glass networks","year":2012,"lang":"en","type":"article","venue":"Chaos Solitons & Fractals","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Chaotic; Attractor; Limit (mathematics); Binary number; Topological conjugacy; Perturbation (astronomy); Mathematics; Statistical physics; Piecewise; Applied mathematics; Computer science; Topology (electrical circuits); Pure mathematics; Mathematical analysis; Physics; Artificial intelligence","score_opus":0.011480919075976094,"score_gpt":0.2456092544034238,"score_spread":0.2341283353274477,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034044469","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":[0.99422294,0.002677511,0.0019496602,0.000046946956,0.00039223954,0.00015950337,0.0000062773,0.0000120280665,0.0005328842],"genre_scores_gemma":[0.9983606,0.00024068994,0.00031221262,0.00005520749,0.00079289946,0.00002438448,0.00008218745,0.000030197918,0.000101629535],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985761,0.000097182405,0.0004069775,0.00027604876,0.00014718917,0.00049650035],"domain_scores_gemma":[0.9990635,0.000028110186,0.00021889913,0.00047336554,0.000064232365,0.00015189973],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031109707,0.00020125159,0.0003188759,0.0001163517,0.00004647685,0.000009314425,0.00016629043,0.00028023546,0.00006180119],"category_scores_gemma":[0.00005281448,0.00020643028,0.00017817713,0.00026842818,0.00011335057,0.000013137987,0.00008731867,0.00013431252,0.000010600126],"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":[0.00007594083,0.00036545232,0.6855977,0.00004741796,0.0002828379,0.0000026923526,0.00026233585,0.005056505,0.2994555,0.0006560095,0.00078313105,0.0074144755],"study_design_scores_gemma":[0.0017046765,0.00032022205,0.43193334,0.00013850631,0.00031955345,0.00012607916,0.001444708,0.006453364,0.53250194,0.00024675508,0.02342752,0.001383368],"about_ca_topic_score_codex":0.000033789507,"about_ca_topic_score_gemma":0.00003247094,"teacher_disagreement_score":0.25366437,"about_ca_system_score_codex":0.000034455054,"about_ca_system_score_gemma":0.000041502033,"threshold_uncertainty_score":0.84179825},"labels":[],"label_agreement":null},{"id":"W2034455925","doi":"10.1073/pnas.0711525105","title":"Gene expression dynamics in the macrophage exhibit criticality","year":2008,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":215,"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 Calgary","funders":"National Institute of General Medical Sciences; National Institutes of Health","keywords":"Criticality; Systems biology; Computational biology; Biology; Adaptability; Gene expression; Computer science; Dynamical systems theory; Biological system; Statistical physics; Gene; Physics; Genetics; Ecology","score_opus":0.025829584627370235,"score_gpt":0.28872273621734384,"score_spread":0.2628931515899736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034455925","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":[0.9966053,0.00024248107,0.0000052641644,0.001079084,0.000006050242,0.00007198511,0.000006275695,0.0000012778224,0.0019823161],"genre_scores_gemma":[0.99853456,0.000063162566,0.0009928048,0.0002476571,0.00006789231,0.0000053274966,4.862847e-7,0.0000023006296,0.00008581659],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99886245,0.000015185578,0.00020692575,0.0001915844,0.0006081005,0.00011576252],"domain_scores_gemma":[0.9996881,0.000023838144,0.00013227206,0.000013824418,0.00012403107,0.000017959788],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009730711,0.00006319975,0.00008557332,0.0000474604,0.00015206444,0.000006887437,0.00066551584,0.00007951356,0.0000047690264],"category_scores_gemma":[0.00022576391,0.00003680103,0.00007622511,0.0004093928,0.0007054723,0.000010929475,0.00013079861,0.000084967294,4.107396e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008241035,0.00004000909,0.026662394,0.000011979122,0.0000056170147,1.4670111e-8,0.00004561166,0.00024050202,0.96983945,0.0024687743,0.00061796163,0.00005941317],"study_design_scores_gemma":[0.00008838105,0.000023196808,0.09031581,0.000013873121,0.000006179947,0.000016858403,0.00013146456,0.0013671458,0.9032206,0.004667349,0.00009481048,0.000054360273],"about_ca_topic_score_codex":0.0000025886573,"about_ca_topic_score_gemma":2.455416e-7,"teacher_disagreement_score":0.06661892,"about_ca_system_score_codex":0.000017643339,"about_ca_system_score_gemma":0.000022286044,"threshold_uncertainty_score":0.25993422},"labels":[],"label_agreement":null},{"id":"W2034459017","doi":"10.1186/1471-2164-11-s4-s18","title":"Functional data analysis for identifying nonlinear models of gene regulatory networks","year":2010,"lang":"en","type":"article","venue":"BMC Genomics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; Ottawa Hospital","funders":"Ontario Ministry of Research and Innovation; Ottawa Hospital Research Institute","keywords":"Overfitting; Gene regulatory network; Computer science; Inference; Linear model; Nonlinear system; Systems biology; Artificial intelligence; Machine learning; Data mining; Biology; Computational biology; Artificial neural network","score_opus":0.04900497916572371,"score_gpt":0.2685729243578686,"score_spread":0.2195679451921449,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034459017","genre_codex":"methods","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":[0.47449294,0.00048571939,0.52460605,0.0000058921974,0.00016809843,0.00010583797,0.00010959027,0.0000058874125,0.000020006808],"genre_scores_gemma":[0.8696757,0.00005859594,0.12494207,0.00003564873,0.0009462508,0.000013273086,0.0040142164,0.000036898957,0.00027734644],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985373,0.00003316182,0.00040766766,0.00061332516,0.00014887896,0.000259664],"domain_scores_gemma":[0.997686,0.000024990542,0.00024231049,0.0017621842,0.00018761013,0.00009686593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005648467,0.00017602475,0.00030141175,0.00012704032,0.00010189551,0.000024766692,0.000566259,0.00024086758,0.000021426466],"category_scores_gemma":[0.00003650579,0.00019224321,0.0003556939,0.00027670423,0.000087250046,0.000009074951,0.0002887281,0.00009798379,0.0000016451864],"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":[0.00007033904,0.00003879653,0.0043140803,0.000012149107,0.0008968903,1.492906e-7,0.000008059133,0.55294514,0.44033533,0.00008562367,0.0007094336,0.00058402674],"study_design_scores_gemma":[0.00041874853,0.000027008948,0.0072673946,0.0000017537118,0.0012209376,0.0000038176613,0.000029139674,0.91549325,0.073107965,0.0001967781,0.0019742022,0.00025900797],"about_ca_topic_score_codex":0.000011716753,"about_ca_topic_score_gemma":0.0007245225,"teacher_disagreement_score":0.39966395,"about_ca_system_score_codex":0.000012716131,"about_ca_system_score_gemma":0.0001504976,"threshold_uncertainty_score":0.7839451},"labels":[],"label_agreement":null},{"id":"W2034960511","doi":"10.1103/physreve.77.041903","title":"Optimizing the readout of morphogen gradients","year":2008,"lang":"en","type":"article","venue":"Physical Review E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Morphogen; Context (archaeology); Multicellular organism; Computer science; Biological system; Biology; Gene; Genetics","score_opus":0.01843625060073492,"score_gpt":0.2735067647057043,"score_spread":0.2550705141049694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034960511","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":[0.93918115,0.059279248,0.00019804598,0.00018423948,0.000027337968,0.00016406375,0.0000033983508,0.0000047745493,0.00095775054],"genre_scores_gemma":[0.97505903,0.024064204,0.00020201718,0.0003097018,0.00016779207,0.000013668621,0.000021303655,0.000010403122,0.0001518803],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99935836,0.00006554769,0.00015053233,0.00016936309,0.00012981312,0.00012636361],"domain_scores_gemma":[0.9993704,0.0000101253845,0.00009003262,0.00043349335,0.00005325687,0.00004267299],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009772543,0.00009146647,0.0002157825,0.000007302842,0.00005253594,0.0000015973228,0.00020146457,0.000017836273,0.000009384799],"category_scores_gemma":[0.000042959917,0.000058932914,0.00024983057,0.00013610662,0.000095567266,0.0000011989365,0.00007799793,0.000043408592,0.00001754595],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040804116,0.00050812965,0.0051744636,0.0007809395,0.0008528878,0.000010943225,0.00025063579,0.0017167852,0.9328965,0.00085160707,0.037623033,0.01929325],"study_design_scores_gemma":[0.0009940718,0.0006010727,0.014121206,0.0012642532,0.0015039713,0.0001218943,0.00003916729,0.0025586693,0.5432347,0.00092836714,0.43348163,0.0011509547],"about_ca_topic_score_codex":0.000004663858,"about_ca_topic_score_gemma":0.0000010725283,"teacher_disagreement_score":0.39585862,"about_ca_system_score_codex":0.0000042346055,"about_ca_system_score_gemma":0.00002072618,"threshold_uncertainty_score":0.24032144},"labels":[],"label_agreement":null},{"id":"W2036036019","doi":"10.1103/physreve.82.022105","title":"Phase transition in a class of nonlinear random networks","year":2010,"lang":"en","type":"article","venue":"Physical Review E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"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 Calgary","funders":"","keywords":"Transition (genetics); Nonlinear system; Class (philosophy); Phase transition; Statistical physics; Mathematics; Computer science; Physics; Condensed matter physics; Artificial intelligence; Chemistry; Quantum mechanics","score_opus":0.007358627351038427,"score_gpt":0.2909999692797177,"score_spread":0.2836413419286793,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2036036019","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":[0.9892252,0.008387396,0.0017924241,0.00017056063,0.000039511284,0.00020142201,0.000004688619,0.000003705803,0.00017510576],"genre_scores_gemma":[0.99400175,0.0050635966,0.00019041204,0.00025096445,0.00035934715,0.0000199663,0.00009360477,0.000010601805,0.000009789162],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931145,0.00006821129,0.000214276,0.00018913303,0.00008654846,0.00013039054],"domain_scores_gemma":[0.9995367,0.000013897595,0.00007266722,0.00028036378,0.000044612123,0.00005177227],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019592923,0.00009845417,0.00031532114,0.00001636449,0.00001176567,0.0000025864765,0.00010290901,0.000049481714,0.000016222764],"category_scores_gemma":[0.00004003119,0.000084554886,0.00022995533,0.00017639778,0.000050879935,0.0000019239096,0.000019459078,0.0001234242,0.000003818093],"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":[0.00015238255,0.0010762614,0.00010371512,0.00033537784,0.0000808258,0.0000023938833,0.00002008412,0.0015451679,0.95135945,0.00012685343,0.0007014151,0.0444961],"study_design_scores_gemma":[0.021626743,0.0016619638,0.0010651631,0.0018377933,0.0013519216,0.000024869103,0.000019646879,0.44272977,0.34843674,0.0009421066,0.17885539,0.0014478943],"about_ca_topic_score_codex":0.0000037373698,"about_ca_topic_score_gemma":0.000031421565,"teacher_disagreement_score":0.6029227,"about_ca_system_score_codex":0.0000025491374,"about_ca_system_score_gemma":0.000021235539,"threshold_uncertainty_score":0.34480482},"labels":[],"label_agreement":null},{"id":"W2037697963","doi":"10.1007/s12038-007-0099-8","title":"The next step in biology: A periodic table?","year":2007,"lang":"en","type":"review","venue":"Journal of Biosciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"RIKEN; University of Nottingham; Canada's Michael Smith Genome Sciences Centre","keywords":"Component (thermodynamics); Table (database); Systems biology; Periodic table; Synthetic biology; Modular design; Biology; Key (lock); Computer science; Computational biology; Biological system; Theoretical computer science; Physics; Ecology; Data mining","score_opus":0.04301426483224627,"score_gpt":0.34806033092965666,"score_spread":0.30504606609741036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2037697963","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008979003,0.99818075,0.00010825416,0.000048285405,0.0005173112,0.00010222135,0.0000032071432,0.000001170859,0.00014087369],"genre_scores_gemma":[0.0010675087,0.99787825,0.00025238213,0.0000408147,0.0005320869,0.0000028599934,0.000004497538,0.000011371999,0.0002102373],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980266,0.00023976027,0.0008566763,0.00027012845,0.00024346786,0.00036332916],"domain_scores_gemma":[0.9984224,0.00007388282,0.0009891599,0.0003024015,0.000112296315,0.00009985771],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002311314,0.00022878611,0.0007428505,0.00026696944,0.00016632509,0.000109123044,0.0010206205,0.00029595845,0.000008177131],"category_scores_gemma":[0.00016809301,0.0001205901,0.000511262,0.00084076356,0.0004664932,0.000006289992,0.00012850732,0.00027620947,0.0000039482024],"study_design_candidate":"not_applicable","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":[0.0000067887827,0.000023733783,0.0002062691,0.00013513496,0.000101203615,0.000009603075,0.000007563214,0.000008145798,0.0002538758,0.000016619526,0.0011592368,0.99807185],"study_design_scores_gemma":[0.000069968075,0.00018144501,0.000033697794,0.0004981889,0.00013242058,0.00013388033,0.00007969395,0.000009664974,0.000023424196,0.00001651528,0.9986796,0.0001414935],"about_ca_topic_score_codex":0.0000055465903,"about_ca_topic_score_gemma":0.00011765362,"teacher_disagreement_score":0.99793035,"about_ca_system_score_codex":0.000047028414,"about_ca_system_score_gemma":0.00078848534,"threshold_uncertainty_score":0.49175215},"labels":[],"label_agreement":null},{"id":"W2038085598","doi":"10.1007/s00216-012-6328-5","title":"High-throughput quantitative analysis with cell growth kinetic curves for low copy number mutant cells","year":2012,"lang":"en","type":"article","venue":"Analytical and Bioanalytical Chemistry","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Institute for Nanotechnology; Alberta Health; University of Alberta","funders":"","keywords":"Mutant; Mutagen; Cell growth; Hypoxanthine-guanine phosphoribosyltransferase; Mutagenesis; Chemistry; Cell; Hypoxanthine; Molecular biology; Mutation; Biology; Genetics; Biochemistry; Gene; DNA; Enzyme","score_opus":0.007826467855218483,"score_gpt":0.2426398447241767,"score_spread":0.23481337686895823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038085598","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":[0.9799481,0.0020857821,0.015028455,0.0006528991,0.00004619852,0.00030261884,0.00015621111,0.00003574061,0.0017439752],"genre_scores_gemma":[0.9928876,0.000644828,0.003561461,0.00044456357,0.00042191494,0.000030103163,0.00039456948,0.000043375963,0.0015715924],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99737865,0.00005808162,0.0005104655,0.0008353928,0.0003837247,0.0008336842],"domain_scores_gemma":[0.9982221,0.00013388606,0.00016536379,0.00053446984,0.0003085199,0.00063566794],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003438752,0.00047691548,0.0007808471,0.000058430698,0.0001342545,0.00005477774,0.00025491396,0.0003075544,0.00032497104],"category_scores_gemma":[0.00009902894,0.00036602825,0.00051519135,0.0008682618,0.0005530435,0.00001602294,0.00014372202,0.00018694335,0.000023119783],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002201585,0.003836409,0.2711672,0.0043749455,0.024508081,0.000057338257,0.00011300474,0.0015271906,0.6651913,0.0046475385,0.021904288,0.0004711532],"study_design_scores_gemma":[0.0016709858,0.00039354243,0.0027900909,0.000096455886,0.013218132,0.00003362665,0.00017860341,0.012772835,0.9632028,0.00020466727,0.0040213102,0.0014169613],"about_ca_topic_score_codex":0.000038432372,"about_ca_topic_score_gemma":0.000012332288,"teacher_disagreement_score":0.29801154,"about_ca_system_score_codex":0.00003187884,"about_ca_system_score_gemma":0.00006808008,"threshold_uncertainty_score":0.9998792},"labels":[],"label_agreement":null},{"id":"W2038186289","doi":"10.1038/nmeth895","title":"A comprehensive library of fluorescent transcriptional reporters for Escherichia coli","year":2006,"lang":"en","type":"article","venue":"Nature Methods","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":813,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Promoter; Operon; Escherichia coli; Biology; Transcription (linguistics); Plasmid; Computational biology; lac operon; Genomic library; Genetics; Gene; Gene expression; Base sequence","score_opus":0.011319831906374613,"score_gpt":0.3048933324768018,"score_spread":0.2935735005704272,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038186289","genre_codex":"empirical","genre_gemma":"methods","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":[0.8156592,0.016851215,0.16526929,0.00035786,0.000472705,0.0004348264,0.00006600215,0.000027503413,0.00086137006],"genre_scores_gemma":[0.49215326,0.000044407752,0.5059451,0.0002927892,0.00039798443,0.000024950237,0.00040736143,0.000027805836,0.0007063492],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989637,0.00016909764,0.00028406797,0.00030175736,0.000115527415,0.00016581117],"domain_scores_gemma":[0.9993685,0.000034607994,0.00014400456,0.00029367313,0.00011544175,0.000043763383],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000201702,0.00013762127,0.00022843102,0.000049211914,0.000040586106,0.000009101209,0.00013532286,0.00034658343,0.000019573137],"category_scores_gemma":[0.000026117661,0.00012914205,0.00030058852,0.00016129478,0.00006885175,0.0000032548487,0.000030752228,0.00012937513,2.3380731e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012363275,0.000051348456,0.0010515013,0.000042499687,0.00013929614,0.0000011005341,0.0000062212675,0.00053267897,0.9848823,0.00052049744,0.010512829,0.002136121],"study_design_scores_gemma":[0.00038146225,0.00008071118,0.018646868,0.000007035813,0.00009003878,0.0000048707784,0.000013795522,0.00039123412,0.71135867,0.00065938744,0.26822686,0.00013905695],"about_ca_topic_score_codex":0.0000042363185,"about_ca_topic_score_gemma":0.0000027389137,"teacher_disagreement_score":0.3406758,"about_ca_system_score_codex":0.0000067432984,"about_ca_system_score_gemma":0.00006925231,"threshold_uncertainty_score":0.526626},"labels":[],"label_agreement":null},{"id":"W2038601384","doi":"10.4236/am.2013.41a038","title":"Simplifying Stochastic Mathematical Models of Biochemical Systems","year":2013,"lang":"en","type":"article","venue":"Applied Mathematics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Stochastic dynamics; Stochastic modelling; Stochastic process; Computer science; Statistical physics; Biological system; Mathematical model; Mathematics; Physics; Biology; Statistics","score_opus":0.0146904184330302,"score_gpt":0.22431764411496147,"score_spread":0.20962722568193126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038601384","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":[0.5203516,0.00032583464,0.47523436,0.000015686694,0.000029205528,0.0005047307,0.000004541159,0.000026145139,0.0035079266],"genre_scores_gemma":[0.9745792,0.000010137364,0.024916288,0.000022497601,0.00010304881,0.00013940316,0.000029391162,0.000046917543,0.00015310729],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99859494,0.000012565584,0.0005362631,0.00029201197,0.00026461697,0.00029961584],"domain_scores_gemma":[0.99883693,0.000048326587,0.0002157515,0.0006655616,0.00011228189,0.000121137055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018441326,0.00022135567,0.000400967,0.00005647316,0.000042649055,0.000028850021,0.00028111166,0.00019906742,0.000048086506],"category_scores_gemma":[0.00003620312,0.00019644004,0.00013091047,0.00013902181,0.00011141179,0.0000039065344,0.00016175816,0.00007795259,0.0000901858],"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":[0.000008017022,0.00024922023,0.0000048826937,0.0005228491,0.00027131638,3.6642874e-7,0.00017553502,0.04315425,0.9069587,0.045076396,0.0032959802,0.00028249872],"study_design_scores_gemma":[0.0011590725,0.00014791524,0.000020149582,0.00020930114,0.00051167695,0.0000764196,0.001977036,0.6020891,0.23928116,0.15317795,0.00016755189,0.0011826882],"about_ca_topic_score_codex":0.0000033036997,"about_ca_topic_score_gemma":2.1602978e-7,"teacher_disagreement_score":0.6676775,"about_ca_system_score_codex":0.000013740265,"about_ca_system_score_gemma":0.000032532123,"threshold_uncertainty_score":0.80105925},"labels":[],"label_agreement":null},{"id":"W2039294433","doi":"10.1063/1.2213613","title":"Noise in genetic and neural networks","year":2006,"lang":"en","type":"article","venue":"Chaos An Interdisciplinary Journal of Nonlinear Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":53,"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 Ottawa; McGill University","funders":"","keywords":"Computer science; Artificial neural network; Bridging (networking); Noise (video); Focus (optics); Field (mathematics); Reading (process); Artificial intelligence; Cognitive science; Data science; Theoretical computer science; Machine learning; Mathematics; Psychology; Linguistics; Physics; Computer security","score_opus":0.007481219593950418,"score_gpt":0.27629256118473244,"score_spread":0.268811341590782,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039294433","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":[0.99509454,0.0014111326,0.003076938,0.00013054612,0.00017979594,0.000048901766,0.0000012744036,0.0000022970096,0.00005457702],"genre_scores_gemma":[0.99585986,0.000056663943,0.0032151628,0.000036896367,0.0007702723,9.5024143e-7,0.0000037216873,0.000011820057,0.00004464774],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99874866,0.000049042832,0.00041615547,0.0002876969,0.00021814367,0.00028030536],"domain_scores_gemma":[0.99922395,0.0000072015514,0.00020865518,0.00025231615,0.000162514,0.00014538813],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053915754,0.00013287357,0.0001876535,0.00021990227,0.0001557061,0.000062124775,0.00044030705,0.000064922606,0.000006962187],"category_scores_gemma":[0.000013744447,0.00011265907,0.000084120045,0.00036949452,0.00043367414,0.000029498113,0.00042701824,0.0001425171,5.3869934e-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":[0.00031038973,0.0004600642,0.15461448,0.000017940105,0.000035530004,0.00023436866,0.00033205043,0.4395688,0.3830208,0.000023579563,0.00034421944,0.021037808],"study_design_scores_gemma":[0.0007435575,0.0011138428,0.32043725,0.000047942853,0.000034514356,0.0010322824,0.00033980387,0.6684049,0.007092333,0.00025944615,0.00017387289,0.00032027115],"about_ca_topic_score_codex":0.000005644096,"about_ca_topic_score_gemma":0.00008111604,"teacher_disagreement_score":0.37592846,"about_ca_system_score_codex":0.000025625524,"about_ca_system_score_gemma":0.000082147286,"threshold_uncertainty_score":0.45941037},"labels":[],"label_agreement":null},{"id":"W2040121180","doi":"10.1038/ncomms7753","title":"Transcriptional refractoriness is dependent on core promoter architecture","year":2015,"lang":"en","type":"article","venue":"Nature Communications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":37,"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":"Fonds de Recherche du Québec - Santé; Deutsche Forschungsgemeinschaft","keywords":"Promoter; RNA polymerase II; Transcription (linguistics); Biology; Transcriptional regulation; RNA polymerase; Gene; Transcription factor; Population; Genetics; RNA; Gene expression; Medicine","score_opus":0.03632421604675666,"score_gpt":0.30773715501104026,"score_spread":0.2714129389642836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040121180","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":[0.9511906,0.01945478,0.0015776344,0.015981361,0.0005474506,0.0005522678,0.0001572558,0.00007545677,0.0104632005],"genre_scores_gemma":[0.99410075,0.00015588068,0.0025649546,0.0011414777,0.00022483603,0.00003342785,0.0005742904,0.000020776964,0.0011835943],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991441,0.00008753369,0.00014703143,0.0002491532,0.00022574322,0.00014645192],"domain_scores_gemma":[0.99781966,0.000013755345,0.00006271991,0.0017748818,0.0002145494,0.00011441377],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016430333,0.00013783445,0.000109851215,0.00005569695,0.0001160634,0.000019296851,0.00076621317,0.00033135377,0.000017889744],"category_scores_gemma":[0.00005441361,0.00012279984,0.00010709292,0.00015493884,0.00007519446,0.000002652662,0.00015671537,0.0004967028,0.000021800703],"study_design_candidate":"not_applicable","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":[0.00074949797,0.0022561299,0.04155027,0.00004954791,0.0016865559,0.000010140616,0.0020960444,0.0053566284,0.6537074,0.017643847,0.24866825,0.026225697],"study_design_scores_gemma":[0.00059468555,0.00015536448,0.008449526,0.000015135999,0.000076890734,0.000024938361,0.00006304116,0.00022736767,0.01638868,0.00082766596,0.97288346,0.0002932345],"about_ca_topic_score_codex":0.0000045381203,"about_ca_topic_score_gemma":0.0001988397,"teacher_disagreement_score":0.7242152,"about_ca_system_score_codex":0.00003206358,"about_ca_system_score_gemma":0.0000925573,"threshold_uncertainty_score":0.50076324},"labels":[],"label_agreement":null},{"id":"W2041333537","doi":"10.1155/2014/693938","title":"Conception of Biologic System: Basis Functional Elements and Metric Properties","year":2014,"lang":"en","type":"article","venue":"Journal of Complex Systems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Joint Attosecond Science Laboratory","funders":"","keywords":"Reciprocal; Basis (linear algebra); Functional analysis; Metric (unit); Algebra over a field; Space (punctuation); Metric space; Group (periodic table)","score_opus":0.03174073717179794,"score_gpt":0.23004255748966032,"score_spread":0.19830182031786237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041333537","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":[0.9876814,0.0034225236,0.008362706,0.000016181044,0.0002670179,0.0000877312,0.0000032406206,0.000003034491,0.0001561798],"genre_scores_gemma":[0.9990278,0.000059688107,0.0002475111,0.000012499393,0.00053655193,0.0000028412605,0.0000088224115,0.000007662455,0.00009666016],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9987285,0.00024610653,0.00058337004,0.000117471995,0.0002159202,0.00010863759],"domain_scores_gemma":[0.9987573,0.000014018889,0.0006804008,0.00014142736,0.000347389,0.000059454593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007232828,0.00010032294,0.0003224936,0.00013931729,0.000048040343,0.000017523505,0.00010590121,0.00007283596,0.0000077001805],"category_scores_gemma":[0.000051788888,0.00007145747,0.00011704429,0.00013471166,0.00006413901,0.000004741813,0.000037567912,0.0000428265,0.0000014961397],"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":[0.00012749418,0.00004684912,0.07185567,0.0002924162,0.0005521153,8.1633283e-7,0.000023157729,0.0065197363,0.9164358,0.0003088006,0.0026541515,0.0011830393],"study_design_scores_gemma":[0.009260973,0.008710271,0.62541807,0.0013616361,0.0019630622,0.0021087117,0.0050937575,0.07792485,0.10667804,0.000091585935,0.1597634,0.0016256876],"about_ca_topic_score_codex":0.000011725591,"about_ca_topic_score_gemma":0.000003740764,"teacher_disagreement_score":0.8097577,"about_ca_system_score_codex":0.000023092096,"about_ca_system_score_gemma":0.000028390956,"threshold_uncertainty_score":0.29139513},"labels":[],"label_agreement":null},{"id":"W2042639771","doi":"10.1049/sb:20045005","title":"Autonomously oscillating biochemical systems: parametric sensitivity of extrema and period","year":2004,"lang":"en","type":"article","venue":"Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Sensitivity (control systems); Context (archaeology); Maxima and minima; Parametric statistics; Control theory (sociology); Steady state (chemistry); Period (music); Work (physics); Biological system; Computer science; Mathematics; Physics; Engineering; Statistics; Mathematical analysis; Artificial intelligence; Biology; Chemistry; Electronic engineering; Acoustics; Thermodynamics","score_opus":0.009826348288303335,"score_gpt":0.233289165153774,"score_spread":0.22346281686547065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042639771","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":[0.984499,0.010561578,0.0042356653,0.000034228775,0.0002598736,0.0002311797,0.00001891496,0.000019632493,0.0001399759],"genre_scores_gemma":[0.99922526,0.00007892691,0.00024592545,0.000011078464,0.00028324276,0.000015639756,0.000060750015,0.000020074847,0.000059090748],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983434,0.00030856673,0.00044235884,0.00050707697,0.00008750864,0.00031107207],"domain_scores_gemma":[0.9990608,0.000037755137,0.00025857205,0.00041468313,0.0001247738,0.00010343308],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006192268,0.0002083723,0.00047209623,0.00012855376,0.00007113073,0.000019477433,0.000096867116,0.00036806762,0.0000013424575],"category_scores_gemma":[0.00016433121,0.00018811817,0.00011251965,0.00025240026,0.00022900148,0.0000025947013,0.00012979025,0.00007825246,0.000004021559],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021366812,0.000034129618,0.025990438,0.00012984383,0.00020489698,0.000006800495,0.000042795025,0.011005088,0.9614499,0.00075305405,0.0000635689,0.00029806868],"study_design_scores_gemma":[0.012479027,0.005431041,0.062412575,0.0012155982,0.0014720863,0.008756083,0.00663449,0.10023512,0.7572479,0.00071911776,0.036795817,0.006601114],"about_ca_topic_score_codex":0.00042053527,"about_ca_topic_score_gemma":0.000023255618,"teacher_disagreement_score":0.20420201,"about_ca_system_score_codex":0.00004017698,"about_ca_system_score_gemma":0.00009596177,"threshold_uncertainty_score":0.76712364},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.006906055701127504,"score_gpt":0.21960796050864112,"score_spread":0.2127019048075136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043393386","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":[0.9882455,0.0012473218,0.008950195,0.00003471579,0.00083367934,0.00039172883,0.000007912785,0.000012412878,0.00027655656],"genre_scores_gemma":[0.9978909,0.000026917212,0.00098617,0.000037845475,0.00080524525,0.000052707277,0.00012256765,0.000009612075,0.00006802011],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9988652,0.00022178679,0.00048509342,0.00015632587,0.00008489083,0.00018672638],"domain_scores_gemma":[0.99879134,0.000025115556,0.0004540193,0.0005170418,0.00017301815,0.000039452236],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055434165,0.00013259225,0.00020022196,0.00003085036,0.00008768932,0.000021473552,0.00027261404,0.0002358806,0.000009592321],"category_scores_gemma":[0.00009566223,0.00008822729,0.00009505743,0.00016047555,0.00013228094,0.000005564025,0.000075691,0.00009153723,0.000018023631],"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":[0.00008429902,0.000029401033,0.33629727,0.00019022552,0.00026980945,1.8546639e-7,0.00016535548,0.035505533,0.6134305,0.008144973,0.003041334,0.002841098],"study_design_scores_gemma":[0.0034113703,0.002020154,0.4507625,0.00020938393,0.0008157226,0.0005093021,0.0019860242,0.065068506,0.1785388,0.0022816043,0.29203817,0.0023584515],"about_ca_topic_score_codex":0.00005952697,"about_ca_topic_score_gemma":0.00017931861,"teacher_disagreement_score":0.43489173,"about_ca_system_score_codex":0.000006017856,"about_ca_system_score_gemma":0.00010205385,"threshold_uncertainty_score":0.35978043},"labels":[],"label_agreement":null},{"id":"W2043460027","doi":"10.1038/msb.2010.108","title":"A comprehensive map of the mTOR signaling network","year":2010,"lang":"en","type":"review","venue":"Molecular Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":244,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Institute for Research in Immunology and Cancer","funders":"","keywords":"SBML; PI3K/AKT/mTOR pathway; Systems biology; Biology; Computational biology; Regulator; Computer science; Markup language; Signal transduction; Bioinformatics; XML; World Wide Web; Cell biology; Genetics","score_opus":0.018369209449593384,"score_gpt":0.27597221408531547,"score_spread":0.2576030046357221,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043460027","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008144322,0.99443096,0.0015970386,0.000016170552,0.002012007,0.0009673766,0.000061397805,0.00001418407,0.00008645592],"genre_scores_gemma":[0.0053563872,0.9907126,0.00046942188,0.0000851049,0.0018515339,0.00023025382,0.00065025967,0.0001663404,0.00047813496],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99608225,0.0013285454,0.0010321874,0.00081798725,0.00017746759,0.0005615933],"domain_scores_gemma":[0.99646586,0.00004973457,0.0011176442,0.0020352756,0.00022446003,0.00010704278],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0003686014,0.000627355,0.0020030478,0.00009183617,0.000118882184,0.000022558748,0.0013717987,0.0015452282,0.000011750964],"category_scores_gemma":[0.00005542423,0.00042781272,0.001549139,0.00032946913,0.00031555485,0.0000010196832,0.00083692395,0.00048897427,0.000028324825],"study_design_candidate":"not_applicable","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":[0.00008566615,0.0003234516,0.0007481347,0.05080302,0.017178228,0.00009330753,0.000050679253,0.0070419004,0.2989649,0.0035463108,0.02890535,0.59225905],"study_design_scores_gemma":[0.00011837733,0.00007961842,0.0000017250571,0.0012307084,0.0008624281,0.000077684446,0.0000042904126,0.00002860181,0.0006644894,0.00002847731,0.9964961,0.0004075333],"about_ca_topic_score_codex":0.000029228255,"about_ca_topic_score_gemma":0.000010767325,"teacher_disagreement_score":0.9675907,"about_ca_system_score_codex":0.00002812949,"about_ca_system_score_gemma":0.00031743635,"threshold_uncertainty_score":0.9998174},"labels":[],"label_agreement":null},{"id":"W2043897351","doi":"10.1016/j.jtbi.2004.03.011","title":"Intrinsic and external noise in an auto-regulatory genetic network","year":2004,"lang":"en","type":"article","venue":"Journal of Theoretical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Negative feedback; Positive feedback; Noise (video); Physics; Messenger RNA; Fano factor; Control theory (sociology); Biological system; Statistical physics; Biology; Gene; Computer science; Genetics; Control (management); Quantum mechanics; Shot noise; Engineering; Optics","score_opus":0.0044680307681030955,"score_gpt":0.23705296841900134,"score_spread":0.23258493765089824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043897351","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":[0.98969394,0.0039274497,0.005836889,0.00023610967,0.00019090218,0.00006246422,0.0000013794463,0.0000035769485,0.000047274374],"genre_scores_gemma":[0.9926362,0.00033920482,0.005809141,0.00025588137,0.00092953304,0.000001831531,0.0000042393035,0.000018095227,0.00000584839],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9985094,0.0002552976,0.0005177902,0.00026580377,0.00010514878,0.00034657784],"domain_scores_gemma":[0.99915725,0.000025847501,0.00020785334,0.000279412,0.000109618384,0.0002200039],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057867175,0.00017422368,0.00034862667,0.000107932625,0.000042011536,0.000017955912,0.0002749791,0.0002656512,0.000039089573],"category_scores_gemma":[0.00008713662,0.00014110997,0.00013718977,0.00013012705,0.0006347947,0.0000059481413,0.000124683,0.0002143483,0.000002805149],"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":[0.00091854343,0.00030932424,0.20251673,0.000017994345,0.00024043338,0.00013104579,0.00007339495,0.015426139,0.6480025,0.101063155,0.00010498405,0.031195737],"study_design_scores_gemma":[0.004452923,0.004454379,0.61427885,0.0001207728,0.00024823597,0.0014628638,0.00006319164,0.0006328962,0.026273772,0.34570792,0.0015808431,0.0007233224],"about_ca_topic_score_codex":0.000002488317,"about_ca_topic_score_gemma":0.000015464411,"teacher_disagreement_score":0.6217287,"about_ca_system_score_codex":0.00003410729,"about_ca_system_score_gemma":0.000105168656,"threshold_uncertainty_score":0.57542974},"labels":[],"label_agreement":null},{"id":"W2044607144","doi":"10.1007/s00285-010-0343-y","title":"Control design for sustained oscillation in a two-gene regulatory network","year":2010,"lang":"en","type":"article","venue":"Journal of Mathematical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Gene regulatory network; Oscillation (cell signaling); Control theory (sociology); Control (management); Biology; Gene; Mathematics; Computer science; Genetics; Gene expression; Artificial intelligence","score_opus":0.010302214597994328,"score_gpt":0.27187126763725117,"score_spread":0.2615690530392568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044607144","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":[0.67242473,0.0002002379,0.32670853,0.00021687018,0.00016925266,0.00022277868,0.000002257183,0.0000031143447,0.00005222963],"genre_scores_gemma":[0.952609,0.000010483049,0.0462074,0.00012263386,0.00096571364,0.0000124172675,0.0000082667275,0.000017479628,0.000046633133],"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985875,0.00019386459,0.00063368736,0.0001797212,0.00009281242,0.0003124006],"domain_scores_gemma":[0.99880546,0.00022234202,0.000372815,0.00025014684,0.00024425815,0.00010497913],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019622797,0.00014392627,0.0004128734,0.00009299582,0.00004310368,0.000010937392,0.00020473846,0.00021277748,0.00003158483],"category_scores_gemma":[0.0006227675,0.00011319851,0.00022452917,0.00011653745,0.000108781125,0.0000042014026,0.00003136601,0.00016854324,0.0000026447374],"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":[0.0005418451,0.000104143575,0.0028663871,0.000017831775,0.00018329246,0.000004799922,0.000019149365,0.009600361,0.9768949,0.007580862,0.00094196876,0.0012444331],"study_design_scores_gemma":[0.025311548,0.005310974,0.0109751485,0.00015744827,0.0010672293,0.0012203862,0.00023283459,0.082971394,0.29988664,0.5580153,0.013100852,0.0017502556],"about_ca_topic_score_codex":4.0978063e-7,"about_ca_topic_score_gemma":0.000009888092,"teacher_disagreement_score":0.6770083,"about_ca_system_score_codex":0.000017941384,"about_ca_system_score_gemma":0.00011465027,"threshold_uncertainty_score":0.46161014},"labels":[],"label_agreement":null},{"id":"W2044890688","doi":"10.1073/pnas.0506771102","title":"Eukaryotic cells are dynamically ordered or critical but not chaotic","year":2005,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":247,"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 Calgary","funders":"National Institute of General Medical Sciences; National Institutes of Health; National Science Foundation","keywords":"Chaotic; Robustness (evolution); Nonlinear system; Boolean network; Statistical physics; Boolean function; Gene regulatory network; Stability (learning theory); Computer science; Systems biology; Biological system; Biology; Gene; Physics; Computational biology; Genetics; Gene expression; Artificial intelligence; Algorithm","score_opus":0.0240136028128596,"score_gpt":0.2904882310983985,"score_spread":0.2664746282855389,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044890688","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":[0.99431026,0.00014784053,0.000009416406,0.0047329003,0.00001605416,0.00008625166,0.000011920566,0.00000493644,0.00068044494],"genre_scores_gemma":[0.9957432,0.000036671525,0.0028648467,0.0005606824,0.00020049805,0.0000045784996,2.8720967e-7,0.0000056277486,0.0005835811],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985264,0.000008628317,0.0002887148,0.0002915448,0.00069951935,0.00018519221],"domain_scores_gemma":[0.9993542,0.000044881417,0.00022881244,0.000014609907,0.00030636802,0.000051173844],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005733579,0.0001027254,0.00015140437,0.00007602789,0.00013446383,0.000017788576,0.00068046816,0.00011918396,0.000026422278],"category_scores_gemma":[0.0005651493,0.000067559864,0.00011023248,0.00039975793,0.0007795288,0.00001736851,0.00017168335,0.000091413436,0.0000029514683],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030498606,0.00005387951,0.0022047255,0.00003793282,0.00002758614,7.6676e-9,0.000013200595,0.0012486731,0.9934254,0.0018588093,0.00085754733,0.00024171795],"study_design_scores_gemma":[0.00014613899,0.00006642057,0.029259382,0.000038920163,0.000036583315,0.000010407471,0.000090408066,0.007382131,0.961138,0.0013882006,0.00032646037,0.00011691403],"about_ca_topic_score_codex":0.0000011307263,"about_ca_topic_score_gemma":5.1411376e-7,"teacher_disagreement_score":0.03228739,"about_ca_system_score_codex":0.000018627308,"about_ca_system_score_gemma":0.000049062568,"threshold_uncertainty_score":0.28722066},"labels":[],"label_agreement":null},{"id":"W2045327901","doi":"10.1111/j.1749-6632.2002.tb04722.x","title":"Topological Studies of the Rat Brain K<sup>+</sup>‐Dependent Na<sup>+</sup>/Ca<sup>2+</sup> Exchanger NCKX2","year":2002,"lang":"en","type":"article","venue":"Annals of the New York Academy of Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Library science; Medicine; Chemistry; Computer science","score_opus":0.08746803547962471,"score_gpt":0.3254307273571292,"score_spread":0.23796269187750446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045327901","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":[0.9407829,0.023537342,0.000021185773,0.0346145,0.00008898953,0.0003865074,0.000030338082,0.000014282643,0.00052394415],"genre_scores_gemma":[0.9877251,0.0025693208,0.00028152802,0.003485623,0.0004898751,0.00001651795,0.0000027177316,0.000022404598,0.005406951],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99554485,0.0006141941,0.0009464699,0.0008890433,0.0012156571,0.00078979786],"domain_scores_gemma":[0.9980318,0.00022593956,0.0006991518,0.00066242536,0.0001848207,0.00019585805],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0019945765,0.00046148157,0.0008071673,0.00015536485,0.0005078627,0.000037270867,0.0027134635,0.00046746273,0.00023806033],"category_scores_gemma":[0.00060511107,0.00027351602,0.00081159646,0.0011348072,0.0029816877,0.00003311351,0.0011592193,0.00037275467,0.00001493796],"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":[0.00017460159,0.00055464753,0.011710019,0.0002077528,0.0015240174,0.0000021852302,0.006255638,0.43653744,0.06406323,0.0009846048,0.4683615,0.009624359],"study_design_scores_gemma":[0.0016469831,0.0014391986,0.0037190623,0.0005293004,0.0006256877,0.00006525154,0.013179387,0.042120982,0.83632326,0.008702778,0.090179816,0.0014683033],"about_ca_topic_score_codex":0.00007181084,"about_ca_topic_score_gemma":0.000008441625,"teacher_disagreement_score":0.77226,"about_ca_system_score_codex":0.000019918987,"about_ca_system_score_gemma":0.0001082777,"threshold_uncertainty_score":0.9999717},"labels":[],"label_agreement":null},{"id":"W2045380775","doi":"10.1103/physreve.82.035102","title":"Attractor and basin entropies of random Boolean networks under asynchronous stochastic update","year":2010,"lang":"en","type":"article","venue":"Physical Review E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"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 Calgary","funders":"","keywords":"Attractor; Asynchronous communication; Boolean network; Probability distribution; Statistical physics; Structural basin; Entropy (arrow of time); Computer science; Mathematics; Discrete mathematics; Boolean function; Statistics; Mathematical analysis; Physics; Geology; Quantum mechanics","score_opus":0.0058673027069139775,"score_gpt":0.25248076032973044,"score_spread":0.24661345762281645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045380775","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":[0.94593436,0.035359055,0.018008687,0.00025984735,0.000087760585,0.00025051032,0.000006281404,0.000008621086,0.00008487839],"genre_scores_gemma":[0.9933219,0.005647073,0.00016016721,0.0003467583,0.00042982504,0.000013852207,0.0000434056,0.000018289355,0.000018709781],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991548,0.000067980436,0.0002102182,0.00026761234,0.00011119119,0.00018821367],"domain_scores_gemma":[0.9993115,0.000035395336,0.0001270464,0.0003669264,0.000058038557,0.00010110203],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014053985,0.00015899407,0.0004152048,0.000013729293,0.000037084366,0.000009800426,0.00012680423,0.00005424781,0.00003145718],"category_scores_gemma":[0.00006640696,0.00012904378,0.00019791262,0.00008397524,0.00014389811,0.0000032728926,0.000082697195,0.00013182423,0.0000068409863],"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":[0.0002740367,0.00070942694,0.0024563468,0.0013383181,0.001290097,0.0000042216643,0.00003782566,0.006891289,0.8684504,0.005815828,0.0055314186,0.10720079],"study_design_scores_gemma":[0.026635036,0.004127999,0.14922458,0.007086961,0.017587153,0.0003295517,0.00016980227,0.2114368,0.24122754,0.021859014,0.3100001,0.010315484],"about_ca_topic_score_codex":0.0000040670184,"about_ca_topic_score_gemma":0.000014952981,"teacher_disagreement_score":0.6272229,"about_ca_system_score_codex":0.0000037185323,"about_ca_system_score_gemma":0.000026730942,"threshold_uncertainty_score":0.52622527},"labels":[],"label_agreement":null},{"id":"W2045854503","doi":"10.4161/cib.23954","title":"Synthetically engineered<i>rpb1</i>alleles altering RNA polymerase II carboxy terminal domain phosphorylation induce discrete morphogenetic defects in<i>Schizosaccharomyces pombe</i>","year":2013,"lang":"en","type":"article","venue":"Communicative & Integrative Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"RNA polymerase II; Biology; Phenotype; Phosphorylation; Cell biology; Computational biology; Genetics; Polymerase; RNA; Gene; Gene expression","score_opus":0.00789033373645488,"score_gpt":0.24364941532706097,"score_spread":0.2357590815906061,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045854503","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":[0.9889361,0.006719083,0.0017487329,0.00045474846,0.00009204745,0.0005545057,0.00005020118,0.000032346124,0.0014122137],"genre_scores_gemma":[0.9934639,0.0008056252,0.004335626,0.00021363985,0.00012929435,0.00035828553,0.0005270054,0.00005676588,0.0001098818],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9968694,0.0009794935,0.0006350827,0.00075240957,0.00013367235,0.00062997825],"domain_scores_gemma":[0.997814,0.00016128574,0.0003007323,0.0013009115,0.00022884224,0.00019420583],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003366774,0.0005705776,0.00062871265,0.00019205477,0.0002673065,0.00004211269,0.0010617513,0.00038629756,0.00013629739],"category_scores_gemma":[0.00017952148,0.0004770373,0.00027111676,0.00035462424,0.00069921894,0.00002124106,0.0008827211,0.0004986551,0.00003119527],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009097381,0.00012280197,0.0056052436,0.000008557496,0.00023596663,0.0000034633285,0.00066892646,0.00012132797,0.9888758,0.0010571836,0.00015947281,0.003050275],"study_design_scores_gemma":[0.0013150849,0.0014654711,0.01969268,0.00018201262,0.00012196946,0.000049411126,0.0022978985,0.0014891826,0.9641616,0.0026064515,0.0053471564,0.0012711346],"about_ca_topic_score_codex":0.00037122,"about_ca_topic_score_gemma":0.0006282685,"teacher_disagreement_score":0.02471426,"about_ca_system_score_codex":0.00009934914,"about_ca_system_score_gemma":0.000119672266,"threshold_uncertainty_score":0.99976814},"labels":[],"label_agreement":null},{"id":"W2045924769","doi":"10.1016/j.jtbi.2007.01.012","title":"Why a simple model of genetic regulatory networks describes the distribution of avalanches in gene expression data","year":2007,"lang":"en","type":"article","venue":"Journal of Theoretical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":152,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Simple (philosophy); Statistical physics; Value (mathematics); Expression (computer science); Distribution (mathematics); Node (physics); Exponent; Mathematics; Computer science; Applied mathematics; Physics; Statistics; Mathematical analysis; Quantum mechanics","score_opus":0.015444532452641558,"score_gpt":0.2624500061486219,"score_spread":0.24700547369598036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045924769","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":[0.7391636,0.0023656688,0.25821894,0.00009700079,0.000053426273,0.000058074158,0.00002868516,0.0000010785561,0.00001357228],"genre_scores_gemma":[0.9961549,0.00041336173,0.0029832881,0.00009046187,0.00021777971,5.585691e-7,0.00012566295,0.000011549742,0.0000024602086],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9982508,0.0002734446,0.0008374297,0.00022111919,0.00014758375,0.0002696349],"domain_scores_gemma":[0.99840033,0.00012179346,0.00050818955,0.0007045476,0.000186211,0.00007893008],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017943174,0.00013842,0.0003726355,0.00006587633,0.00003136079,0.000003962461,0.00070198264,0.00026503456,0.000013359176],"category_scores_gemma":[0.0002948718,0.000089559435,0.00016446947,0.00015111527,0.0007816989,0.000006296575,0.0003319634,0.00017228466,1.4517431e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007275847,0.00015763681,0.028685337,0.000016846454,0.00016427788,0.0000039011657,0.000030974286,0.060658548,0.9006713,0.005232015,0.0015502331,0.0021013545],"study_design_scores_gemma":[0.0012580476,0.0008693633,0.016811956,0.00008445286,0.00030548716,0.000098419216,0.00014266462,0.100079656,0.8465301,0.03249328,0.0010057064,0.00032086275],"about_ca_topic_score_codex":0.0000038550174,"about_ca_topic_score_gemma":0.0000090631875,"teacher_disagreement_score":0.25699133,"about_ca_system_score_codex":0.0000183621,"about_ca_system_score_gemma":0.000066471664,"threshold_uncertainty_score":0.36521277},"labels":[],"label_agreement":null},{"id":"W2046183976","doi":"10.1196/annals.1407.010","title":"CellFrame: A Data Structure for Abstraction of Cell Biology Experiments and Construction of Perturbation Networks","year":2007,"lang":"en","type":"article","venue":"Annals of the New York Academy of Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"University of Toronto","funders":"Ontario Genomics Institute; Genome Canada","keywords":"Computer science; Perturbation (astronomy); Biological network; Theoretical computer science; Abstraction; Systems biology; Data integration; Data type; Biological data; Data mining; Biological system; Computational biology; Bioinformatics; Biology; Programming language; Physics","score_opus":0.061172757792288854,"score_gpt":0.3442200195832497,"score_spread":0.28304726179096085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046183976","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":[0.99335974,0.0038298834,0.0023071603,0.00022214289,0.00007692425,0.00012726245,0.000028362814,0.0000011435875,0.000047402074],"genre_scores_gemma":[0.99408406,0.00034229129,0.005367083,0.00005035277,0.00010121434,4.5232815e-7,0.000014488929,0.0000034711704,0.00003655954],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99914724,0.00003239655,0.00033467097,0.00023183206,0.00012427353,0.0001295663],"domain_scores_gemma":[0.9991003,0.000043129407,0.00061459537,0.00015335061,0.000055944805,0.000032645275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005663801,0.000078342404,0.0001684215,0.000054819193,0.000055713346,0.000003047438,0.00041057402,0.00018309426,0.0000036018105],"category_scores_gemma":[0.000043897762,0.000057467256,0.000065808155,0.00019337401,0.00061651616,0.000010677171,0.00011471085,0.00005074995,1.5674459e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000064953645,0.00001606131,0.0032025506,0.00002532025,0.00004295392,2.3251303e-9,0.000043101132,0.0022389467,0.98705274,0.00029389095,0.00068612426,0.0063333693],"study_design_scores_gemma":[0.00014238856,0.00012897595,0.0038299176,0.00001743449,0.000033562716,0.0000011216131,0.00018983449,0.0014690018,0.9910187,0.0022361986,0.0008795014,0.000053338263],"about_ca_topic_score_codex":0.000024165536,"about_ca_topic_score_gemma":0.0000040866526,"teacher_disagreement_score":0.006280031,"about_ca_system_score_codex":0.0000015278837,"about_ca_system_score_gemma":0.000036053767,"threshold_uncertainty_score":0.23434466},"labels":[],"label_agreement":null},{"id":"W2046590649","doi":"10.1038/embor.2009.195","title":"The complexity of living: when biology meets theory","year":2009,"lang":"en","type":"article","venue":"EMBO Reports","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Institute of Genetics; Centre National de la Recherche Scientifique; Weizmann Institute of Science; Institut National de la Santé et de la Recherche Médicale","keywords":"Biology; Evolutionary biology; Computational biology","score_opus":0.016394508893243568,"score_gpt":0.25553871105171,"score_spread":0.23914420215846643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046590649","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":[0.982818,0.005182342,0.0012876687,0.0008339909,0.00023723402,0.00015006526,0.0000024180563,0.000019434512,0.009468837],"genre_scores_gemma":[0.99815327,0.000089665096,0.0003895086,0.00013940444,0.000161564,0.0000034258153,0.000017862048,0.000008464453,0.0010368493],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.998921,0.00016417941,0.00033733682,0.00027719687,0.000094371186,0.00020594776],"domain_scores_gemma":[0.99881095,0.000040071533,0.00026798344,0.0007406731,0.000087066,0.00005328792],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007722742,0.00011331073,0.00017389366,0.000022380205,0.00011387191,0.000009966573,0.00015794956,0.00010520155,0.000045988098],"category_scores_gemma":[0.0003111609,0.000080518,0.00015661497,0.00006468647,0.00030505093,0.0000013009941,0.0000807539,0.000050599683,0.0000016715165],"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":[0.00010193097,0.00027525067,0.040932614,0.00001565634,0.0007607236,0.000061004408,0.0002697611,0.00039823764,0.8582492,0.03338135,0.02947028,0.036084004],"study_design_scores_gemma":[0.00020044167,0.00088458793,0.16974622,0.00007225991,0.00028540866,0.00058166625,0.00018221243,0.00018108936,0.25451717,0.2602143,0.31232205,0.00081261265],"about_ca_topic_score_codex":0.000007942078,"about_ca_topic_score_gemma":0.000026592836,"teacher_disagreement_score":0.60373205,"about_ca_system_score_codex":0.000006984876,"about_ca_system_score_gemma":0.000050412113,"threshold_uncertainty_score":0.32834288},"labels":[],"label_agreement":null},{"id":"W2047890830","doi":"10.1016/j.crvi.2005.09.005","title":"The mechanism distinguishability problem in biochemical kinetics: The single-enzyme, single-substrate reaction as a case study","year":2005,"lang":"en","type":"article","venue":"Comptes Rendus Biologies","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":47,"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 Lethbridge","funders":"Wellcome Trust","keywords":"Substrate specificity; Michaelis–Menten kinetics; Transformation (genetics); Substrate (aquarium); Stereochemistry; Chemistry; Philosophy; Enzyme; Biology; Enzyme assay; Biochemistry; Gene","score_opus":0.026815823825031664,"score_gpt":0.26424082638686114,"score_spread":0.23742500256182947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047890830","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":[0.99431175,0.0041680676,0.000059643848,0.000452168,0.00012388614,0.0005483779,0.000007186438,0.00005570046,0.00027319594],"genre_scores_gemma":[0.99871916,0.00014013694,0.00046558017,0.000057089343,0.0003376659,0.000100266734,0.000045700035,0.000021935139,0.00011246603],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99781895,0.00040237303,0.0005218864,0.000639907,0.00015987888,0.00045699326],"domain_scores_gemma":[0.9984884,0.0001895978,0.0002296385,0.00089627045,0.00013160297,0.000064458414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062888325,0.0003083053,0.00026082632,0.00004432698,0.0002975184,0.00010488963,0.00049749174,0.00022536716,0.0000100953475],"category_scores_gemma":[0.00043061865,0.00018677517,0.00015170017,0.0002650992,0.0003707112,0.0000055419387,0.0003685541,0.00025241403,0.000014403818],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010519353,0.00078428205,0.008216265,0.0000093472745,0.00016612983,0.000058753958,0.00022408697,0.00046041788,0.97129446,0.00003318386,0.0011538514,0.017494008],"study_design_scores_gemma":[0.0013779686,0.0030141287,0.01114162,0.00004826083,0.00025197663,0.0010815032,0.0109805865,0.0011419507,0.9462563,0.0019127053,0.021713724,0.0010792927],"about_ca_topic_score_codex":0.00013834122,"about_ca_topic_score_gemma":0.0011196242,"teacher_disagreement_score":0.025038198,"about_ca_system_score_codex":0.00009165855,"about_ca_system_score_gemma":0.000035870085,"threshold_uncertainty_score":0.76164705},"labels":[],"label_agreement":null},{"id":"W2048438929","doi":"10.1002/bies.201100031","title":"The molecular and mathematical basis of Waddington's epigenetic landscape: A framework for post‐Darwinian biology?","year":2011,"lang":"en","type":"article","venue":"BioEssays","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":368,"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; Canadian Institutes of Health Research","keywords":"Biology; Darwinism; Evolutionary biology; Epigenetics; Basis (linear algebra); Computational biology; Ecology; Genetics; Gene","score_opus":0.013210756294345486,"score_gpt":0.24946813863839762,"score_spread":0.23625738234405214,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048438929","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":[0.9279498,0.0060465513,0.06438429,0.0002659022,0.00008806082,0.0003350759,0.00004951769,0.00001374748,0.00086704094],"genre_scores_gemma":[0.98051244,0.00023981833,0.018921051,0.000082809755,0.00007999501,0.000047280802,0.000029179491,0.000026053249,0.000061356],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999031,0.00006986917,0.0002469077,0.00030422298,0.0000753798,0.00027260653],"domain_scores_gemma":[0.9991178,0.00007468661,0.00012095227,0.00048828864,0.00011248703,0.00008580241],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003147833,0.00015954829,0.00020898909,0.000036903755,0.000115883166,0.000013451677,0.00024726437,0.00022982716,0.00004103796],"category_scores_gemma":[0.00021476866,0.000112483634,0.00016687927,0.00008636307,0.00024445812,0.0000015039429,0.000119685246,0.00005569585,0.0000036109823],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00050077296,0.00032457977,0.027645748,0.00023982182,0.001662399,0.00000634528,0.0005833034,0.000019321955,0.7217048,0.2106282,0.001154005,0.035530746],"study_design_scores_gemma":[0.0008839141,0.0012635394,0.0058864276,0.000069158945,0.00049357454,0.00002807219,0.0005355842,0.000566592,0.8888044,0.089870416,0.010947882,0.00065044145],"about_ca_topic_score_codex":0.0000039607025,"about_ca_topic_score_gemma":0.000005810246,"teacher_disagreement_score":0.16709964,"about_ca_system_score_codex":0.0000034124216,"about_ca_system_score_gemma":0.000034471635,"threshold_uncertainty_score":0.45869496},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.02809685971942087,"score_gpt":0.26069570326793556,"score_spread":0.2325988435485147,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048939079","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":[0.94713867,0.0007443658,0.051431898,0.00002054066,0.00031828062,0.0002123819,0.000021101798,0.000009774716,0.000102975224],"genre_scores_gemma":[0.9983073,0.00001429729,0.0007514593,0.000038435584,0.00039583995,0.00000585699,0.00026108077,0.000013151023,0.00021257406],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9987559,0.0001919414,0.00039226332,0.00034647895,0.00010341898,0.0002100288],"domain_scores_gemma":[0.9992894,0.000009551269,0.00020539928,0.00030211383,0.00012260916,0.00007096001],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001583076,0.00016061093,0.00025893757,0.00011234158,0.000050219136,0.000010414233,0.00012584309,0.0002358461,0.000012627867],"category_scores_gemma":[0.000011873513,0.00015060727,0.0001549885,0.00015714476,0.000029817927,0.0000042655893,0.000018441222,0.000039083938,0.000005247491],"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":[0.00006159713,0.00004098467,0.023543017,0.00002080008,0.000032388216,9.499674e-8,0.0000168251,0.04146384,0.9343492,0.00028813805,0.000083036284,0.00010008629],"study_design_scores_gemma":[0.0012407207,0.0008477862,0.6158452,0.000048052247,0.00021044466,0.000019266485,0.00006786687,0.011755656,0.3629016,0.00025350496,0.0062104673,0.0005994106],"about_ca_topic_score_codex":0.00004315068,"about_ca_topic_score_gemma":0.000026213389,"teacher_disagreement_score":0.5923022,"about_ca_system_score_codex":0.000033945,"about_ca_system_score_gemma":0.000051160263,"threshold_uncertainty_score":0.61415863},"labels":[],"label_agreement":null},{"id":"W2049926459","doi":"10.1063/1.2211787","title":"Estimations of intrinsic and extrinsic noise in models of nonlinear genetic networks","year":2006,"lang":"en","type":"article","venue":"Chaos An Interdisciplinary Journal of Nonlinear Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":103,"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 Ottawa; University of Waterloo","funders":"","keywords":"Nonlinear system; Noise (video); Computer science; Gene regulatory network; Genetic network; Biological system; Control theory (sociology); Physics; Biology; Artificial intelligence; Gene; Genetics","score_opus":0.011300790286782629,"score_gpt":0.2805673961774796,"score_spread":0.269266605890697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2049926459","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":[0.9809006,0.0015022382,0.017275369,0.000059989423,0.00009766612,0.000088022105,0.000007800353,0.0000019635213,0.00006634707],"genre_scores_gemma":[0.9715608,0.00015200187,0.027958639,0.00000858118,0.0002784093,0.0000013158415,0.000008217278,0.000013636421,0.000018451712],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99828696,0.000056549645,0.00082441734,0.00028621103,0.00030273656,0.00024315089],"domain_scores_gemma":[0.9984854,0.000019074338,0.0005582759,0.00036409855,0.00044868723,0.00012450322],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006356639,0.00015696636,0.0003512029,0.00040997934,0.00010048323,0.000022487733,0.0004984518,0.00008893165,0.000005352746],"category_scores_gemma":[0.000027125843,0.00013961592,0.00012928837,0.00064010534,0.0006917147,0.000051323674,0.0004601078,0.0001441991,2.8564486e-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":[0.00018632917,0.00054619194,0.014581539,0.00004384148,0.00004229607,0.000025071146,0.00032798422,0.7607853,0.210289,0.00007536627,0.000039269686,0.013057838],"study_design_scores_gemma":[0.0008995581,0.0011381105,0.08310025,0.00018768384,0.00007797266,0.0002787739,0.00037560318,0.88205445,0.030568276,0.0010300709,0.000024835159,0.0002644082],"about_ca_topic_score_codex":0.000013250942,"about_ca_topic_score_gemma":0.00007307285,"teacher_disagreement_score":0.17972071,"about_ca_system_score_codex":0.000027348407,"about_ca_system_score_gemma":0.00022560627,"threshold_uncertainty_score":0.5693372},"labels":[],"label_agreement":null},{"id":"W2051093359","doi":"10.1016/j.jtbi.2007.10.035","title":"Monte Carlo simulation of a simple gene network yields new evolutionary insights","year":2007,"lang":"en","type":"article","venue":"Journal of Theoretical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Monte Carlo method; Gene duplication; Gene; Biology; Phenotype; Function (biology); Computational biology; Computer science; Statistical physics; Simple (philosophy); Stability (learning theory); Biological system; Gene regulatory network; Genetics; Physics; Mathematics; Gene expression; Machine learning; Statistics","score_opus":0.0075387879761822044,"score_gpt":0.2613074207028105,"score_spread":0.2537686327266283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2051093359","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":[0.9240515,0.004670968,0.07066559,0.00011356193,0.00022628457,0.00006277571,0.000002820992,0.0000032781313,0.00020318179],"genre_scores_gemma":[0.9950099,0.00013850965,0.0030888307,0.00014908076,0.0015471597,3.12185e-7,0.000011619315,0.000013433874,0.00004117912],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99858487,0.00015660722,0.00066155253,0.00017627254,0.00013667125,0.00028402935],"domain_scores_gemma":[0.99875546,0.00014018369,0.00039988244,0.00025073744,0.00027258485,0.00018112751],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059230014,0.00014131962,0.000343901,0.00009266707,0.000044871605,0.0000040938307,0.0002377278,0.00033219997,0.00007031711],"category_scores_gemma":[0.00023792975,0.000110903646,0.00029999728,0.00018605232,0.00031400478,0.0000040338773,0.00009658229,0.00015005957,0.0000019843985],"study_design_candidate":"simulation_or_modeling","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":[0.0018441939,0.00016723624,0.020991962,0.000013332864,0.00088569184,0.000024946667,0.00007816296,0.6968785,0.24330123,0.024403572,0.004675697,0.006735476],"study_design_scores_gemma":[0.007192519,0.012384684,0.05438559,0.0001556054,0.0018364837,0.00074612396,0.00028806436,0.09343476,0.3199903,0.37667137,0.13094996,0.0019645079],"about_ca_topic_score_codex":0.000004832907,"about_ca_topic_score_gemma":0.000009331152,"teacher_disagreement_score":0.60344374,"about_ca_system_score_codex":0.00002455497,"about_ca_system_score_gemma":0.00011284263,"threshold_uncertainty_score":0.45225194},"labels":[],"label_agreement":null},{"id":"W2053424935","doi":"10.1214/13-aap946","title":"Stochastically-induced bistability in chemical reaction systems","year":2014,"lang":"en","type":"article","venue":"The Annals of Applied Probability","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"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":"Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Bistability; Chemical reaction; Branching (polymer chemistry); Bounded function; Mechanism (biology); Chemical species; Chemical process; Chemical Dynamics","score_opus":0.03846017869960279,"score_gpt":0.27760922336088784,"score_spread":0.23914904466128506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053424935","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":[0.9967031,0.000055063672,0.0007041263,0.00024191437,0.000038433893,0.00042363693,0.0000029660227,0.000011509314,0.0018192319],"genre_scores_gemma":[0.99956316,0.000006160472,0.00014025143,0.0000632626,0.00012219154,0.000066616616,0.000019889432,0.000011406913,0.0000070459987],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985544,0.00016427832,0.00042349394,0.0004158368,0.00019211782,0.00024984338],"domain_scores_gemma":[0.9986422,0.000059934937,0.00014941189,0.0009453372,0.0001363207,0.000066785884],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020237335,0.00014772014,0.0002778029,0.000026461497,0.000036841204,0.000009906227,0.00027795832,0.00016262912,0.000003844056],"category_scores_gemma":[0.0002076343,0.00011225659,0.00011465979,0.00019185613,0.0001807131,0.0000022207837,0.000117292846,0.00012780711,0.000004224682],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039891005,0.00018403369,0.0008352366,0.0000725671,0.000046510217,4.5429797e-8,0.000046867477,0.0026804472,0.989672,0.002893698,0.00008677148,0.003082909],"study_design_scores_gemma":[0.0005832277,0.00022106765,0.021044679,0.000019809517,0.00005291559,0.000002434844,0.000093853865,0.0032923047,0.94883966,0.023670882,0.0018004479,0.00037872593],"about_ca_topic_score_codex":0.000048465914,"about_ca_topic_score_gemma":0.00003144821,"teacher_disagreement_score":0.040832352,"about_ca_system_score_codex":0.00001629468,"about_ca_system_score_gemma":0.000044813216,"threshold_uncertainty_score":0.45776907},"labels":[],"label_agreement":null},{"id":"W2053460598","doi":"10.1126/science.1188308","title":"Quantifying <i>E. coli</i> Proteome and Transcriptome with Single-Molecule Sensitivity in Single Cells","year":2010,"lang":"en","type":"article","venue":"Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2109,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research; National Institutes of Health","keywords":"Messenger RNA; Biology; Escherichia coli; Transcriptome; Proteome; Single-cell analysis; Transcription (linguistics); Fusion protein; Gene expression; Molecular biology; RNA; Cell; Gene; Uncorrelated; Cell biology; Genetics","score_opus":0.012831085027316318,"score_gpt":0.23068872467952328,"score_spread":0.21785763965220697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053460598","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":[0.99820113,0.000075630735,0.0011929375,0.00008351034,0.000072457646,0.00015491656,0.0000020284172,0.000008873899,0.00020850463],"genre_scores_gemma":[0.9976373,0.0000050453923,0.0021493696,0.0000956865,0.000040859497,0.00000628095,0.000002344046,0.000010072005,0.00005308527],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988815,0.000031245898,0.000110934496,0.00046549007,0.00020380398,0.00030701287],"domain_scores_gemma":[0.9994822,0.000005767832,0.000045575922,0.00028689692,0.000073674215,0.00010585606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052855536,0.00011440335,0.00011617273,0.00008668794,0.00012150871,0.0000647164,0.00012972274,0.00006459213,0.0000026892785],"category_scores_gemma":[0.000022698037,0.00010098203,0.000026538164,0.0005084462,0.0005986819,0.000012507661,0.000055433396,0.00010271172,0.0000017873977],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015289063,0.000049706676,0.0057016765,0.000006676737,0.0000033861156,0.0000070550586,0.000052645566,0.00017962916,0.99367,0.000007585779,0.0000053441627,0.0003010478],"study_design_scores_gemma":[0.00020024345,0.00013744115,0.012124376,0.000010376278,0.000007864072,0.000026570735,0.0000388956,0.00046720146,0.98615605,0.000008011741,0.00066854694,0.00015441762],"about_ca_topic_score_codex":0.000016421776,"about_ca_topic_score_gemma":0.0011608147,"teacher_disagreement_score":0.007513903,"about_ca_system_score_codex":0.000011481815,"about_ca_system_score_gemma":0.00009392977,"threshold_uncertainty_score":0.41179278},"labels":[],"label_agreement":null},{"id":"W2053632366","doi":"10.3389/fonc.2013.00064","title":"Stochastic and Deterministic Models of Cellular p53 Regulation","year":2013,"lang":"en","type":"article","venue":"Frontiers in Oncology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Regulator; In silico; MDMX; Computer science; Master regulator; Computational biology; Synchronization (alternating current); Systems biology; Biology; Stochastic modelling; Mdm2; Transcription factor; Genetics; Mathematics; Gene","score_opus":0.0076180330377753755,"score_gpt":0.22268436380281523,"score_spread":0.21506633076503986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053632366","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":[0.7649997,0.00141277,0.23273277,0.00006523301,0.00019323999,0.0001844494,0.000001769887,0.0000039096867,0.0004061569],"genre_scores_gemma":[0.9906293,0.000055833472,0.008810449,0.000041891726,0.00006893982,0.000029864852,0.000027328842,0.000012846749,0.00032350508],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991778,0.00008824295,0.0002451437,0.00024699647,0.00006573138,0.00017608251],"domain_scores_gemma":[0.99954027,0.000012587484,0.00011011969,0.00022687869,0.00005472241,0.000055405897],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010738046,0.00010203113,0.000245091,0.00010306955,0.000023058743,0.000004833078,0.00010191834,0.00019678911,0.000016186294],"category_scores_gemma":[0.000029661884,0.00010614323,0.000045848483,0.000092234106,0.00014594234,0.0000047143144,0.00006772516,0.00005282915,0.000001817545],"study_design_candidate":"simulation_or_modeling","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":[0.00021271482,0.0002631445,0.017135179,0.00009040937,0.0003265116,0.000009808214,0.00041000725,0.16067283,0.7023784,0.0004985808,0.023112986,0.094889425],"study_design_scores_gemma":[0.0027058052,0.0014864093,0.02566538,0.000042965858,0.0002588141,0.00003681704,0.0006685716,0.8998499,0.029189317,0.034113362,0.005233109,0.0007495328],"about_ca_topic_score_codex":0.000016834392,"about_ca_topic_score_gemma":0.000018436038,"teacher_disagreement_score":0.7391771,"about_ca_system_score_codex":0.0000313607,"about_ca_system_score_gemma":0.000056800985,"threshold_uncertainty_score":0.4328395},"labels":[],"label_agreement":null},{"id":"W2054854610","doi":"10.1155/2014/761562","title":"State Observer Design for Delayed Genetic Regulatory Networks","year":2014,"lang":"en","type":"article","venue":"Computational and Mathematical Methods in Medicine","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Beijing Wuzi University","keywords":"Observer (physics); Gene regulatory network; Computer science; Linear matrix inequality; State (computer science); Control theory (sociology); Genetic network; Mathematical optimization; Gene; Genetics; Biology; Mathematics; Control (management); Artificial intelligence; Gene expression; Physics","score_opus":0.0400740962968691,"score_gpt":0.3536375812136368,"score_spread":0.3135634849167677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2054854610","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.054293193,0.0010205128,0.9441125,0.00020283724,0.000059824295,0.00024590167,8.4373517e-7,0.0000088197985,0.000055571614],"genre_scores_gemma":[0.14783166,0.00004026447,0.85123885,0.00042700156,0.00022693486,0.00004859625,0.000026961343,0.000020020589,0.00013973197],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985739,0.00039121037,0.00039037215,0.0003113168,0.00012995927,0.00020323861],"domain_scores_gemma":[0.99882096,0.0006981687,0.000088998575,0.00018747892,0.00009269104,0.00011172412],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018166533,0.00015092466,0.00031686612,0.00005803091,0.00005409543,0.000007724453,0.000106986176,0.00009313349,0.000017819466],"category_scores_gemma":[0.000463509,0.00012073745,0.000055182576,0.00011219705,0.0001744618,0.0000023056932,0.000054271095,0.000064066175,8.9726285e-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":[0.00019120712,0.0000929709,0.00048268933,0.00016956343,0.0002100646,0.000001835803,0.00013036738,0.8591607,0.008935002,0.008069257,0.0029219636,0.11963434],"study_design_scores_gemma":[0.00078370946,0.00028065944,0.0050019943,0.00004166827,0.000060653936,0.000013523615,0.000013123435,0.7530228,0.00044165863,0.23928763,0.0009090896,0.00014350853],"about_ca_topic_score_codex":0.0000010319847,"about_ca_topic_score_gemma":0.0000012232169,"teacher_disagreement_score":0.23121838,"about_ca_system_score_codex":0.000009451414,"about_ca_system_score_gemma":0.00002193097,"threshold_uncertainty_score":0.49235305},"labels":[],"label_agreement":null},{"id":"W2055423376","doi":"10.1002/cjce.5450840401","title":"Dynamic Modelling and Prediction of Cytotoxicity on Microelectronic cell Sensor Array","year":2006,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cytotoxicity; Toxicant; Microelectronics; Computer science; Process (computing); Identification (biology); Biological system; System identification; Estimation theory; Term (time); Data mining; Engineering; Algorithm; Chemistry; Measure (data warehouse)","score_opus":0.0029052492548073557,"score_gpt":0.15380922566717137,"score_spread":0.150903976412364,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055423376","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":[0.9918094,0.001073415,0.006973918,0.000050534865,0.00002627543,0.000027882243,0.0000059034182,0.000001429096,0.00003123344],"genre_scores_gemma":[0.9992078,0.000012508145,0.00061433914,0.000010305296,0.00011351558,4.358319e-7,0.000005646489,0.000012223373,0.00002321553],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995019,0.000010006678,0.000182649,0.00007568912,0.000068757894,0.00016102899],"domain_scores_gemma":[0.99966115,0.000008847059,0.000080204976,0.00010289521,0.000048316808,0.00009861322],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000118163254,0.00008047588,0.00011211501,0.000056213205,0.00002636311,0.000008789686,0.00009048609,0.00007149534,0.0000017717534],"category_scores_gemma":[0.000009024093,0.00006721441,0.000074002935,0.00006221064,0.000035301884,0.0000020079956,0.0000046135992,0.00013217206,1.5850198e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000050846274,0.0000024359217,0.00007007067,0.0000058396104,0.000017677634,7.3703336e-7,0.0000052036567,0.36088812,0.6389665,0.0000053330455,0.00002241613,0.000010585251],"study_design_scores_gemma":[0.00013862518,0.000047272428,0.000098841505,0.00001692243,0.000036064048,0.0000393146,0.00000253623,0.04777901,0.9515766,0.000031263757,0.00017730118,0.000056246216],"about_ca_topic_score_codex":0.0001484495,"about_ca_topic_score_gemma":0.000096894335,"teacher_disagreement_score":0.31310913,"about_ca_system_score_codex":0.000058827543,"about_ca_system_score_gemma":0.00010389311,"threshold_uncertainty_score":0.2740924},"labels":[],"label_agreement":null},{"id":"W2056090982","doi":"10.1016/j.bpc.2003.08.009","title":"Conservation analysis in biochemical networks: computational issues for software writers","year":2004,"lang":"en","type":"review","venue":"Biophysical Chemistry","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":95,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Software; Data science; Property (philosophy); Balance (ability); Moiety; Contrast (vision); Computer science; Flux (metallurgy); Scale (ratio); Theoretical computer science; Biochemical engineering; Chemistry; Data mining; Management science; Epistemology; Artificial intelligence; Psychology; Geography; Engineering; Neuroscience","score_opus":0.016853713703339237,"score_gpt":0.2975842670122676,"score_spread":0.2807305533089284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056090982","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017923319,0.9860127,0.011436176,0.000037646172,0.0000447108,0.0004459601,0.00018649189,0.00003404698,0.000009922685],"genre_scores_gemma":[0.0033914277,0.95876384,0.006027359,0.0000845748,0.0015771462,0.00040392153,0.029145481,0.00013565793,0.00047059284],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99752706,0.000058057612,0.00073014514,0.0010172188,0.0002328709,0.00043464566],"domain_scores_gemma":[0.9987007,0.000081152284,0.00035724672,0.0005724529,0.00013888361,0.00014956278],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00014429839,0.0005735128,0.001486867,0.00011169947,0.00006479554,0.000050183222,0.00042213645,0.00084939576,0.000020440255],"category_scores_gemma":[0.000090690664,0.0005755976,0.0016470299,0.0010687261,0.0001683184,0.0000041128965,0.00014323785,0.000241824,0.000005535154],"study_design_candidate":"not_applicable","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":[0.000703833,0.004751634,0.0017150519,0.12804967,0.050959148,0.00010767848,0.000094248135,0.41943526,0.025801728,0.00024524084,0.047722314,0.3204142],"study_design_scores_gemma":[0.0017973876,0.00014886046,0.00011696767,0.0050085876,0.014339449,0.000025443931,0.000022404141,0.013129269,0.004262059,0.00036604865,0.9573912,0.0033923108],"about_ca_topic_score_codex":0.00001249406,"about_ca_topic_score_gemma":0.000003548185,"teacher_disagreement_score":0.9096689,"about_ca_system_score_codex":0.00015550709,"about_ca_system_score_gemma":0.00031030978,"threshold_uncertainty_score":0.99966955},"labels":[],"label_agreement":null},{"id":"W2058740724","doi":"10.1103/physreve.75.061903","title":"Effects of coupling strength and space on the dynamics of coupled toggle switches in stochastic gene networks with multiple-delayed reactions","year":2007,"lang":"en","type":"article","venue":"Physical Review E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"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 Calgary","funders":"","keywords":"Bistability; Coupling (piping); Gene regulatory network; Stability (learning theory); Control theory (sociology); Biological system; Statistical physics; Physics; Parameter space; Stochastic process; Computer science; Phase space; Coupling strength; Topology (electrical circuits); Mathematics; Gene; Biology; Gene expression; Materials science; Quantum mechanics; Genetics; Combinatorics; Statistics; Artificial intelligence","score_opus":0.005645650362899382,"score_gpt":0.24303418747099642,"score_spread":0.23738853710809704,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058740724","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":[0.9647563,0.008818729,0.026007488,0.000071989176,0.000011496229,0.00031930523,0.0000020404282,0.0000029809405,0.000009675224],"genre_scores_gemma":[0.99667484,0.0030127906,0.00015567525,0.00003791115,0.000059947404,0.000015319836,0.000021658483,0.000014548306,0.0000073097276],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992869,0.000024975503,0.00021451506,0.00019782658,0.00012046354,0.00015535628],"domain_scores_gemma":[0.99914485,0.00031286216,0.00017690702,0.00026022154,0.000058760477,0.00004639883],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025963582,0.0001302569,0.0003167287,0.000021665348,0.000027448703,0.0000026214943,0.000087146924,0.000039105398,7.383254e-7],"category_scores_gemma":[0.00014025584,0.00008638069,0.00008391043,0.00022604805,0.00008498486,0.0000017702487,0.000038540904,0.000101909965,2.5834447e-7],"study_design_candidate":"simulation_or_modeling","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":[0.00047564213,0.00086358096,0.003804329,0.0012179511,0.00064072997,0.0000043357104,0.00005490407,0.34021583,0.64631265,0.0015642452,0.00004834479,0.0047974167],"study_design_scores_gemma":[0.00081228785,0.00062816904,0.009177512,0.0015647998,0.0004946636,0.0000035607989,0.000048452916,0.8986543,0.08822344,0.000062906984,0.000050166465,0.00027975757],"about_ca_topic_score_codex":0.00003466958,"about_ca_topic_score_gemma":0.00018652997,"teacher_disagreement_score":0.5584384,"about_ca_system_score_codex":0.00001517535,"about_ca_system_score_gemma":0.000019382851,"threshold_uncertainty_score":0.35225025},"labels":[],"label_agreement":null},{"id":"W2059744016","doi":"10.1016/j.artmed.2009.10.002","title":"Scalable approach for effective control of gene regulatory networks","year":2009,"lang":"en","type":"article","venue":"Artificial Intelligence in Medicine","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Türkiye Bilimsel ve Teknolojik Araştırma Kurumu","keywords":"Scalability; Computer science; Gene regulatory network; Control (management); Domain (mathematical analysis); Process (computing); Gene; Distributed computing; Computational biology; Data mining; Machine learning; Artificial intelligence; Biology; Genetics; Mathematics","score_opus":0.014956136121543185,"score_gpt":0.2785611587238206,"score_spread":0.2636050226022774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059744016","genre_codex":"methods","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":[0.1475265,0.0024657492,0.84873,0.0001907461,0.00011100365,0.00064888864,0.0000027863139,0.000008881027,0.0003153875],"genre_scores_gemma":[0.9952203,0.00007568434,0.0035441413,0.00028880834,0.0006797376,0.00005832809,0.00006781453,0.000015230263,0.000049955488],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984531,0.00010138073,0.0005448227,0.00041040574,0.00016871492,0.0003216075],"domain_scores_gemma":[0.99911416,0.00006574587,0.00015987447,0.00040706128,0.0001695718,0.00008359458],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009226839,0.00017883844,0.0004157576,0.000116432755,0.000048915794,0.0000047826416,0.00022475813,0.00018352325,0.000013723489],"category_scores_gemma":[0.00020747638,0.00015802016,0.00012320983,0.00034630724,0.00023441021,0.0000040109912,0.00001474985,0.00009612631,0.0000010451018],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060513493,0.00022835849,0.0010171703,0.000019098863,0.000100103825,0.0000018924234,0.00010944596,0.2598893,0.55258214,0.0020084726,0.0005474362,0.18289141],"study_design_scores_gemma":[0.00039012727,0.0015336344,0.0034982103,0.000058212663,0.00013720208,0.000006237716,0.0003105091,0.37269345,0.6167991,0.00400722,0.0002736867,0.00029238441],"about_ca_topic_score_codex":0.000021620133,"about_ca_topic_score_gemma":0.000019325851,"teacher_disagreement_score":0.8476938,"about_ca_system_score_codex":0.000023222523,"about_ca_system_score_gemma":0.000027970762,"threshold_uncertainty_score":0.6443875},"labels":[],"label_agreement":null},{"id":"W2059950865","doi":"10.1137/10079118x","title":"Asymptotic and Bifurcation Analysis of Wave-Pinning in a Reaction-Diffusion Model for Cell Polarization","year":2011,"lang":"en","type":"article","venue":"SIAM Journal on Applied Mathematics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":131,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; National Institute of General Medical Sciences; McKnight Foundation; Alfred P. Sloan Foundation; National Institutes of Health; National Science Foundation","keywords":"Bistability; Reaction–diffusion system; Saddle point; Polarization (electrochemistry); Bifurcation; Physics; Pattern formation; Mechanics; Nonlinear system; Chemistry; Thermodynamics; Mathematics; Geometry; Quantum mechanics","score_opus":0.021481043195242074,"score_gpt":0.2312318267003,"score_spread":0.20975078350505794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059950865","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":[0.7660989,0.00005378801,0.23329167,0.000008760597,0.000011839021,0.00012938459,0.0000023953182,0.0000026755276,0.00040058565],"genre_scores_gemma":[0.958149,0.00009548815,0.041552283,0.00003153633,0.000027990372,0.00000964639,0.000034265675,0.00001765899,0.00008213041],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991676,0.00001443261,0.00039489847,0.00016361164,0.00013023756,0.00012918888],"domain_scores_gemma":[0.9992752,0.000017696988,0.0003808748,0.00019183045,0.00008033088,0.000054079126],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036354747,0.000115598195,0.00024448792,0.00034615025,0.000058660295,0.000011126392,0.000069083224,0.00011372915,0.0000044854305],"category_scores_gemma":[0.000023804234,0.00010682772,0.000112441136,0.00031982939,0.00002260972,0.0000043236328,0.000024820383,0.00007587396,4.4180413e-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":[0.0001215368,0.00044644493,0.0011697761,0.00010531488,0.00043445785,5.1435916e-7,0.0014365081,0.024180897,0.9678954,0.0026145354,0.000032828066,0.0015617944],"study_design_scores_gemma":[0.0007484785,0.00014318072,0.0034019107,0.000032921038,0.0009059799,0.000006522057,0.00033841742,0.92144954,0.06860596,0.004153461,0.000021865868,0.00019174062],"about_ca_topic_score_codex":0.0000013267467,"about_ca_topic_score_gemma":0.000008832728,"teacher_disagreement_score":0.8992894,"about_ca_system_score_codex":0.000022313185,"about_ca_system_score_gemma":0.000032267006,"threshold_uncertainty_score":0.4356308},"labels":[],"label_agreement":null},{"id":"W2060184615","doi":"10.1038/nbt.2891","title":"The Synthetic Biology Open Language (SBOL) provides a community standard for communicating designs in synthetic biology","year":2014,"lang":"en","type":"article","venue":"Nature Biotechnology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":290,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"U.S. National Library of Medicine; National Human Genome Research Institute; Engineering and Physical Sciences Research Council","keywords":"Synthetic biology; Workflow; Documentation; Computer science; Software; Software engineering; Systems biology; XML; World Wide Web; Data science; Programming language; Biology; Bioinformatics; Database","score_opus":0.013949896455435921,"score_gpt":0.3063010714780855,"score_spread":0.29235117502264957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060184615","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":[0.9602735,0.0152369365,0.0145465955,0.006974585,0.00028028095,0.0017338241,0.000091831826,0.00012462234,0.0007378185],"genre_scores_gemma":[0.99385065,0.00053229963,0.00459171,0.00040182384,0.00008035623,0.00025463433,0.00015336371,0.000047018737,0.00008817013],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9968993,0.0013884209,0.00045002296,0.0005535291,0.00006586475,0.00064287684],"domain_scores_gemma":[0.99659765,0.0006612737,0.0002716778,0.0022967143,0.000113044225,0.000059644844],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0026762655,0.0003059042,0.00050824834,0.00016734506,0.0006484172,0.00005539064,0.0028513146,0.0018778143,0.0000047460308],"category_scores_gemma":[0.0018971977,0.00023110202,0.00015786034,0.00034628954,0.0008750442,0.0000050358135,0.0009566724,0.0012483358,0.0000038319918],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035333735,0.00012634025,0.0018369241,0.000038695183,0.00022679614,8.7164966e-7,0.00012893314,0.000055113454,0.851914,0.035580654,0.0005234918,0.109214835],"study_design_scores_gemma":[0.0018838128,0.0022753074,0.00025726316,0.00007963901,0.00012282698,0.000046178182,0.0009910616,0.0014235739,0.4989314,0.019522242,0.47373626,0.00073042815],"about_ca_topic_score_codex":0.00015856358,"about_ca_topic_score_gemma":0.0030558424,"teacher_disagreement_score":0.47321275,"about_ca_system_score_codex":0.00005493364,"about_ca_system_score_gemma":0.00010781715,"threshold_uncertainty_score":0.99941796},"labels":[],"label_agreement":null},{"id":"W2060522170","doi":"10.1016/j.bpj.2014.11.3457","title":"Local Perturbation Analysis: A Computational Tool for Biophysical Reaction-Diffusion Models","year":2015,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"National Institute of General Medical Sciences; National Institutes of Health","keywords":"Curse of dimensionality; Parameter space; Perturbation (astronomy); Statistical physics; Bifurcation; Computer science; Reaction–diffusion system; Biological system; Partial differential equation; Physics; Mathematics; Mathematical analysis; Nonlinear system; Artificial intelligence; Geometry","score_opus":0.017564278173106553,"score_gpt":0.2562762103949817,"score_spread":0.23871193222187517,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060522170","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":[0.56145984,0.000036388967,0.43807435,0.00018050746,0.000095800184,0.000086437496,0.000011189395,0.000010346915,0.000045160054],"genre_scores_gemma":[0.9939273,0.000013494155,0.0038724574,0.00015313008,0.0013570683,0.00001811658,0.0003324965,0.000023329725,0.0003025844],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984894,0.000097869444,0.00034792675,0.00036656094,0.00042163028,0.0002766163],"domain_scores_gemma":[0.99877447,0.000026649952,0.00019276871,0.00023162241,0.00050721364,0.00026725902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024930146,0.0002005737,0.00029483854,0.00013719784,0.00017689276,0.000074188436,0.0001851436,0.0001518982,0.0000054291672],"category_scores_gemma":[0.00004082545,0.00017529163,0.0006006771,0.00041581533,0.00009878931,0.000021380016,0.00006282604,0.00013778091,0.000012340085],"study_design_candidate":"simulation_or_modeling","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":[0.0004334653,0.0003865825,0.00019709315,0.000006617661,0.0011188007,0.000003910017,0.000065562526,0.41671035,0.57290655,0.001383114,0.004213245,0.0025747316],"study_design_scores_gemma":[0.0014169692,0.0005290064,0.0015551366,0.0000082399365,0.0010230201,0.00004597964,0.00012000781,0.9701946,0.015270976,0.0066837445,0.0027457122,0.0004066546],"about_ca_topic_score_codex":0.000004525805,"about_ca_topic_score_gemma":0.0000027382002,"teacher_disagreement_score":0.55763555,"about_ca_system_score_codex":0.000081812475,"about_ca_system_score_gemma":0.00016438315,"threshold_uncertainty_score":0.71481854},"labels":[],"label_agreement":null},{"id":"W2060977279","doi":"10.1103/physreve.73.031912","title":"Network growth models and genetic regulatory networks","year":2006,"lang":"en","type":"article","venue":"Physical Review E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":44,"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 Calgary","funders":"National Science Foundation","keywords":"Counterintuitive; Degree distribution; Node (physics); Computer science; Scaling; Degree (music); Gene regulatory network; Gene; Class (philosophy); Genome; Computational biology; Biology; Genetics; Mathematics; Complex network; Physics; Artificial intelligence; Gene expression","score_opus":0.008240815115916456,"score_gpt":0.23538281533581007,"score_spread":0.22714200021989361,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060977279","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":[0.5513511,0.4303846,0.015421316,0.00033139452,0.000088207235,0.00043260548,0.000003028137,0.000040091683,0.001947688],"genre_scores_gemma":[0.9751724,0.021107255,0.0006176762,0.00092681806,0.0018852692,0.000037359136,0.00005736463,0.00003582002,0.00016005477],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99865294,0.00011094936,0.0002575156,0.00046030222,0.00016258647,0.00035570876],"domain_scores_gemma":[0.99922943,0.0000150393425,0.000106234256,0.0004663311,0.00007343017,0.00010954025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012700421,0.00022697932,0.00037263203,0.000013185844,0.00008534657,0.000017809713,0.00016236819,0.00006822306,0.0000063421426],"category_scores_gemma":[0.000011536442,0.00020441083,0.000199249,0.00020318919,0.00009968894,0.0000045821635,0.00013698728,0.000089886606,0.0000075711923],"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":[0.000084604006,0.0005741502,0.016930647,0.0017800963,0.0006680994,0.000037132966,0.000014135734,0.5698759,0.032150857,0.036301784,0.30213183,0.039450753],"study_design_scores_gemma":[0.0024145572,0.00092210586,0.1446944,0.0028382204,0.0036293946,0.00022245628,0.000007895314,0.45686254,0.0060553127,0.25481102,0.12260681,0.004935271],"about_ca_topic_score_codex":0.000012266602,"about_ca_topic_score_gemma":0.000009864408,"teacher_disagreement_score":0.4238213,"about_ca_system_score_codex":0.000010011422,"about_ca_system_score_gemma":0.000022280678,"threshold_uncertainty_score":0.83356315},"labels":[],"label_agreement":null},{"id":"W2061073918","doi":"10.1073/pnas.1215850110","title":"Dissecting genealogy and cell cycle as sources of cell-to-cell variability in MAPK signaling using high-throughput lineage tracking","year":2013,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"Canadian Institutes of Health Research; Genome British Columbia; Michael Smith Health Research BC","keywords":"Biology; Cell cycle; Cell division; Genetics; Cell; Cell fate determination; Phenotype; Cell type; Cell biology; Gene","score_opus":0.016940771862373666,"score_gpt":0.2669728775543855,"score_spread":0.25003210569201184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061073918","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":[0.99904686,0.0002178092,0.000027760047,0.00009998609,0.0000121445,0.00015532156,0.0000029072737,0.000002157749,0.00043506056],"genre_scores_gemma":[0.993852,0.000017011016,0.005945691,0.000054410742,0.00008637877,0.0000041572343,2.8129864e-7,0.0000060937905,0.000033970126],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99867433,0.00002112196,0.00039535383,0.00034081002,0.00039212184,0.00017625137],"domain_scores_gemma":[0.9991615,0.00007449979,0.00042559882,0.000017637292,0.0002789105,0.000041879495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014780656,0.00010561793,0.00018989143,0.0001141096,0.00011682916,0.000020317808,0.0003935412,0.00011799235,0.000008017212],"category_scores_gemma":[0.0002375642,0.00008457372,0.00006673266,0.00048201004,0.00031277453,0.000029709869,0.00021390125,0.00009467073,2.9145906e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000056382346,0.000040858118,0.0322306,0.000078549005,0.0000069670978,3.610736e-9,0.00015959893,0.0150720645,0.9522481,0.00009216664,0.0000057631196,0.00005969763],"study_design_scores_gemma":[0.0001230076,0.00004428166,0.018984566,0.000027770226,0.00001684606,0.0000017082822,0.00033796954,0.0069378046,0.970576,0.0028602653,0.0000049815626,0.00008482867],"about_ca_topic_score_codex":0.0000844522,"about_ca_topic_score_gemma":4.1332356e-7,"teacher_disagreement_score":0.01832788,"about_ca_system_score_codex":0.000015870253,"about_ca_system_score_gemma":0.00003231873,"threshold_uncertainty_score":0.34488165},"labels":[],"label_agreement":null},{"id":"W2061289989","doi":"10.1016/j.bpj.2008.12.1520","title":"Pitchfork And Hopf Bifurcations In Stochastic Regulatory Networks With Delayed Feedback","year":2009,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Pitchfork bifurcation; Bifurcation diagram; Mathematics; Biological applications of bifurcation theory; Saddle-node bifurcation; Statistical physics; Bifurcation; Infinite-period bifurcation; Parametric statistics; Hopf bifurcation; Limit (mathematics); Transcritical bifurcation; Nonlinear system; Stationary distribution; Noise (video); Control theory (sociology); Mathematical analysis; Physics; Quantum mechanics; Computer science; Statistics","score_opus":0.0046314508030490245,"score_gpt":0.2127742311214849,"score_spread":0.2081427803184359,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061289989","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":[0.97755986,0.00043190134,0.021504832,0.00032124095,0.000040329607,0.00007954057,0.0000013201861,0.0000072998578,0.000053642456],"genre_scores_gemma":[0.9983019,0.00008150728,0.0006302621,0.00020531533,0.00066276715,0.0000031272752,0.000015291387,0.000015759126,0.00008402803],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99900293,0.0000579282,0.00022042611,0.00026337453,0.00015888456,0.00029645514],"domain_scores_gemma":[0.99938107,0.000009677335,0.000108741995,0.00023876804,0.000071916766,0.00018982182],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012555285,0.0001699591,0.00019276474,0.00007364917,0.00012371533,0.000050811635,0.00013630831,0.000116220835,0.0000058486658],"category_scores_gemma":[0.000010685998,0.00013900241,0.00008522187,0.0002540241,0.000099714154,0.0000076098945,0.0000316068,0.00020737879,0.0000026904133],"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":[0.0009946233,0.0005831139,0.004397879,0.000006485354,0.00043556953,0.00005583696,0.00012218698,0.3379796,0.62641186,0.00058254483,0.0029667956,0.0254635],"study_design_scores_gemma":[0.006139828,0.0045746295,0.8742714,0.00022884291,0.00059489947,0.0012685354,0.0003326456,0.08948746,0.017702844,0.0012742754,0.0020964853,0.0020281856],"about_ca_topic_score_codex":0.0000025375891,"about_ca_topic_score_gemma":0.000016477565,"teacher_disagreement_score":0.86987346,"about_ca_system_score_codex":0.000025217312,"about_ca_system_score_gemma":0.00006004999,"threshold_uncertainty_score":0.56683534},"labels":[],"label_agreement":null},{"id":"W2061310665","doi":"10.1142/s0218127405012302","title":"BIFURCATIONS IN GLASS NETWORKS","year":2005,"lang":"en","type":"article","venue":"International Journal of Bifurcation and Chaos","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"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 Victoria","funders":"","keywords":"Multistability; Intermittency; Bifurcation; Cascade; Sigmoid function; Period-doubling bifurcation; Mathematics; Statistical physics; Pitchfork bifurcation; Bifurcation theory; Artificial neural network; Nonlinear system; Computer science; Physics; Artificial intelligence; Mechanics","score_opus":0.005482150930350527,"score_gpt":0.2517728433148574,"score_spread":0.24629069238450685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061310665","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":[0.98280734,0.0018047123,0.0111415945,0.0035301833,0.0002687759,0.000045068533,0.0000018389857,0.0000027478993,0.0003977643],"genre_scores_gemma":[0.99665767,0.00095987896,0.00070289825,0.0004006491,0.0009872082,0.0000025755255,0.000019938765,0.0000070244314,0.0002621595],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99931824,0.000032802654,0.0003053862,0.00010034225,0.00016239169,0.00008083316],"domain_scores_gemma":[0.9994026,0.00000911821,0.00019184146,0.000086436914,0.0002564208,0.00005360608],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021398066,0.000067981986,0.00008603325,0.00016634617,0.000020470074,0.000025892865,0.00017240345,0.00006331083,0.000026017233],"category_scores_gemma":[0.00003435465,0.00006479278,0.000063807565,0.000087907574,0.00003057839,0.000012237654,0.000034787518,0.00007315105,0.0000031038185],"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":[0.0004731911,0.00077500095,0.25331774,0.000011402105,0.0010004501,0.000022151884,0.0007858045,0.22532052,0.106128536,0.0033824458,0.012855599,0.39592716],"study_design_scores_gemma":[0.004953581,0.00039738588,0.37025434,0.00013775496,0.00012604786,0.00071670976,0.0006373162,0.07972566,0.031189533,0.0006345937,0.510527,0.0007000973],"about_ca_topic_score_codex":0.000003904534,"about_ca_topic_score_gemma":0.000084165345,"teacher_disagreement_score":0.4976714,"about_ca_system_score_codex":0.00003187209,"about_ca_system_score_gemma":0.000045160043,"threshold_uncertainty_score":0.2642173},"labels":[],"label_agreement":null},{"id":"W2061854785","doi":"10.1038/srep04819","title":"Transittability of complex networks and its applications to regulatory biomolecular networks","year":2014,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":62,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Program for New Century Excellent Talents in University; Japan Society for the Promotion of Science; Council for Science and Technology Policy; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Controllability; Computer science; Complex network; Graph; Set (abstract data type); Kernel (algebra); Complex system; State (computer science); Biological network; Topology (electrical circuits); Theoretical computer science; Distributed computing; Algorithm; Mathematics; Artificial intelligence; Bioinformatics; Biology","score_opus":0.009837347896152477,"score_gpt":0.23997361847666288,"score_spread":0.2301362705805104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061854785","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":[0.7616835,0.0011358142,0.23612829,0.00005979231,0.00036042306,0.0004205928,0.0000016664085,0.000017315058,0.00019257302],"genre_scores_gemma":[0.99863416,0.000012126331,0.00067571737,0.00006475414,0.0001520922,0.000043095773,0.00013835913,0.000019209867,0.00026047343],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99799126,0.00010472167,0.00048768253,0.00088963954,0.00023862823,0.00028807856],"domain_scores_gemma":[0.9980662,0.000012260286,0.00020646001,0.0012492174,0.00024352275,0.00022237592],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013587116,0.00016315143,0.0002477043,0.00008662567,0.00019620293,0.000046393467,0.00016309229,0.00013577272,0.000017526749],"category_scores_gemma":[0.00005223014,0.00016527604,0.0001377998,0.00050768256,0.00023732004,0.0000041737653,0.00012461797,0.000054619275,0.0000015247281],"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":[0.000019976575,0.00009098561,0.008683341,0.000040776074,0.00010265765,0.000003946619,0.000037988535,0.10614506,0.8722257,0.00016232682,0.004149073,0.00833815],"study_design_scores_gemma":[0.00058817695,0.00032736943,0.06248639,0.00005907231,0.00039061203,0.00022961733,0.000065232955,0.16532798,0.3643737,0.0022001236,0.40259132,0.0013603959],"about_ca_topic_score_codex":0.0000038290227,"about_ca_topic_score_gemma":0.000026851705,"teacher_disagreement_score":0.507852,"about_ca_system_score_codex":0.000010794786,"about_ca_system_score_gemma":0.000041913736,"threshold_uncertainty_score":0.6739761},"labels":[],"label_agreement":null},{"id":"W2061902004","doi":"10.1016/j.jtbi.2004.07.012","title":"Intrinsic noise, gene regulation and steady-state statistics in a two-gene network","year":2004,"lang":"en","type":"article","venue":"Journal of Theoretical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Fano factor; Noise (video); Repressor; Statistics; Gene regulatory network; Physics; Statistical physics; Steady state (chemistry); Variance (accounting); Biology; Mathematics; Gene; Control theory (sociology); Computer science; Genetics; Shot noise; Control (management); Gene expression; Artificial intelligence; Chemistry","score_opus":0.004798344588068132,"score_gpt":0.24683648968817845,"score_spread":0.24203814510011032,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061902004","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":[0.94705904,0.0015724184,0.05074274,0.00026629193,0.00020070691,0.00008045629,0.000014061402,0.0000028657798,0.00006144182],"genre_scores_gemma":[0.9818278,0.00052752276,0.016757691,0.00019294498,0.0006134022,0.0000017523703,0.000045858025,0.000016942702,0.000016081176],"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99855864,0.00023371661,0.0005591808,0.00022994918,0.00010276453,0.00031576015],"domain_scores_gemma":[0.99911493,0.000051722654,0.00027422621,0.00020677492,0.00021064014,0.00014170863],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006892614,0.00016246909,0.00036159658,0.00010309406,0.0000423458,0.000015128486,0.00016258913,0.00013668406,0.000027109958],"category_scores_gemma":[0.00020961184,0.0001343497,0.000090824244,0.00017112069,0.0004638125,0.0000042872066,0.00010954566,0.00017900727,0.0000030638855],"study_design_candidate":"theoretical_or_conceptual","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":[0.0015912155,0.00023964935,0.034513406,0.000025137302,0.0005569656,0.00012913381,0.0001254173,0.095797956,0.6570768,0.19130932,0.0005891337,0.018045917],"study_design_scores_gemma":[0.005691232,0.0021364486,0.04067317,0.000065606895,0.00027064187,0.00084007415,0.000041303803,0.0010109597,0.12814398,0.8188611,0.0016394554,0.00062601303],"about_ca_topic_score_codex":0.000004903952,"about_ca_topic_score_gemma":0.000031764204,"teacher_disagreement_score":0.6275518,"about_ca_system_score_codex":0.000041946027,"about_ca_system_score_gemma":0.00009760839,"threshold_uncertainty_score":0.5478622},"labels":[],"label_agreement":null},{"id":"W2061999684","doi":"10.1016/j.ces.2011.03.029","title":"Parameter estimation in nonlinear chemical and biological processes with unmeasured variables from small data sets","year":2011,"lang":"en","type":"article","venue":"Chemical Engineering Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institutes of Natural Sciences","keywords":"Nonlinear system; Markov chain Monte Carlo; Algorithm; Estimation theory; Monte Carlo method; Mathematics; Random variable; Biological data; Mathematical optimization; Computer science; Applied mathematics; Statistics","score_opus":0.03304456234300235,"score_gpt":0.22462856424924796,"score_spread":0.1915840019062456,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061999684","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":[0.98643476,0.00022747488,0.013210138,0.000009189162,0.000014869452,0.000059314425,0.000011099994,0.000018129218,0.000014999252],"genre_scores_gemma":[0.84713686,0.000016844282,0.15268421,0.000015230335,0.00002643494,0.000006769282,0.000104613835,0.000007935092,0.0000011281089],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989335,0.0000063944553,0.00013823759,0.00056736526,0.00012049862,0.00023400347],"domain_scores_gemma":[0.99936754,0.000033285323,0.00003307476,0.0004106013,0.00005169261,0.00010383085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019470922,0.00013170367,0.0001358688,0.000038008293,0.00001989136,0.00002407223,0.00045996532,0.000104621984,0.0000036256515],"category_scores_gemma":[0.0007136309,0.000105129926,0.000011398455,0.00035075008,0.0002437185,0.000013717391,0.00025596446,0.000081102386,8.104221e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026872553,0.000038515784,0.004848839,0.000018221821,0.000015211333,0.0000022339918,0.000031548465,0.0012659421,0.9931484,0.0000046292994,0.0000045853726,0.0005950005],"study_design_scores_gemma":[0.00021761181,0.000030839652,0.0031332115,0.000039426817,0.000017872919,0.000011095983,0.000006986353,0.11509113,0.88115555,0.00005408892,0.00003189273,0.00021029495],"about_ca_topic_score_codex":0.000013553932,"about_ca_topic_score_gemma":0.0000031580485,"teacher_disagreement_score":0.13947406,"about_ca_system_score_codex":0.000013390238,"about_ca_system_score_gemma":0.0000972903,"threshold_uncertainty_score":0.42870742},"labels":[],"label_agreement":null},{"id":"W2062826454","doi":"10.1063/1.4807480","title":"Sensitive dependence on initial conditions in gene networks","year":2013,"lang":"en","type":"article","venue":"Chaos An Interdisciplinary Journal of Nonlinear Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Attractor; Limiting; Sigmoid function; Statistical physics; Perturbation (astronomy); Singular perturbation; Limit (mathematics); Mathematics; Gene regulatory network; Limit cycle; Applied mathematics; Physics; Computer science; Mathematical analysis; Gene; Biology; Gene expression; Artificial neural network; Genetics; Quantum mechanics","score_opus":0.012857141600868836,"score_gpt":0.31941765189711463,"score_spread":0.3065605102962458,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062826454","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":[0.9951333,0.00007455753,0.0039392887,0.00022481967,0.0002955077,0.00010365244,0.0000058840747,0.000003340489,0.0002196458],"genre_scores_gemma":[0.9970158,0.000032285174,0.001970946,0.00016324314,0.00074204034,0.0000040395307,0.000015403457,0.000013245935,0.00004301268],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984849,0.00009061064,0.00043211677,0.00033342882,0.00032958543,0.0003293715],"domain_scores_gemma":[0.9986885,0.000020709393,0.00026079486,0.00033066486,0.00046279296,0.00023649939],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006283524,0.00015685156,0.00021253793,0.00029352595,0.00023996846,0.000072439936,0.0005507782,0.00009029128,0.000049324834],"category_scores_gemma":[0.00004877159,0.00013393351,0.00012807657,0.00044447102,0.00048218228,0.000062283696,0.00037941794,0.00024706623,0.000018903916],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029455018,0.00071644096,0.0044791824,0.000007609079,0.00009608859,0.000283894,0.0008614539,0.16872306,0.8169468,0.00006170834,0.0007306638,0.0067985314],"study_design_scores_gemma":[0.001969508,0.0061954567,0.12562208,0.00033344654,0.000083225765,0.002378303,0.0039046586,0.33070892,0.5266544,0.000991304,0.00013398379,0.0010246827],"about_ca_topic_score_codex":0.0000049250875,"about_ca_topic_score_gemma":0.00003011769,"teacher_disagreement_score":0.29029238,"about_ca_system_score_codex":0.0000579599,"about_ca_system_score_gemma":0.00021005291,"threshold_uncertainty_score":0.546165},"labels":[],"label_agreement":null},{"id":"W2063397490","doi":"10.1063/1.1286997","title":"Combinatorial explosion in model gene networks","year":2000,"lang":"en","type":"article","venue":"Chaos An Interdisciplinary Journal of Nonlinear Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":94,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biological network; Boolean network; Computer science; Limit (mathematics); Gene regulatory network; Combinatorial explosion; Stability (learning theory); Theoretical computer science; Mathematics; Boolean function; Algorithm; Gene; Combinatorics; Biology","score_opus":0.012787653223869426,"score_gpt":0.29752254177389553,"score_spread":0.2847348885500261,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063397490","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":[0.9947525,0.0003595062,0.0041561057,0.00010164695,0.00035150527,0.000062437684,0.0000022575625,0.0000037601183,0.00021026422],"genre_scores_gemma":[0.9954402,0.0002062515,0.0032885524,0.000050293238,0.0008983784,0.0000017741474,0.000009037614,0.000017116909,0.000088430155],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983709,0.00006279807,0.00051068194,0.0003442677,0.0003702717,0.00034111794],"domain_scores_gemma":[0.99895465,0.000005974094,0.0001927983,0.00039591914,0.00021815505,0.00023247565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00097202946,0.00016146869,0.00024356932,0.00020819897,0.00021562589,0.000053239426,0.00081439747,0.00010525321,0.000048399594],"category_scores_gemma":[0.000016101889,0.00013955473,0.00015252411,0.00047558104,0.00031620258,0.000053454503,0.00033439905,0.00020910215,0.000004769399],"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":[0.00048284783,0.00044145645,0.0013493045,0.000004239816,0.000024251523,0.000047953505,0.00044316213,0.7842797,0.20126234,0.00002628419,0.0001821619,0.011456288],"study_design_scores_gemma":[0.0009835603,0.0011365622,0.0018473814,0.00006326331,0.000026492966,0.00023370497,0.00021557971,0.9620685,0.032123335,0.00081349886,0.00020040928,0.0002877414],"about_ca_topic_score_codex":0.0000011543833,"about_ca_topic_score_gemma":0.000009491953,"teacher_disagreement_score":0.17778875,"about_ca_system_score_codex":0.000056954843,"about_ca_system_score_gemma":0.00023119326,"threshold_uncertainty_score":0.5690876},"labels":[],"label_agreement":null},{"id":"W2063854986","doi":"10.1016/j.bpj.2010.03.058","title":"The Potential Landscape of Genetic Circuits Imposes the Arrow of Time in Stem Cell Differentiation","year":2010,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":264,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Air Force Office of Scientific Research; National Key Research and Development Program of China; National Natural Science Foundation of China; Canada Foundation for Innovation; National Cancer Institute; National Science Foundation; National Institutes of Health; University of Calgary","keywords":"Attractor; Reprogramming; Biology; Stem cell; Cellular differentiation; Branching process; Multipotent Stem Cell; Progenitor cell; Gene regulatory network; Cell fate determination; Asymmetry; Physics; Gene expression; Regulation of gene expression; Evolutionary biology; Gene; Cell biology; Statistical physics; Genetics; Transcription factor; Mathematics; Quantum mechanics","score_opus":0.003255349270753168,"score_gpt":0.19021166631580178,"score_spread":0.18695631704504861,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063854986","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":[0.9992153,0.00022970457,0.00023823023,0.000078419835,0.00013746863,0.00005459328,0.0000033998724,0.0000011391107,0.00004173987],"genre_scores_gemma":[0.99927473,0.00012409076,0.000023010114,0.0000074881214,0.00045776207,0.0000016785411,0.0000043976697,0.000009014464,0.00009782418],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991753,0.00009976753,0.00027960428,0.0001105476,0.00018490078,0.00014985958],"domain_scores_gemma":[0.99936014,0.000021228148,0.00024120872,0.0002458322,0.00008748105,0.000044079054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001612772,0.00008842143,0.0001333984,0.000027494716,0.00008315115,0.00002218247,0.00027965955,0.00007695266,0.000013454167],"category_scores_gemma":[0.000007942631,0.000050162253,0.0001795491,0.00010489296,0.000102446626,0.0000023303826,0.000053743664,0.00016063939,0.0000029514167],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019696874,0.00006353111,0.0039717583,0.000003930714,0.000044997305,8.649584e-7,0.00001952197,0.0004823827,0.9919689,0.0000074413715,0.00013774635,0.0032792091],"study_design_scores_gemma":[0.00038872907,0.0001384975,0.15738249,0.0000062892495,0.00007827758,0.000021859312,0.000042516094,0.003205689,0.83836025,0.0000997065,0.00018117037,0.0000945474],"about_ca_topic_score_codex":0.0000025331112,"about_ca_topic_score_gemma":0.000012620802,"teacher_disagreement_score":0.15360868,"about_ca_system_score_codex":0.0000032383366,"about_ca_system_score_gemma":0.000044415414,"threshold_uncertainty_score":0.20455573},"labels":[],"label_agreement":null},{"id":"W2064227389","doi":"10.4161/cc.9.19.13379","title":"Controlled chaos: New insights into genetically programmed cell cycle asynchrony","year":2010,"lang":"en","type":"letter","venue":"Cell Cycle","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"National Cancer Institute; National Institute of General Medical Sciences; McGill University","keywords":"Biology; Asynchrony (computer programming); Asynchronous communication; Cytoplasm; CHAOS (operating system); Cell cycle; Cell biology; Cell; Image (mathematics); Computational biology; Genetics; Artificial intelligence; Computer science","score_opus":0.003923846394634044,"score_gpt":0.2022611750072348,"score_spread":0.19833732861260076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064227389","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":[0.77566236,0.053777948,0.0065043513,0.12109977,0.0038923994,0.006031159,0.0000466293,0.00038537802,0.03259998],"genre_scores_gemma":[0.6819517,0.0017168932,0.0095380265,0.20877303,0.030638782,0.0004883143,0.0041724145,0.000736902,0.06198394],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99611795,0.0002351114,0.0007390214,0.001403211,0.0005324909,0.0009722106],"domain_scores_gemma":[0.99710125,0.00004099241,0.00045910646,0.0017933984,0.000201566,0.00040370584],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00018526595,0.0008356147,0.0010502642,0.00016678759,0.0001972984,0.00014731573,0.0009994217,0.0035584928,0.00031439713],"category_scores_gemma":[0.00003968238,0.000777416,0.00086954335,0.00022487219,0.00024036024,0.000004922937,0.00037454956,0.0018460974,0.00032898271],"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":[0.000107743006,0.0001565677,0.000045562214,0.0001511515,0.00033941193,0.000089912566,0.00007374609,0.00039651294,0.28610477,0.0000015881448,0.7086586,0.003874444],"study_design_scores_gemma":[0.0033280947,0.000260229,0.000034374676,0.00001672268,0.00048148038,0.0000065723902,0.000009979342,0.00076573115,0.115182154,0.00030408058,0.87871844,0.0008921373],"about_ca_topic_score_codex":0.000118571705,"about_ca_topic_score_gemma":0.00022756009,"teacher_disagreement_score":0.1709226,"about_ca_system_score_codex":0.000055361746,"about_ca_system_score_gemma":0.0005310471,"threshold_uncertainty_score":0.9994677},"labels":[],"label_agreement":null},{"id":"W2065576510","doi":"10.1089/cmb.2007.0185","title":"On the Sparse Reconstruction of Gene Networks","year":2008,"lang":"en","type":"article","venue":"Journal of Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"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 Calgary","funders":"","keywords":"Greedy algorithm; Heuristic; Computer science; Noise (video); Algorithm; Iterative method; Mathematical optimization; Computational biology; Theoretical computer science; Pattern recognition (psychology); Mathematics; Artificial intelligence; Biology","score_opus":0.013229108107174608,"score_gpt":0.2320361408289565,"score_spread":0.21880703272178187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065576510","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":[0.9558168,0.0006147121,0.04296158,0.00024058936,0.00021596033,0.000032169417,0.0000024073688,0.0000010926411,0.00011467822],"genre_scores_gemma":[0.99645966,0.0001456565,0.0027660185,0.0001969794,0.0003830805,6.879559e-7,0.000017376147,0.000005395034,0.000025133657],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9992495,0.00013983775,0.00034201992,0.000089428024,0.000090720765,0.00008848013],"domain_scores_gemma":[0.99907947,0.00009096022,0.00041650294,0.000103098464,0.0002765334,0.000033438853],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024826243,0.000073245275,0.00015866506,0.00006273096,0.00006169415,0.0000020412988,0.0001351144,0.00008836296,0.000028281735],"category_scores_gemma":[0.000061281375,0.00004921509,0.00015776703,0.00009671031,0.00017232882,0.0000018844233,0.000017841536,0.00008969994,0.0000017985308],"study_design_candidate":"simulation_or_modeling","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":[0.00020533167,0.000061473955,0.010694164,0.000001712896,0.00037571424,0.000004671488,0.000018749633,0.9446543,0.035092637,0.0016508913,0.003669068,0.0035713047],"study_design_scores_gemma":[0.008609679,0.012678757,0.37129936,0.00018687075,0.0007543483,0.021597173,0.0003280703,0.16086806,0.28568375,0.11088553,0.025310295,0.0017981002],"about_ca_topic_score_codex":9.076721e-7,"about_ca_topic_score_gemma":8.282496e-7,"teacher_disagreement_score":0.78378624,"about_ca_system_score_codex":0.000009234626,"about_ca_system_score_gemma":0.00008705133,"threshold_uncertainty_score":0.20069332},"labels":[],"label_agreement":null},{"id":"W2066534603","doi":"10.1109/acc.2008.4586737","title":"Model reduction and consistency in discrete event representation of biological systems","year":2008,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Concordia University","funders":"","keywords":"Petri net; Computer science; Consistency (knowledge bases); Representation (politics); Construct (python library); Theoretical computer science; Reduction (mathematics); Domain (mathematical analysis); Event (particle physics); Data mining; Distributed computing; Artificial intelligence; Programming language; Mathematics","score_opus":0.03348530274365948,"score_gpt":0.27333775869099175,"score_spread":0.23985245594733226,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066534603","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":[0.995072,0.00090220774,0.0035249256,0.000026741958,0.000023406928,0.00008620016,0.0000014459935,0.0000032087587,0.00035988545],"genre_scores_gemma":[0.9982953,0.00066090643,0.00047236434,0.000004572166,0.000029048966,0.0000084948615,0.000030412548,0.0000034443267,0.0004954663],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99943763,0.000052158408,0.00019431447,0.0001887493,0.000054065134,0.00007307392],"domain_scores_gemma":[0.9997288,0.0000029083294,0.000056733476,0.00015180508,0.000034395176,0.000025373492],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000078894576,0.00005535804,0.00011695934,0.00003313773,0.000022997534,0.0000019460851,0.000032065036,0.00007273547,0.0000021705832],"category_scores_gemma":[0.000016054888,0.00004530616,0.000041829273,0.000079313424,0.00008484016,0.0000017033137,0.00003168646,0.00002007767,3.2627582e-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":[0.00005280278,0.000040599974,0.06860746,0.000012099372,0.00004923627,0.0000016052123,0.00005717593,0.089054205,0.8411247,0.00041657325,0.0003323132,0.0002511919],"study_design_scores_gemma":[0.0018558335,0.0005881283,0.13384987,0.000048886952,0.00009142727,0.00040091935,0.0014891442,0.45370433,0.40625846,0.0007244567,0.00032977076,0.0006587699],"about_ca_topic_score_codex":0.00005507323,"about_ca_topic_score_gemma":0.0000105089875,"teacher_disagreement_score":0.43486628,"about_ca_system_score_codex":0.0000057236593,"about_ca_system_score_gemma":0.000019089095,"threshold_uncertainty_score":0.18475315},"labels":[],"label_agreement":null},{"id":"W2067203347","doi":"10.1504/ijdmb.2008.016753","title":"Gene Regulatory Network modelling: a state-space approach","year":2008,"lang":"en","type":"article","venue":"International Journal of Data Mining and Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Dalian University of Technology","keywords":"Principal component analysis; Gene regulatory network; Probabilistic logic; State variable; Computer science; Bayesian network; State (computer science); State space; Control (management); Bayesian information criterion; Expression (computer science); Statistical model; State-space representation; Data mining; Gene; Mathematics; Artificial intelligence; Gene expression; Biology; Statistics; Genetics; Algorithm; Physics","score_opus":0.041370472827446304,"score_gpt":0.2592375920972098,"score_spread":0.21786711926976352,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067203347","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":[0.76291573,0.0017224081,0.23458607,0.00008933654,0.00023727992,0.00004023766,0.000047609094,0.0000051375396,0.00035620324],"genre_scores_gemma":[0.58039874,0.0018305707,0.41652665,0.00010886557,0.0006442234,4.2884685e-7,0.00031239082,0.000010866353,0.00016725245],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988051,0.000027957647,0.0005048635,0.00013054512,0.00037387572,0.0001576655],"domain_scores_gemma":[0.99880755,0.000016155349,0.00045085666,0.00035216942,0.00027088367,0.00010236747],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049741147,0.0001240036,0.000176062,0.00008674233,0.000077033765,0.00004248806,0.0006353718,0.00007328115,0.0000025254103],"category_scores_gemma":[0.0000337456,0.00010591735,0.000068540154,0.000076486285,0.000093279545,0.00004825361,0.00033334535,0.00008366367,9.553498e-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":[0.0010225625,0.00043560236,0.039552327,0.00009095464,0.0053710323,0.00017371296,0.003559057,0.49991158,0.0064616343,0.000058041984,0.18937114,0.25399235],"study_design_scores_gemma":[0.0014562381,0.00027849423,0.0015595116,0.00008847141,0.00015168665,0.0034070238,0.0005056871,0.96579736,0.0034655281,0.00004563837,0.02279244,0.00045192806],"about_ca_topic_score_codex":0.000001972922,"about_ca_topic_score_gemma":0.0000013194981,"teacher_disagreement_score":0.4658858,"about_ca_system_score_codex":0.000013022514,"about_ca_system_score_gemma":0.00011432149,"threshold_uncertainty_score":0.43191844},"labels":[],"label_agreement":null},{"id":"W2068211838","doi":"10.1016/j.biosystems.2012.10.005","title":"Self-organization and entropy reduction in a living cell","year":2012,"lang":"en","type":"article","venue":"Biosystems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":106,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Cancer Institute; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Entropy (arrow of time); Living cell; Genetic code; DNA; Information theory; Living systems; Computer science; Context (archaeology); Theoretical computer science; Biological system; Statistical physics; Mathematics; Artificial intelligence; Biology; Thermodynamics; Statistics; Genetics; Physics","score_opus":0.0037632748140133798,"score_gpt":0.187550408012666,"score_spread":0.18378713319865264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068211838","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":[0.9962959,0.0031404882,0.00013261994,0.000010714961,0.0001772899,0.00008811096,6.3488864e-7,0.000012545861,0.00014168008],"genre_scores_gemma":[0.99875855,0.00020515495,0.00026356385,0.0000065329887,0.0005585361,0.0000039182396,0.000017294022,0.000013318767,0.00017310827],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994748,0.000062365114,0.00011891036,0.00014165365,0.000054445874,0.00014781451],"domain_scores_gemma":[0.99972844,0.0000027036874,0.000053555763,0.00013615243,0.00002810406,0.00005104132],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017401812,0.00007069342,0.00007659941,0.00004277095,0.000031856096,0.000013113419,0.000037787686,0.00008834763,0.000005239959],"category_scores_gemma":[0.000014512914,0.00007108755,0.000018612238,0.00014956438,0.0000079676165,0.0000042794472,0.00003714713,0.000022772172,0.0000078382045],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000018995082,0.000049086655,0.21981628,0.00004128837,0.000018024008,1.6504123e-7,0.00021899046,0.00002108617,0.7794215,0.00001852857,0.00029852006,0.000094642266],"study_design_scores_gemma":[0.000503019,0.00010511124,0.09489485,0.00005465559,0.00009508502,0.00011901036,0.0007965534,0.0006027814,0.8706399,0.0000033643564,0.031691063,0.00049461215],"about_ca_topic_score_codex":0.000008809386,"about_ca_topic_score_gemma":0.0000040812047,"teacher_disagreement_score":0.12492143,"about_ca_system_score_codex":0.000019642443,"about_ca_system_score_gemma":0.000012581233,"threshold_uncertainty_score":0.2898866},"labels":[],"label_agreement":null},{"id":"W2068271774","doi":"10.4161/sysb.24471","title":"Long loops of information flow in genetic networks highlight an inherent directionality","year":2013,"lang":"en","type":"article","venue":"Systems Biomedicine","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Directionality; Swap (finance); Computer science; Information flow; Degree distribution; Clustering coefficient; Genetic network; Flow network; Topology (electrical circuits); Enhanced Data Rates for GSM Evolution; Cluster analysis; Mathematics; Combinatorics; Gene; Complex network; Biology; Genetics; Artificial intelligence","score_opus":0.005115901732318648,"score_gpt":0.21427010465919472,"score_spread":0.20915420292687606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068271774","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":[0.98215985,0.002855451,0.013842445,0.00007439505,0.00045921176,0.00041861396,0.0000056324307,0.000012939329,0.00017145954],"genre_scores_gemma":[0.99855185,0.000097529264,0.00021078662,0.000041761992,0.0004766034,0.00006457584,0.00040396448,0.000010624526,0.00014229049],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986527,0.00013129058,0.0005828361,0.00020300136,0.00021867506,0.00021149113],"domain_scores_gemma":[0.99908924,0.000007467334,0.0002093278,0.00039909803,0.00018392951,0.00011093144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003129456,0.00014617128,0.00026631926,0.00016520476,0.000028984721,0.000016531394,0.00014528133,0.00016812328,0.000042547137],"category_scores_gemma":[0.00001756718,0.000121659046,0.00005751206,0.0003752603,0.000080099824,0.000015378722,0.000046838955,0.00005821127,0.000012271524],"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":[0.00014520664,0.00047425207,0.5796426,0.0007249965,0.000683071,0.000008022993,0.0003943756,0.20717652,0.12435224,0.0000911589,0.014616566,0.071690984],"study_design_scores_gemma":[0.0013634835,0.00044973096,0.869377,0.00015713854,0.00007029978,0.00003376006,0.0002345241,0.11051675,0.0044943774,0.000021770204,0.012920792,0.00036038048],"about_ca_topic_score_codex":0.00086067326,"about_ca_topic_score_gemma":0.00017152012,"teacher_disagreement_score":0.2897344,"about_ca_system_score_codex":0.000035386103,"about_ca_system_score_gemma":0.0000379314,"threshold_uncertainty_score":0.49611118},"labels":[],"label_agreement":null},{"id":"W2069227582","doi":"10.1007/s11047-004-2638-7","title":"Biomolecular swarms – an agent-based model of the lactose operon","year":2004,"lang":"en","type":"article","venue":"Natural Computing","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Theory of computation; Operon; Computer science; Biochemical engineering; Computational biology; Chemistry; Biology; Engineering; Biochemistry; Algorithm","score_opus":0.011513166261984002,"score_gpt":0.24892667939046695,"score_spread":0.23741351312848294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069227582","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":[0.97662216,0.0006761152,0.022341507,0.00010527652,0.000108039705,0.00009318796,0.0000024848475,0.00001248415,0.000038715945],"genre_scores_gemma":[0.99592155,0.000002695661,0.003569984,0.00032311145,0.000096861666,7.528542e-7,0.000036316982,0.000017909268,0.000030803614],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990927,0.000062386185,0.0001839542,0.00027505128,0.00018004567,0.00020584355],"domain_scores_gemma":[0.99929255,0.000003681371,0.00011092061,0.0004542811,0.00008742514,0.000051158026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001505624,0.00013454369,0.00012925033,0.000030858508,0.000119743556,0.0000146589055,0.00034723303,0.00010315411,0.0000012763862],"category_scores_gemma":[0.000023992052,0.000098822,0.00018429024,0.00017814114,0.00007170776,0.0000026960024,0.0001444131,0.00011180127,0.0000011308811],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000088554925,0.000022383108,0.0003390956,0.000005073521,0.000022968283,4.354956e-7,0.000016941995,0.43194726,0.5667897,0.000025821702,0.000013451095,0.0008080188],"study_design_scores_gemma":[0.0004656029,0.000056421883,0.00090912095,0.00001833835,0.00003551032,0.0000026765954,0.000017641998,0.28998598,0.70822823,0.00006515461,0.00007053204,0.00014477712],"about_ca_topic_score_codex":0.000020920674,"about_ca_topic_score_gemma":0.000035037938,"teacher_disagreement_score":0.14196129,"about_ca_system_score_codex":0.000025147143,"about_ca_system_score_gemma":0.000093885166,"threshold_uncertainty_score":0.4029844},"labels":[],"label_agreement":null},{"id":"W2069734863","doi":"10.1016/j.pbi.2004.07.001","title":"Systems approaches to understanding cell signaling and gene regulation","year":2004,"lang":"en","type":"review","venue":"Current Opinion in Plant Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Biology; Computational biology; Gene; Signal transduction; Regulation of gene expression; Cell biology; Genetics","score_opus":0.2534963240507159,"score_gpt":0.3292097881354352,"score_spread":0.0757134640847193,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069734863","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00015832423,0.9908786,0.006303932,0.000009004565,0.0018170216,0.0006569246,0.00014146067,0.000011663276,0.000023056971],"genre_scores_gemma":[0.0048794704,0.9883849,0.0001611839,0.0000020077482,0.00079120003,0.00010321386,0.005624094,0.000037242964,0.000016690177],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978422,0.00030259194,0.0006159457,0.00079843076,0.000085022584,0.0003558386],"domain_scores_gemma":[0.9991905,0.000037957332,0.000306899,0.0003333191,0.000012287842,0.00011905672],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003646017,0.00040033602,0.00089866127,0.0003377088,0.00006960753,0.00003362965,0.0002093787,0.00052940106,0.0000025716192],"category_scores_gemma":[0.000013545389,0.0003561035,0.00017649424,0.00025849752,0.000059818158,0.0000025313138,0.00017541714,0.00019290311,0.0000071084933],"study_design_candidate":"not_applicable","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":[0.00034228904,0.0010793501,0.002576244,0.24883693,0.002661324,0.00001194623,0.0006526593,0.05875458,0.0061912797,0.03936348,0.0070591946,0.6324707],"study_design_scores_gemma":[0.00032474322,0.00013951937,0.0000070718097,0.0070037157,0.00017193206,0.00006450635,0.00004097868,0.00021601615,0.00007113685,0.00018886404,0.99109983,0.000671687],"about_ca_topic_score_codex":0.0000068275904,"about_ca_topic_score_gemma":0.000002747851,"teacher_disagreement_score":0.9840406,"about_ca_system_score_codex":0.00018040538,"about_ca_system_score_gemma":0.00015876516,"threshold_uncertainty_score":0.9998891},"labels":[],"label_agreement":null},{"id":"W2070718329","doi":"10.1142/s0219720004000892","title":"IMPROVING GENE NETWORK INFERENCE BY COMPARING EXPRESSION TIME-SERIES ACROSS SPECIES, DEVELOPMENTAL STAGES OR TISSUES","year":2004,"lang":"en","type":"article","venue":"Journal of Bioinformatics and Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"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 Ottawa; Université de Montréal","funders":"","keywords":"Inference; Gene regulatory network; Computer science; Graph; Time series; Series (stratigraphy); Gene; Data mining; Computational biology; Gene expression; Biology; Artificial intelligence; Machine learning; Theoretical computer science; Genetics","score_opus":0.01041361670249012,"score_gpt":0.2526595291995905,"score_spread":0.2422459124971004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070718329","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":[0.90458393,0.0011742269,0.09396716,0.00006151083,0.0000839847,0.0000541952,0.000023950852,0.0000049618175,0.000046086418],"genre_scores_gemma":[0.86338276,0.0003013563,0.13564968,0.0001100525,0.00020394243,0.0000013124021,0.00022431325,0.000008130109,0.00011844076],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989986,0.000027697983,0.00052982447,0.00010624468,0.00012234152,0.00021530228],"domain_scores_gemma":[0.99922556,0.000028284605,0.00044097612,0.000064471635,0.00015273939,0.000087959525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023575746,0.00014373861,0.00025640932,0.000037539285,0.00017240808,0.000057448106,0.00014961678,0.00010428835,0.000013216221],"category_scores_gemma":[0.000038863927,0.000107899425,0.00005812121,0.00008502609,0.00012828544,0.000024974068,0.00016979492,0.00008679581,0.0000030960905],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009851005,0.00020890313,0.069329955,0.00014726413,0.00088051986,0.000020259398,0.0014282523,0.40176544,0.48555252,0.00041838826,0.0067675365,0.032495856],"study_design_scores_gemma":[0.016889518,0.009069947,0.072355516,0.0008000563,0.0004181207,0.0045259143,0.0055930456,0.06842452,0.6939567,0.012591272,0.11116198,0.004213407],"about_ca_topic_score_codex":0.0000031340553,"about_ca_topic_score_gemma":0.0000066030557,"teacher_disagreement_score":0.3333409,"about_ca_system_score_codex":0.000028845467,"about_ca_system_score_gemma":0.00015766374,"threshold_uncertainty_score":0.4400011},"labels":[],"label_agreement":null},{"id":"W2070813442","doi":"10.5555/1400549.1400635","title":"Modeling and simulating a disease outbreak by learning a contagion parameter-based model","year":2008,"lang":"en","type":"article","venue":"Spring Simulation Multiconference","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Outbreak; Computer science; Disease; Infectious disease (medical specialty); Emotional contagion; Process (computing); Epidemic model; Artificial intelligence; Econometrics; Machine learning; Medicine; Virology; Psychology; Mathematics; Environmental health; Social psychology","score_opus":0.027145293329674816,"score_gpt":0.26657081021464507,"score_spread":0.23942551688497027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070813442","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":[0.6070162,0.00019153173,0.39263386,0.000014495411,0.0000097620805,0.00009536217,0.0000025262996,0.000027753122,0.000008478498],"genre_scores_gemma":[0.9957187,0.000033612614,0.003945511,0.00007329577,0.000042181957,0.000011913386,0.00006146895,0.000030864074,0.00008244579],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99873763,0.0000804161,0.00027465064,0.0004737539,0.00017856206,0.00025498198],"domain_scores_gemma":[0.99924606,0.000060131028,0.00009539059,0.0002861734,0.00013537971,0.00017687086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012314986,0.00020589809,0.00018237598,0.000059408074,0.00027409228,0.000037159112,0.000098670236,0.000102719736,0.0000040863606],"category_scores_gemma":[0.00026259545,0.00022504797,0.00008721011,0.000061015973,0.00006669615,0.000012287563,0.00007820408,0.00012264085,0.0000027349718],"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":[0.00005716495,0.000025569818,0.051390674,0.0000133249005,0.000020722719,0.0000013534319,0.000051002047,0.91100585,0.036744207,0.000008987359,8.1283343e-7,0.0006803314],"study_design_scores_gemma":[0.0006597125,0.000032218562,0.0022268037,0.000026095677,0.000039948685,4.877387e-7,0.000016056758,0.9951694,0.0015052746,0.00002882783,0.000036108147,0.000259044],"about_ca_topic_score_codex":0.0000548498,"about_ca_topic_score_gemma":0.00001545857,"teacher_disagreement_score":0.38870248,"about_ca_system_score_codex":0.000020272502,"about_ca_system_score_gemma":0.00008205087,"threshold_uncertainty_score":0.917719},"labels":[],"label_agreement":null},{"id":"W2071691258","doi":"10.1016/j.tig.2005.06.013","title":"Network motifs are enriched with transcription factors whose transcripts have short half-lives","year":2005,"lang":"en","type":"article","venue":"Trends in Genetics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; Biotechnology Research Institute","funders":"Medical Research Council; Deutsche Forschungsgemeinschaft","keywords":"Biology; Transcription factor; Motif (music); Gene; Computational biology; Gene regulatory network; Genome; Network motif; Structural motif; Genetics; Transcription (linguistics); Gene expression; Biological network","score_opus":0.020565715942197364,"score_gpt":0.2502615199891589,"score_spread":0.22969580404696155,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071691258","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":[0.99057853,0.0055721113,0.002641017,0.00020233523,0.000108940694,0.00013293416,0.00001339214,0.000031285643,0.00071945897],"genre_scores_gemma":[0.9944262,0.00044153733,0.002592813,0.00013355362,0.000573083,0.000023684242,0.00030536158,0.00007120207,0.0014325771],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978985,0.00012415448,0.00041925718,0.0006607915,0.00029014843,0.0006071059],"domain_scores_gemma":[0.99902725,0.000008422211,0.00009721837,0.0006252293,0.000072473944,0.0001694052],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00015630973,0.00041210308,0.0003819747,0.00018143805,0.00009987052,0.000038683946,0.00030632492,0.00026153342,0.000060730406],"category_scores_gemma":[0.0000045274437,0.0003777191,0.00020458631,0.0004398751,0.00013002414,0.000008095686,0.00003359532,0.0001853641,0.0000036117176],"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":[0.00024723468,0.00036738065,0.43515107,0.000025728586,0.000412716,0.000019255289,0.0010902077,0.37683272,0.1443227,0.000020065496,0.002386376,0.039124526],"study_design_scores_gemma":[0.002516142,0.0010118997,0.8234792,0.00007702582,0.0006646745,0.000037594316,0.0011422889,0.01157794,0.10086831,0.00007704139,0.05671114,0.001836797],"about_ca_topic_score_codex":0.000016048314,"about_ca_topic_score_gemma":0.0036791319,"teacher_disagreement_score":0.38832808,"about_ca_system_score_codex":0.00005218814,"about_ca_system_score_gemma":0.000036398902,"threshold_uncertainty_score":0.9998675},"labels":[],"label_agreement":null},{"id":"W2072448219","doi":"10.1145/2808719.2808730","title":"The potential power of dynamics in epistasis analysis","year":2015,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Health Canada","keywords":"Epistasis; Identifiability; Computational biology; Computer science; Observable; Gene regulatory network; Biology; Genetics; Gene; Machine learning; Physics; Gene expression","score_opus":0.005608604210530582,"score_gpt":0.22837855065264553,"score_spread":0.22276994644211495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072448219","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":[0.9898864,0.000680505,0.0068526436,0.00019403391,0.000044271193,0.000043561882,0.0000047281396,0.0000030821632,0.002290768],"genre_scores_gemma":[0.9985371,0.00005376147,0.0003433874,0.000025407935,0.000022273805,0.0000027975318,0.000050861283,0.0000064485835,0.00095794786],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992664,0.00006919974,0.00020976206,0.0001679938,0.00013872058,0.00014791086],"domain_scores_gemma":[0.9993537,0.000006079706,0.000069304144,0.00040946322,0.00010403923,0.000057412268],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035080465,0.00007587445,0.00014227112,0.0000766897,0.000025350613,0.000010617386,0.00018156388,0.00007288723,0.0000151765935],"category_scores_gemma":[0.000033183944,0.00005392228,0.00018887686,0.00050117297,0.0000709475,0.0000010212028,0.000083124025,0.000032143544,0.0000025781058],"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":[0.00045359464,0.00042829715,0.6694952,0.000012901787,0.0084318295,0.000019356545,0.00017896917,0.23561732,0.05702011,0.005133556,0.012242655,0.0109661715],"study_design_scores_gemma":[0.0046543158,0.0011507579,0.3140618,0.000013739643,0.0049553965,0.000028137865,0.012998021,0.47429588,0.14564697,0.0038577255,0.036311377,0.0020258864],"about_ca_topic_score_codex":0.000093304625,"about_ca_topic_score_gemma":0.0027719398,"teacher_disagreement_score":0.35543343,"about_ca_system_score_codex":0.0000307522,"about_ca_system_score_gemma":0.00004846264,"threshold_uncertainty_score":0.21988867},"labels":[],"label_agreement":null},{"id":"W2073661114","doi":"10.1109/iembs.2010.5626506","title":"Identification of gene regulatory networks from time course gene expression data","year":2010,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Gene regulatory network; Inference; Computer science; Identification (biology); Computational biology; Gene; Constraint (computer-aided design); Gene expression; Regulation of gene expression; Systems biology; Regulator gene; Expression (computer science); Data mining; Biology; Artificial intelligence; Genetics; Mathematics","score_opus":0.007909618373417412,"score_gpt":0.23878797057954965,"score_spread":0.23087835220613223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073661114","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":[0.97046185,0.0009515059,0.027992137,0.000035171655,0.00022839042,0.000110260466,0.00008422222,0.000018788687,0.000117695025],"genre_scores_gemma":[0.9882312,0.00007005885,0.006297516,0.000042828844,0.0007009656,0.0000054508337,0.0033283455,0.000028912555,0.0012947255],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99858093,0.000063047104,0.0003901512,0.0005829611,0.00019713587,0.00018579556],"domain_scores_gemma":[0.99696237,0.000012073594,0.000245255,0.0025623576,0.00011927516,0.00009869505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003863315,0.0001545338,0.00019050171,0.00003082525,0.00006273002,0.00001928585,0.0006930019,0.0002704639,0.0002471295],"category_scores_gemma":[0.000030318,0.000145753,0.000086582746,0.000103541424,0.000106747066,0.000008454267,0.00031567176,0.00010042383,0.000026762873],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020393061,0.000057971785,0.0016147437,0.0000014349233,0.00008744371,5.5720284e-7,0.000004423152,0.0014249199,0.9853931,0.0000049070127,0.009745541,0.0016445805],"study_design_scores_gemma":[0.00019867565,0.000015146202,0.01256219,0.000003659262,0.00010586404,0.000002617639,0.000007200236,0.027319394,0.95832,0.000027042373,0.001275271,0.00016289494],"about_ca_topic_score_codex":0.000016266002,"about_ca_topic_score_gemma":0.000037326467,"teacher_disagreement_score":0.02707304,"about_ca_system_score_codex":0.0000038910757,"about_ca_system_score_gemma":0.000052699623,"threshold_uncertainty_score":0.5943635},"labels":[],"label_agreement":null},{"id":"W2073841094","doi":"10.1103/physreve.77.021908","title":"Effects of protein maturation on the noise in gene expression","year":2008,"lang":"en","type":"article","venue":"Physical Review E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"College of Family Physicians of Canada; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Gene expression; Protein expression; Fusion protein; Biology; Gene; Green fluorescent protein; Fluorescence; Fluorescent protein; Cell biology; Messenger RNA; Folding (DSP implementation); Genetics; Physics; Recombinant DNA","score_opus":0.008508542354228155,"score_gpt":0.24965487987036586,"score_spread":0.2411463375161377,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073841094","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":[0.98827726,0.011044336,0.000062806525,0.00014642718,0.000008146516,0.00037398605,4.648398e-7,0.0000020891348,0.000084495965],"genre_scores_gemma":[0.9951416,0.0043675224,0.000068955866,0.00017771666,0.00010132235,0.0000822987,0.0000101342075,0.000006726205,0.00004371574],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994276,0.00012388968,0.00011571115,0.00014286328,0.000110614186,0.00007928902],"domain_scores_gemma":[0.9996266,0.00001909769,0.00006809638,0.00024175196,0.000023451677,0.000021010983],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006574333,0.00007607931,0.0001571844,0.000009370044,0.00002338074,0.0000012358636,0.00009341682,0.000021982421,0.0000030478807],"category_scores_gemma":[0.000088890316,0.000046105226,0.00010595753,0.000111806934,0.000030855597,0.0000012636704,0.000032841166,0.00004791698,0.000009348827],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013408389,0.000076963406,0.00004257966,0.00017746662,0.0000073275096,0.0000010086017,0.000007192245,0.00004224461,0.9984409,0.000048080048,0.00039541186,0.00074738904],"study_design_scores_gemma":[0.00008186814,0.000058956593,0.0018813412,0.00042662,0.000014845739,7.0946584e-7,4.213055e-7,0.00007417213,0.99633396,0.00007521317,0.0009993454,0.00005254953],"about_ca_topic_score_codex":0.0000015053411,"about_ca_topic_score_gemma":4.8939404e-7,"teacher_disagreement_score":0.0068643596,"about_ca_system_score_codex":0.0000051592356,"about_ca_system_score_gemma":0.000013517903,"threshold_uncertainty_score":0.18801166},"labels":[],"label_agreement":null},{"id":"W2076130704","doi":"10.1016/j.biosystems.2005.09.009","title":"An analysis of the class of gene regulatory functions implied by a biochemical model","year":2005,"lang":"en","type":"article","venue":"Biosystems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Boolean network; Gene regulatory network; Gene; Computational biology; Biology; Function (biology); Repressor; Boolean function; Class (philosophy); Gene product; Network topology; Regulation of gene expression; Genetics; Computer science; Gene expression; Artificial intelligence; Algorithm","score_opus":0.006701873828978041,"score_gpt":0.22142895591072126,"score_spread":0.2147270820817432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076130704","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":[0.99538755,0.0012531239,0.0028348234,0.00004886096,0.000046256006,0.000118453376,0.00017196895,0.00000864367,0.00013031966],"genre_scores_gemma":[0.9988535,0.000014563907,0.00030815983,0.000040054503,0.00013385667,0.000011481364,0.0002263593,0.000017977693,0.00039402102],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99871755,0.00008359991,0.00044004802,0.0003464395,0.00023001964,0.00018232406],"domain_scores_gemma":[0.99839383,0.0000051219945,0.0002741708,0.0011093123,0.00013269877,0.00008485763],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021750745,0.00015056324,0.00033428386,0.00010377556,0.000054539785,0.0000067905526,0.00033976574,0.00020971335,0.000009949782],"category_scores_gemma":[0.000010238436,0.00011751853,0.00043099702,0.0005637335,0.00011280485,0.0000032146543,0.000058875987,0.000046390825,0.0000012742918],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018839602,0.00008676442,0.0038823218,0.000008809955,0.0008166866,2.4882821e-8,0.000020673564,0.0388609,0.9523516,0.000022658864,0.003784213,0.00014650407],"study_design_scores_gemma":[0.0001815883,0.000038159233,0.0033969209,0.0000055371415,0.00091293914,0.0000015597673,0.00006252784,0.106612355,0.88723564,0.0000017569644,0.0014158366,0.00013520356],"about_ca_topic_score_codex":0.000025729572,"about_ca_topic_score_gemma":0.00007109527,"teacher_disagreement_score":0.06775145,"about_ca_system_score_codex":0.000029565777,"about_ca_system_score_gemma":0.000066287685,"threshold_uncertainty_score":0.47922668},"labels":[],"label_agreement":null},{"id":"W2076590236","doi":"10.1007/s10955-005-7009-y","title":"Chaotic Dynamics in an Electronic Model of a Genetic Network","year":2005,"lang":"en","type":"article","venue":"Journal of Statistical Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria; McGill University","funders":"","keywords":"Chaotic; Ordinary differential equation; Piecewise linear function; Statistical physics; Computer science; Mathematics; Dynamics (music); Differential equation; Oscillation (cell signaling); Function (biology); Nonlinear system; Applied mathematics; Mathematical analysis; Physics; Artificial intelligence","score_opus":0.0068619904005244,"score_gpt":0.24668203539974554,"score_spread":0.23982004499922113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076590236","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":[0.5781854,0.0003547301,0.42132416,0.000034107852,0.000019089555,0.000035771536,0.000010039502,0.0000010380923,0.000035702997],"genre_scores_gemma":[0.96569663,0.00015246407,0.0334863,0.000058797494,0.00054594374,9.723063e-7,0.000020131072,0.000019747527,0.000019027178],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99879307,0.000069983435,0.00049231097,0.0001423732,0.00020365283,0.00029859343],"domain_scores_gemma":[0.9992569,0.000020431444,0.00026671824,0.00020067825,0.00015097727,0.00010427993],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020330153,0.00012188989,0.0002908957,0.000033843236,0.000019844962,0.000008389892,0.00018683291,0.00007829087,0.0000067598853],"category_scores_gemma":[0.000024120398,0.0001165419,0.00010223531,0.0001424938,0.00007366207,0.0000072814987,0.000035532972,0.00017355746,0.0000011022224],"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":[0.000095462994,0.00020089945,0.0045930925,0.000012960331,0.000085034146,0.0000033828549,0.00002146562,0.96777135,0.008502277,0.0077957497,0.00024340213,0.0106749],"study_design_scores_gemma":[0.0004958081,0.0005515604,0.0036802369,0.000016690508,0.00011520391,0.0000133380545,0.000022893806,0.97199017,0.000936195,0.02195462,0.00006985564,0.00015341422],"about_ca_topic_score_codex":0.0000020917444,"about_ca_topic_score_gemma":0.00012410738,"teacher_disagreement_score":0.38783786,"about_ca_system_score_codex":0.00009413324,"about_ca_system_score_gemma":0.00019632676,"threshold_uncertainty_score":0.4752441},"labels":[],"label_agreement":null},{"id":"W2077720193","doi":"10.1016/j.jtbi.2007.04.020","title":"Noisy attractors and ergodic sets in models of gene regulatory networks","year":2007,"lang":"en","type":"article","venue":"Journal of Theoretical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":104,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Ergodic theory; Attractor; Gene regulatory network; Boolean network; Statistical physics; Noise (video); Computer science; Set (abstract data type); Stochastic process; State (computer science); Mathematics; Physics; Boolean function; Gene; Algorithm; Biology; Artificial intelligence; Pure mathematics; Gene expression; Genetics; Statistics; Mathematical analysis","score_opus":0.007100353387720793,"score_gpt":0.2488492284213301,"score_spread":0.24174887503360928,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2077720193","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":[0.96576434,0.0042147827,0.029523198,0.00007876258,0.00013070871,0.00004927466,0.0000023354253,0.0000016495894,0.00023494667],"genre_scores_gemma":[0.99741054,0.00049045694,0.0017448025,0.000097135824,0.00022653527,4.497289e-7,0.000008162281,0.000014197477,0.00000771584],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985583,0.0001713573,0.0006706694,0.00019731287,0.00010553855,0.00029685322],"domain_scores_gemma":[0.9990801,0.00008892537,0.000321932,0.00022886605,0.00012907121,0.00015105541],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014952658,0.00014599046,0.0003992394,0.00015800874,0.000020939695,0.000004193215,0.00020445915,0.00036668396,0.000019953139],"category_scores_gemma":[0.00009863065,0.00011629048,0.00017272023,0.00013900085,0.00067273853,0.0000045287265,0.00007863227,0.00020393195,3.0430385e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013892031,0.00024352103,0.05288038,0.000021127906,0.0004241692,0.000051476065,0.00008343023,0.016390048,0.84589314,0.06880339,0.00023001674,0.013590074],"study_design_scores_gemma":[0.005391265,0.0046389373,0.16226281,0.00019213803,0.0006109395,0.0013878709,0.0003233677,0.023285594,0.6558878,0.14359081,0.0011514237,0.0012770353],"about_ca_topic_score_codex":0.0000019398349,"about_ca_topic_score_gemma":0.0000083303,"teacher_disagreement_score":0.19000536,"about_ca_system_score_codex":0.000019136243,"about_ca_system_score_gemma":0.00004346719,"threshold_uncertainty_score":0.47421882},"labels":[],"label_agreement":null},{"id":"W2078008084","doi":"10.1126/science.1242063","title":"Control Profiles of Complex Networks","year":2014,"lang":"en","type":"article","venue":"Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":394,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Complex network; Computer science; Statistic; Control (management); Complex system; Distributed computing; Topology (electrical circuits); Network topology; Function (biology); Small-world network; Control system; Control function; Artificial intelligence; Computer network; Mathematics; Engineering; Statistics; Biology","score_opus":0.0073142157131668405,"score_gpt":0.2333693393838749,"score_spread":0.22605512367070807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078008084","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":[0.9372329,0.00019836631,0.061057337,0.000059655125,0.0000775818,0.000073687115,0.0000016494529,0.000006152809,0.001292661],"genre_scores_gemma":[0.99885017,0.000006255707,0.0007942744,0.00011938697,0.00011997745,0.0000029701807,0.0000050145068,0.0000039256133,0.00009802632],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99931884,0.0000319363,0.000108586995,0.00021579745,0.00014638073,0.00017845086],"domain_scores_gemma":[0.9994563,0.0000065150957,0.00006560375,0.00031075563,0.00010313776,0.00005768689],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046669424,0.000057109715,0.00009409039,0.000031886164,0.00007275124,0.000010259249,0.00029219862,0.00003214541,0.000014536388],"category_scores_gemma":[0.000058469253,0.000049338814,0.000046882727,0.00023045672,0.0004572779,0.0000019173885,0.00006238182,0.000021831389,0.0000030932365],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007649169,0.000012001883,0.014686626,0.00000274802,0.000010126883,6.475132e-8,0.000004240469,0.016371798,0.9650748,0.0003613531,0.0004177488,0.0030508474],"study_design_scores_gemma":[0.00084769033,0.00038253525,0.19240047,0.0000138165915,0.00005401003,0.000007667399,0.000030045529,0.30521497,0.46131948,0.00029748792,0.03906168,0.0003701445],"about_ca_topic_score_codex":0.0000027873928,"about_ca_topic_score_gemma":0.0000050137087,"teacher_disagreement_score":0.50375533,"about_ca_system_score_codex":0.000004010791,"about_ca_system_score_gemma":0.0000435721,"threshold_uncertainty_score":0.20119783},"labels":[],"label_agreement":null},{"id":"W2078334027","doi":"10.1101/gad.189035.112","title":"Synthetic memory circuits for tracking human cell fate","year":2012,"lang":"en","type":"article","venue":"Genes & Development","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":76,"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; Hansjörg Wyss Institute for Biologically Inspired Engineering, Harvard University; Harvard University; Center for the Environment, Harvard University; Defense Advanced Research Projects Agency; Advanced Research Projects Agency; National Institutes of Health; National Science Foundation","keywords":"Biology; Cell fate determination; Cell biology; Cell; Population; Neuroscience; Computational biology; Gene; Genetics; Transcription factor","score_opus":0.02000548528847,"score_gpt":0.24730301600544902,"score_spread":0.227297530716979,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078334027","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":[0.98702866,0.0059031504,0.0057482473,0.000021080676,0.00024429863,0.00025174228,0.0000028127563,0.000019996287,0.00078001415],"genre_scores_gemma":[0.99411774,0.0000709187,0.0032697634,0.00010501265,0.0004328489,0.00010616362,0.00012831947,0.000042083037,0.0017271513],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998688,0.000038157978,0.00027709818,0.00033822603,0.00014537679,0.0005131662],"domain_scores_gemma":[0.999339,0.0000076558645,0.00009979077,0.00033230078,0.00007727478,0.00014398685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037192804,0.00020148436,0.00017555301,0.000055972854,0.00023025644,0.000020875217,0.00019533082,0.00012165091,0.000031879525],"category_scores_gemma":[0.000008623321,0.00020397939,0.00012842061,0.000076501994,0.000029395567,0.0000041972958,0.00009361904,0.00003690913,0.000032872253],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000058836995,0.000086133965,0.0055647218,0.000050154984,0.0001417841,5.629042e-7,0.00028470551,0.00031420085,0.9246416,0.000015320775,0.0009302632,0.06796464],"study_design_scores_gemma":[0.00024378003,0.000024372532,0.007357505,0.000008097565,0.000057391237,0.000005366802,0.00008392269,0.000011295332,0.8661088,0.000012908155,0.1257974,0.00028918503],"about_ca_topic_score_codex":0.0000015480584,"about_ca_topic_score_gemma":0.000011413547,"teacher_disagreement_score":0.12486714,"about_ca_system_score_codex":0.000038714537,"about_ca_system_score_gemma":0.00008093951,"threshold_uncertainty_score":0.8318038},"labels":[],"label_agreement":null},{"id":"W2078723335","doi":"10.1371/journal.pcbi.1001069","title":"Gene Expression Noise in Spatial Patterning: hunchback Promoter Structure Affects Noise Amplitude and Distribution in Drosophila Segmentation","year":2011,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":85,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria; British Columbia Institute of Technology","funders":"National Center for Research Resources; National Institute of General Medical Sciences; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; British Columbia Institute of Technology; Fundação de Amparo à Pesquisa do Estado de São Paulo; National Institutes of Health; National Science Foundation","keywords":"Drosophila embryogenesis; Biology; Gap gene; Mutant; Regulation of gene expression; Drosophila melanogaster; Noise (video); Gene expression; Genetics; Gene; Transcription factor; Promoter; Cell biology; Computer science","score_opus":0.012781269399537984,"score_gpt":0.23211068184200573,"score_spread":0.21932941244246773,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078723335","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":[0.9892345,0.00016713637,0.010156185,0.00004746644,0.000052078765,0.00025544022,0.000070511625,0.000008226707,0.000008453314],"genre_scores_gemma":[0.9929062,0.00001687821,0.003095602,0.00007338564,0.00011265588,0.000028541544,0.003749921,0.000013291143,0.000003492228],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9988326,0.00018555149,0.0002387814,0.0004462582,0.000088726345,0.0002080789],"domain_scores_gemma":[0.9996224,0.00002018198,0.00011618077,0.0001324743,0.000051835723,0.00005693198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009291972,0.0001676357,0.00018270333,0.00008295559,0.000042156065,0.000010711153,0.00009189422,0.00019563394,0.000026890375],"category_scores_gemma":[0.000025058971,0.00016123336,0.000038111655,0.0001032608,0.00007484174,0.000007669081,0.00010392769,0.00009651139,0.0000026108032],"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":[0.000091431204,0.00008693115,0.34746507,0.000016240207,0.000022761673,0.0000036890713,0.00012246726,0.0035495998,0.64769065,0.000017256698,0.000015391039,0.00091848295],"study_design_scores_gemma":[0.001022106,0.00021066373,0.70991933,0.000024750947,0.000020130623,0.000010919773,0.000016414195,0.0047939783,0.28189096,0.0018430948,0.000017247916,0.00023039084],"about_ca_topic_score_codex":0.000029947243,"about_ca_topic_score_gemma":0.000089775385,"teacher_disagreement_score":0.36579973,"about_ca_system_score_codex":0.000035768975,"about_ca_system_score_gemma":0.00003352545,"threshold_uncertainty_score":0.65749055},"labels":[],"label_agreement":null},{"id":"W2079182920","doi":"10.1038/nrg2886","title":"Stochasticity versus determinism in development: a false dichotomy?","year":2010,"lang":"en","type":"review","venue":"Nature Reviews Genetics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":46,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Wellcome Trust","keywords":"Biology; Determinism; Interpretation (philosophy); Expression (computer science); Epistemology; Evolutionary biology; Linguistics; Philosophy; Computer science","score_opus":0.033696482389804286,"score_gpt":0.34672632472782433,"score_spread":0.31302984233802006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079182920","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00023138686,0.99684006,0.00020562625,0.0000036885126,0.0008681506,0.0015633142,0.000022051161,0.000015033295,0.0002506627],"genre_scores_gemma":[0.00007715141,0.9927274,0.0048468057,0.000071892035,0.00087874394,0.00036459588,0.0006274143,0.00014153893,0.00026448542],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99580103,0.00043552023,0.0015114859,0.0012138705,0.0003563036,0.0006818013],"domain_scores_gemma":[0.9972236,0.000058822046,0.00081507216,0.0015349376,0.000108804896,0.00025872607],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00083488395,0.0010020545,0.0025754655,0.00029542224,0.00009817822,0.000051689956,0.0010579609,0.0032813954,0.000028834433],"category_scores_gemma":[0.0003265693,0.0008527619,0.0010118155,0.0006617308,0.00010760403,0.0000027304543,0.00043401506,0.001968202,0.00012038111],"study_design_candidate":"design_other","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":[0.000010836372,0.00005019633,0.000010759178,0.0032258139,0.00015416993,0.00000820169,0.000010333295,0.000006570845,0.00006268634,0.0000039475544,0.00041397923,0.9960425],"study_design_scores_gemma":[0.00036361412,0.00006827578,0.000011427285,0.0027785946,0.0008194914,0.000023030674,0.0000012629858,0.0000066381804,0.00012704196,0.0000033530878,0.99496275,0.00083449483],"about_ca_topic_score_codex":7.939608e-7,"about_ca_topic_score_gemma":0.00027571144,"teacher_disagreement_score":0.995208,"about_ca_system_score_codex":0.000098692195,"about_ca_system_score_gemma":0.00073299586,"threshold_uncertainty_score":0.99939233},"labels":[],"label_agreement":null},{"id":"W2080094927","doi":"10.1039/c4mb00526k","title":"Investigating the functional implications of reinforcing feedback loops in transcriptional regulatory networks","year":2014,"lang":"en","type":"article","venue":"Molecular BioSystems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Occupational Cancer Research Centre; Canadian Sugar Institute; University of Toronto","funders":"","keywords":"Network motif; Gene regulatory network; Computational biology; microRNA; Biology; Systems biology; Transcription factor; Positive feedback; Epigenetics; Regulation of gene expression; Computer science; Gene; Biological network; Genetics; Gene expression","score_opus":0.0092181487460618,"score_gpt":0.20571205866214992,"score_spread":0.19649390991608812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080094927","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":[0.9473173,0.0012887906,0.050032813,0.0003367835,0.00013808503,0.00022415469,0.0000047820427,0.000011953607,0.0006453599],"genre_scores_gemma":[0.99888426,0.000012535654,0.00028221303,0.00023735361,0.00025135075,0.000043503547,0.00014360808,0.000027400049,0.00011778151],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99842876,0.00023744268,0.0004982192,0.0003477866,0.00022821508,0.00025959272],"domain_scores_gemma":[0.9989213,0.000024143006,0.00020939324,0.00064259634,0.00012587108,0.000076717726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007188133,0.00017596595,0.00021339682,0.00008238626,0.0001094549,0.000021557304,0.000261627,0.0001756121,0.000010141104],"category_scores_gemma":[0.00006181667,0.00015160505,0.00019675358,0.0003779778,0.0001476623,0.000004627803,0.00006168545,0.00012146064,0.0000030680683],"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":[0.0000080836835,0.000016249565,0.019259196,0.00002621882,0.00008266494,2.2865554e-7,0.000022303606,0.14043958,0.8352038,0.00387051,0.0004424547,0.00062866486],"study_design_scores_gemma":[0.0024776352,0.000379458,0.53447324,0.00033304712,0.00027026498,0.000113656606,0.00035069344,0.10468316,0.3357829,0.0013132079,0.018578438,0.0012442982],"about_ca_topic_score_codex":0.000032084787,"about_ca_topic_score_gemma":0.000086418644,"teacher_disagreement_score":0.515214,"about_ca_system_score_codex":0.000027392525,"about_ca_system_score_gemma":0.000069895155,"threshold_uncertainty_score":0.6182275},"labels":[],"label_agreement":null},{"id":"W2081003219","doi":"10.1016/j.crvi.2003.11.009","title":"Modeling operon dynamics: the tryptophan and lactose operons as paradigms","year":2004,"lang":"en","type":"article","venue":"Comptes Rendus Biologies","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"trp operon; Humanities; Operon; Philosophy; Biology; Genetics; Gene","score_opus":0.015719728252523144,"score_gpt":0.24932286392354658,"score_spread":0.23360313567102342,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081003219","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":[0.98153603,0.014845596,0.002197877,0.0007198942,0.00008886099,0.00013094369,0.00001178796,0.00003727889,0.00043174095],"genre_scores_gemma":[0.9955081,0.003274996,0.0005927691,0.00017002666,0.00013190141,0.0000208586,0.0001317248,0.00001768293,0.00015195277],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989716,0.00007160701,0.00019051351,0.00039865842,0.00007617331,0.00029148196],"domain_scores_gemma":[0.99933654,0.000016824075,0.000048070182,0.00049644476,0.000037826532,0.00006426749],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013566366,0.00020871316,0.00019649998,0.00003322056,0.00022355895,0.000057379355,0.00035866335,0.00017332994,0.000016694234],"category_scores_gemma":[0.000054713077,0.00013718891,0.00009970519,0.000092850656,0.00024616133,0.0000045154848,0.00030454755,0.000118271004,0.00002315226],"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":[0.00024002728,0.0002057509,0.016479533,0.000040015817,0.001043345,0.000018507228,0.00037653945,0.6088204,0.32790446,0.0051595042,0.001789549,0.037922412],"study_design_scores_gemma":[0.008616483,0.005039953,0.02241154,0.000337998,0.0010538939,0.0007633937,0.013648798,0.4668454,0.38503155,0.02824968,0.06210879,0.0058925482],"about_ca_topic_score_codex":0.00010772399,"about_ca_topic_score_gemma":0.00018502442,"teacher_disagreement_score":0.14197496,"about_ca_system_score_codex":0.000030810304,"about_ca_system_score_gemma":0.00004869217,"threshold_uncertainty_score":0.55944014},"labels":[],"label_agreement":null},{"id":"W2081146885","doi":"10.1038/nbt0209-149","title":"Knocking sense into regulatory pathways","year":2009,"lang":"en","type":"article","venue":"Nature Biotechnology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Sense (electronics); Computational biology; Biology; Chemistry","score_opus":0.0036194355303219464,"score_gpt":0.21864757733886017,"score_spread":0.21502814180853821,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081146885","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":[0.9853866,0.008877889,0.0008482116,0.0036454673,0.00024021594,0.0001273906,0.0000029416601,0.00017381854,0.00069746084],"genre_scores_gemma":[0.9944922,0.00025871387,0.0028479975,0.0016891132,0.00040116112,0.0000040704053,0.0000590614,0.000024569203,0.00022315611],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985413,0.00005208248,0.00022574214,0.0006354173,0.00015957856,0.00038589758],"domain_scores_gemma":[0.9987223,0.0000060588777,0.00011101324,0.0010012316,0.000079872894,0.00007949376],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00018926625,0.00024383685,0.00024083779,0.00019445596,0.00013037889,0.000014332539,0.00031053516,0.0023863744,0.000013246987],"category_scores_gemma":[0.000101480546,0.00023868792,0.00017286856,0.0003748672,0.00014371677,0.0000029362461,0.00013566007,0.000582891,0.000022156302],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002972361,0.0000372398,0.00017668182,0.000004342605,0.00006453091,0.00002300244,0.0000133026815,0.00007269013,0.9557511,0.0044869296,0.0063899364,0.0329505],"study_design_scores_gemma":[0.00030741462,0.00026951468,0.002421695,0.000009906173,0.00003982482,0.000103210805,0.00004075425,0.00010910451,0.8272692,0.0026113745,0.16648228,0.00033571688],"about_ca_topic_score_codex":0.0000021177593,"about_ca_topic_score_gemma":0.000022283884,"teacher_disagreement_score":0.16009235,"about_ca_system_score_codex":0.00003944586,"about_ca_system_score_gemma":0.00006023551,"threshold_uncertainty_score":0.99890876},"labels":[],"label_agreement":null},{"id":"W2081172240","doi":"10.1109/tcbb.2011.60","title":"Reverse Engineering and Analysis of Genome-Wide Gene Regulatory Networks from Gene Expression Profiles Using High-Performance Computing","year":2011,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Computational Biology and Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"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":"Institute of Genetics; Erasmus+; Fondazione Telethon","keywords":"Gene; Gene regulatory network; Computational biology; Genome; Biology; Gene expression; DNA microarray; Regulation of gene expression; Reverse engineering; Cluster analysis; Genetics; Pairwise comparison; Computer science; Artificial intelligence","score_opus":0.01262603156760239,"score_gpt":0.2157993412607598,"score_spread":0.20317330969315742,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081172240","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":[0.5499197,0.00016957417,0.44971845,0.0000032789744,0.0000580373,0.000062627354,0.00005714115,0.000009132343,0.0000020070008],"genre_scores_gemma":[0.8000928,0.00016959464,0.19923675,0.000057430403,0.000042166303,0.0000027663175,0.00038534508,0.000009846652,0.0000032826483],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99895215,0.000049139962,0.00046157514,0.0002536728,0.00009402732,0.00018945958],"domain_scores_gemma":[0.99924296,0.00007856991,0.00022509856,0.0002736521,0.000100378646,0.0000793338],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017657409,0.00020055911,0.00031493307,0.00025794524,0.00017373025,0.000010037929,0.0001318083,0.00023723545,0.000012039419],"category_scores_gemma":[0.000009559814,0.00018962064,0.00009950002,0.00030090648,0.00014476929,0.000017212662,0.000025455745,0.00011965062,5.889062e-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":[0.00006540882,0.000036918773,0.009839241,0.000020467727,0.00086287997,4.4438895e-7,0.00016608884,0.93784255,0.04815866,0.0000049980617,0.0000028285326,0.0029995407],"study_design_scores_gemma":[0.00030985783,0.00012037516,0.07705822,0.000025052792,0.000513252,0.000006486971,0.000044892015,0.8357942,0.08586375,0.000036640984,0.0000073902115,0.00021988655],"about_ca_topic_score_codex":0.000017649405,"about_ca_topic_score_gemma":0.000003061738,"teacher_disagreement_score":0.25048172,"about_ca_system_score_codex":0.000015376383,"about_ca_system_score_gemma":0.000029998397,"threshold_uncertainty_score":0.7732505},"labels":[],"label_agreement":null},{"id":"W2081466838","doi":"10.1371/journal.pone.0002456","title":"Critical Dynamics in Genetic Regulatory Networks: Examples from Four Kingdoms","year":2008,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":232,"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 Calgary","funders":"National Institute of General Medical Sciences","keywords":"Robustness (evolution); Adaptability; Gene regulatory network; Systems biology; Organism; Boolean network; Network dynamics; Computer science; Generality; Biology; Computational biology; Biological network; Evolutionary dynamics; Gene; Genetics; Mathematics; Gene expression; Population; Ecology","score_opus":0.03144954516924011,"score_gpt":0.2192329958183487,"score_spread":0.1877834506491086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081466838","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":[0.9922981,0.0029872528,0.0041913595,0.000101372556,0.0000509441,0.00012442577,0.000013448349,0.000024942183,0.00020811781],"genre_scores_gemma":[0.9910203,0.0006072568,0.0070644896,0.00017086588,0.0006548002,0.00002804158,0.00017465054,0.00004990885,0.00022967652],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982685,0.00013106564,0.00034375815,0.0005438099,0.0002922133,0.0004206599],"domain_scores_gemma":[0.9989606,0.000051442003,0.00006538091,0.0006792209,0.00009835089,0.0001450105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011763679,0.00021640242,0.00033334264,0.00007500132,0.00009936874,0.00001746029,0.00026415105,0.00026155004,0.00006269531],"category_scores_gemma":[0.00013817368,0.00024233511,0.00012047834,0.00019393941,0.00021384675,0.000004635648,0.0001462443,0.00015202827,0.000017385855],"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":[0.00015488708,0.0017343152,0.8160779,0.00005584341,0.0010414497,0.00019173972,0.00006983455,0.01710162,0.16084303,0.00036202822,0.0010976085,0.0012697349],"study_design_scores_gemma":[0.0015533969,0.00035192625,0.7260908,0.00021932575,0.0005686383,0.00004411803,0.00010272971,0.22595108,0.04207398,0.0011603697,0.00057513895,0.0013084929],"about_ca_topic_score_codex":0.00009425133,"about_ca_topic_score_gemma":0.0006424411,"teacher_disagreement_score":0.20884946,"about_ca_system_score_codex":0.00007747819,"about_ca_system_score_gemma":0.00006148086,"threshold_uncertainty_score":0.9882139},"labels":[],"label_agreement":null},{"id":"W2082946409","doi":"10.1371/journal.pcbi.1000064","title":"Implementing Arithmetic and Other Analytic Operations By Transcriptional Regulation","year":2008,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Science Foundation","keywords":"Computation; Multiplication (music); Subtraction; Computer science; Arithmetic; Expression (computer science); Theoretical computer science; Arbitrary-precision arithmetic; Transcription (linguistics); Algorithm; Simple (philosophy); Interpretation (philosophy); Mathematics","score_opus":0.0181923529846822,"score_gpt":0.25136870238406156,"score_spread":0.23317634939937937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2082946409","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":[0.9373368,0.00076784985,0.061224233,0.00027373718,0.00002544915,0.00010916814,0.00006649917,0.000014454515,0.00018179645],"genre_scores_gemma":[0.990624,0.000028618711,0.007284424,0.00041785464,0.00013644891,0.00001770019,0.0012149485,0.00001376622,0.0002622446],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99905324,0.00008951177,0.00023286682,0.00032345235,0.00009602168,0.0002049021],"domain_scores_gemma":[0.99966645,0.000021558933,0.000046776655,0.00010761934,0.00010011657,0.000057452315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011120278,0.00011913886,0.00013268745,0.00006926309,0.0002642793,0.000010164461,0.00006603322,0.00007372023,0.000098237244],"category_scores_gemma":[0.000019270074,0.00012026273,0.00006137296,0.00010969101,0.00014364571,0.000004536792,0.00003991484,0.00004603058,0.000008549564],"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":[0.00003772046,0.0001718373,0.10778707,0.000012574346,0.0006106971,0.0000011583976,0.00011001291,0.065875545,0.8132038,0.008687673,0.0025476073,0.0009542754],"study_design_scores_gemma":[0.003716695,0.0007340813,0.22604801,0.000024258607,0.00043952154,0.00039251646,0.00012518602,0.5955865,0.03688453,0.007610796,0.126916,0.0015219158],"about_ca_topic_score_codex":0.000015931151,"about_ca_topic_score_gemma":0.000033567274,"teacher_disagreement_score":0.77631927,"about_ca_system_score_codex":0.000012172789,"about_ca_system_score_gemma":0.00005084945,"threshold_uncertainty_score":0.49041718},"labels":[],"label_agreement":null},{"id":"W2083265547","doi":"10.1109/ccece.2014.6901004","title":"Structural analysis of Petri nets for modeling and analyzing signaling pathways","year":2014,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Petri net; MAPK/ERK pathway; Ode; Computer science; Computational biology; Epidermal growth factor receptor; Signal transduction; Drug discovery; Cancer; Biology; Bioinformatics; Cell biology; Distributed computing; Mathematics; Genetics","score_opus":0.014811826512523548,"score_gpt":0.23526580347603068,"score_spread":0.22045397696350713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2083265547","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":[0.79638684,0.00043476914,0.20302781,0.000012268054,0.00001501736,0.000051645755,0.000005629355,0.0000055764276,0.00006042842],"genre_scores_gemma":[0.9933569,0.000024098334,0.006320127,0.000039488135,0.00008101005,0.000004102229,0.000120228935,0.000012361328,0.000041718456],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991256,0.000038529244,0.00025906257,0.00031178817,0.000086253975,0.00017879401],"domain_scores_gemma":[0.999435,0.000024033297,0.00009677332,0.00025673708,0.00012198721,0.00006544579],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028480164,0.000121215744,0.00029327694,0.00017918067,0.00007290657,0.00001664541,0.000098529046,0.00008505814,0.000011063093],"category_scores_gemma":[0.000051053394,0.00010883102,0.00025639893,0.00032248246,0.000028118367,0.0000025800455,0.000056552246,0.000026878466,1.1431226e-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":[0.000022292696,0.0000046391838,0.013518435,0.000013936953,0.0012112636,6.0529786e-8,0.000025846199,0.6171098,0.3651935,0.0002480197,0.000016125721,0.0026361123],"study_design_scores_gemma":[0.00020280074,0.000063331645,0.0008075659,0.0000029329287,0.001019854,5.490099e-7,0.000047364043,0.954473,0.043000784,0.00016366711,0.00008076919,0.00013733836],"about_ca_topic_score_codex":0.000020300151,"about_ca_topic_score_gemma":0.00006576682,"teacher_disagreement_score":0.33736324,"about_ca_system_score_codex":0.0000048604606,"about_ca_system_score_gemma":0.000013939363,"threshold_uncertainty_score":0.4438},"labels":[],"label_agreement":null},{"id":"W2083992072","doi":"10.1155/2015/567275","title":"Adaptive Time-Stepping Using Control Theory for the Chemical Langevin Equation","year":2015,"lang":"en","type":"article","venue":"Journal of Applied Mathematics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Langevin equation; Stochastic differential equation; Multiplicative function; Applied mathematics; Multiplicative noise; Statistical physics; Computer science; Constant (computer programming); Mathematics; Mathematical optimization; Physics; Mathematical analysis","score_opus":0.03638665304871609,"score_gpt":0.25899323766402044,"score_spread":0.22260658461530436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2083992072","genre_codex":"methods","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":[0.14763153,0.0007232718,0.85071725,0.00006678205,0.0000595714,0.00026424072,0.0000036945326,0.0000037122068,0.0005299357],"genre_scores_gemma":[0.93306446,0.000009787765,0.066066355,0.0001060723,0.0006584758,0.0000076045344,0.0000039237552,0.000023339637,0.000059966118],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992775,0.00002072825,0.0003182916,0.00007971333,0.00018089624,0.00012291626],"domain_scores_gemma":[0.99899316,0.00013036758,0.0004243031,0.0001728398,0.00021663212,0.00006272193],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011824071,0.00009775326,0.0002085708,0.000029220946,0.000041228275,0.00001810773,0.00017285807,0.00008211609,0.0000043989357],"category_scores_gemma":[0.00013196666,0.0000650694,0.00013826856,0.0000575323,0.000043147633,0.0000029270675,0.000030903986,0.00006787152,0.000003250428],"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":[0.00060420204,0.00011610645,0.000007191299,0.00003727861,0.00095157395,0.0000011604449,0.0005266224,0.05075434,0.93617415,0.0046218676,0.0029649993,0.0032405201],"study_design_scores_gemma":[0.0050995946,0.00047428833,0.000008998033,0.0001047656,0.002398885,0.00014540109,0.0040763174,0.6294149,0.29664168,0.056455504,0.004644767,0.0005348957],"about_ca_topic_score_codex":1.490298e-7,"about_ca_topic_score_gemma":1.9042837e-7,"teacher_disagreement_score":0.78543293,"about_ca_system_score_codex":0.000033477383,"about_ca_system_score_gemma":0.00009376534,"threshold_uncertainty_score":0.2653453},"labels":[],"label_agreement":null},{"id":"W2085491974","doi":"10.1371/journal.pbio.1000380","title":"Cell Lineage Determination in State Space: A Systems View Brings Flexibility to Dogmatic Canonical Rules","year":2010,"lang":"en","type":"article","venue":"PLoS Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":71,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Biology; Flexibility (engineering); Lineage (genetic); Space (punctuation); Computational biology; State space; State (computer science); Evolutionary biology; Genetics; Computer science; Mathematics; Gene; Algorithm","score_opus":0.01093730934728768,"score_gpt":0.26077943442443846,"score_spread":0.24984212507715078,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2085491974","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":[0.99802333,0.00059014885,0.00057308853,0.00011000649,0.00016308922,0.00033795877,0.000020402676,0.00001627617,0.0001657085],"genre_scores_gemma":[0.99795866,0.000061702835,0.0013073774,0.00010184916,0.00016579957,0.00006558115,0.000095455754,0.00001915179,0.00022443278],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985152,0.00019174156,0.0003683701,0.00051103893,0.00007565769,0.00033801564],"domain_scores_gemma":[0.9990846,0.00003462756,0.00010860754,0.0005312969,0.000085006344,0.0001558963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041892086,0.00017576265,0.0003105022,0.0000917161,0.000038048962,0.00001993625,0.00024082986,0.0002490293,0.000025106468],"category_scores_gemma":[0.0001822912,0.00016106661,0.000083073566,0.00014624254,0.00008146565,0.0000028091522,0.00015344138,0.00016805754,0.000049463342],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029319835,0.00010934808,0.016618012,0.00008184783,0.000027380729,0.000003423045,0.000059619044,0.00030948815,0.98174393,0.000038919447,0.000083406885,0.0008953208],"study_design_scores_gemma":[0.0014591371,0.00072806986,0.033228155,0.0000925472,0.00015241806,0.000041062165,0.000093800794,0.021288175,0.91303134,0.00031353915,0.028424714,0.0011470207],"about_ca_topic_score_codex":0.00019161156,"about_ca_topic_score_gemma":0.0013376015,"teacher_disagreement_score":0.068712555,"about_ca_system_score_codex":0.000027562364,"about_ca_system_score_gemma":0.00010175571,"threshold_uncertainty_score":0.6568106},"labels":[],"label_agreement":null},{"id":"W2086486335","doi":"10.1109/bibe.2008.4696728","title":"Stability and oscillation of genetic regulatory networks with time delays","year":2008,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Saskatchewan","funders":"","keywords":"Oscillation (cell signaling); Control theory (sociology); Stability (learning theory); Genetic algorithm; Interval (graph theory); Genetic network; Computer science; Nonlinear system; Gene regulatory network; Zebrafish; Topology (electrical circuits); Mathematics; Mathematical optimization; Physics; Biology; Genetics; Control (management); Gene; Artificial intelligence","score_opus":0.006376529993347581,"score_gpt":0.18424421752322676,"score_spread":0.17786768752987916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086486335","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":[0.9886703,0.0009802374,0.009531638,0.000012166373,0.000009622248,0.00009656752,0.0000013944729,0.000009026103,0.0006890801],"genre_scores_gemma":[0.9964521,0.00014024318,0.0029792446,0.000027340251,0.00006669997,0.000003245094,0.000022954055,0.000013710687,0.0002944463],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992335,0.000050997885,0.00018407937,0.00027537136,0.00011536948,0.00014072674],"domain_scores_gemma":[0.9993764,0.00000758019,0.00008041216,0.00037103024,0.00009611677,0.000068451714],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000109062225,0.0001113483,0.0001534195,0.000024899766,0.00006136984,0.0000031015545,0.00006224227,0.0001010318,0.0000709744],"category_scores_gemma":[0.000006822202,0.000092210765,0.000047610374,0.000109139044,0.000203528,0.0000021131773,0.00004996157,0.00003148157,0.0000015083094],"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":[0.00018498694,0.00007269004,0.7251015,0.000022402206,0.0002602889,0.000003941831,0.000056508743,0.048998985,0.2220998,0.000026052518,0.0014071508,0.001765719],"study_design_scores_gemma":[0.00083022757,0.00057509815,0.86042625,0.000010464212,0.00013124985,0.00012167446,0.000034032415,0.04253069,0.09362493,0.000029494411,0.0012514957,0.00043437586],"about_ca_topic_score_codex":0.0000106527705,"about_ca_topic_score_gemma":0.000027837019,"teacher_disagreement_score":0.13532479,"about_ca_system_score_codex":0.0000071400436,"about_ca_system_score_gemma":0.000039483173,"threshold_uncertainty_score":0.37602457},"labels":[],"label_agreement":null},{"id":"W2087332832","doi":"10.1049/iet-syb.2010.0039","title":"Cell–cell interaction and diversity of emergent behaviours","year":2011,"lang":"en","type":"article","venue":"IET Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":57,"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":"University of Calgary","keywords":"Expression (computer science); Gene regulatory network; Boolean network; Biology; Computational biology; Diversity (politics); Gene; Coupling (piping); Computer science; Cell biology; Gene expression; Biological system; Boolean function; Genetics; Engineering; Sociology","score_opus":0.020699924995003872,"score_gpt":0.2283613602462121,"score_spread":0.20766143525120823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2087332832","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":[0.99590266,0.0019614843,0.00045052747,0.0000041141707,0.00039643273,0.00009359435,0.0000148190165,0.000005454185,0.0011709351],"genre_scores_gemma":[0.99928707,0.00015721354,0.00007267107,0.000009122926,0.000075903125,0.0000036111433,0.0000498867,0.0000074883483,0.00033705306],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992835,0.00010855544,0.00018827211,0.00024302199,0.000039026367,0.00013765694],"domain_scores_gemma":[0.999504,0.000003859819,0.0001471285,0.00022927031,0.00006028855,0.00005540951],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013341093,0.00010095182,0.00017101188,0.000045855657,0.000051893418,0.0000021608182,0.00011242376,0.00016360605,0.00002723922],"category_scores_gemma":[0.000003422458,0.00009386599,0.00007553502,0.000046963276,0.00007048701,0.000001861614,0.00022178449,0.00004094027,0.000005078051],"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":[0.00005162532,0.000089164954,0.65718496,0.000036406615,0.000088971254,0.0000014151867,0.00020652857,0.00003767535,0.34039107,0.00004415009,0.0017171777,0.0001508877],"study_design_scores_gemma":[0.0013861835,0.0017703959,0.13530347,0.000030452347,0.00050715625,0.00005238496,0.0019194658,0.00027993548,0.84406793,0.00007082872,0.013862111,0.0007496531],"about_ca_topic_score_codex":0.0007217131,"about_ca_topic_score_gemma":0.000068847454,"teacher_disagreement_score":0.52188146,"about_ca_system_score_codex":0.000007810505,"about_ca_system_score_gemma":0.000011281643,"threshold_uncertainty_score":0.38277438},"labels":[],"label_agreement":null},{"id":"W2087585655","doi":"10.1142/s0218339004001324","title":"STATE-SPACE MODEL WITH TIME DELAYS FOR GENE REGULATORY NETWORKS","year":2004,"lang":"en","type":"article","venue":"Journal of Biological Systems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; University of Saskatchewan","keywords":"Gene regulatory network; Computer science; Expression (computer science); Bayesian network; State space; Dynamic Bayesian network; State variable; Gene; State (computer science); Probabilistic logic; Gene expression; Computational biology; Mathematics; Biology; Genetics; Algorithm; Artificial intelligence; Statistics; Physics","score_opus":0.012367089360110758,"score_gpt":0.21806529894227342,"score_spread":0.20569820958216267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2087585655","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":[0.69836885,0.003278581,0.2979648,0.000068346766,0.000087170614,0.00018103392,0.000008585957,0.0000068302033,0.000035775647],"genre_scores_gemma":[0.99347764,0.0002155273,0.0051284987,0.00006905958,0.0006662558,0.00001226417,0.000028142376,0.000023662482,0.00037896418],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99863625,0.000083375795,0.00050485035,0.00026256402,0.00018426053,0.0003286921],"domain_scores_gemma":[0.9986883,0.000020003808,0.000516361,0.0002691709,0.00031670515,0.00018946746],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061383506,0.00020667697,0.00043659133,0.00005101351,0.000082820006,0.00003158248,0.0002612086,0.00025749992,0.000002524671],"category_scores_gemma":[0.000030527706,0.00012867867,0.00027049283,0.000114670715,0.00009484316,0.00000567659,0.000046250923,0.00011667582,0.0000025279098],"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":[0.00033652445,0.000049835817,0.00040361457,0.000006008944,0.00023289386,0.000008277283,0.000007708127,0.8194381,0.17842841,0.000050453036,0.0007786364,0.00025952223],"study_design_scores_gemma":[0.0192662,0.02562065,0.008726062,0.0007345627,0.0013225863,0.0040750913,0.00034381612,0.61282694,0.29304433,0.0026478372,0.027488543,0.0039033615],"about_ca_topic_score_codex":0.0000033085337,"about_ca_topic_score_gemma":0.000002756344,"teacher_disagreement_score":0.29510877,"about_ca_system_score_codex":0.00006070195,"about_ca_system_score_gemma":0.000114263414,"threshold_uncertainty_score":0.5247364},"labels":[],"label_agreement":null},{"id":"W2088752199","doi":"10.1111/j.1749-6632.2008.03752.x","title":"Global Robustness and Identifiability of Random, Scale‐Free, and Small‐World Networks","year":2009,"lang":"en","type":"article","venue":"Annals of the New York Academy of Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Ontario Genomics Institute; Genome Canada","keywords":"Identifiability; Robustness (evolution); Network topology; Reachability; Biological network; Computer science; Complex network; Subnetwork; Topology (electrical circuits); Mathematics; Theoretical computer science; Biology; Machine learning; Combinatorics; Computer network","score_opus":0.03033280021679998,"score_gpt":0.2915664698674857,"score_spread":0.26123366965068573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088752199","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":[0.98542273,0.010725609,0.00044220933,0.003048211,0.00003369703,0.00012030843,0.0000059727327,0.000002711752,0.00019855972],"genre_scores_gemma":[0.99832875,0.000553112,0.0006279105,0.00024489002,0.00008522945,6.8031767e-7,6.3034537e-7,0.000002487862,0.00015630019],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99875206,0.00011215089,0.00036337192,0.00032691215,0.00023661312,0.00020886539],"domain_scores_gemma":[0.99930555,0.000032713087,0.00032270502,0.00019904187,0.000050007584,0.00008996129],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011110357,0.00012353623,0.00030149275,0.000042413078,0.000100672485,0.000015339474,0.00065622444,0.000119077566,0.0000029162854],"category_scores_gemma":[0.00008146854,0.000087209126,0.0001444757,0.0005976261,0.0011262634,0.000009156966,0.00022774917,0.000060352788,3.0703344e-8],"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":[0.0010447978,0.00032479878,0.45016322,0.00020284051,0.00051311246,2.678438e-7,0.0001747791,0.26629204,0.12543833,0.0024861533,0.046883047,0.10647662],"study_design_scores_gemma":[0.0015527952,0.00037330834,0.655357,0.0002013165,0.00022553655,0.000013638855,0.00012213875,0.008355267,0.31242272,0.019191384,0.0017811366,0.00040376518],"about_ca_topic_score_codex":0.00004385553,"about_ca_topic_score_gemma":0.00007527395,"teacher_disagreement_score":0.25793678,"about_ca_system_score_codex":0.0000019116635,"about_ca_system_score_gemma":0.000040261333,"threshold_uncertainty_score":0.41497642},"labels":[],"label_agreement":null},{"id":"W2088801753","doi":"10.1016/j.tibtech.2011.10.003","title":"Synthetic biology confronts publics and policy makers: challenges for communication, regulation and commercialization","year":2011,"lang":"en","type":"article","venue":"Trends in biotechnology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; University of Alberta","funders":"Nature","keywords":"Commercialization; Synthetic biology; Novelty; Stakeholder; Business; Publics; Biotechnology; Biology; Political science; Public relations; Computational biology; Marketing; Law","score_opus":0.04126036716723019,"score_gpt":0.290405989948823,"score_spread":0.2491456227815928,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088801753","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":[0.95753485,0.018246671,0.0072704027,0.014324132,0.00008113544,0.00037766862,0.000029352808,0.000094602896,0.0020412065],"genre_scores_gemma":[0.99072504,0.0058275685,0.00301819,0.000083413666,0.000033591685,0.00004094269,0.0001650396,0.000016669275,0.000089560606],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9991397,0.0000890552,0.0002094419,0.00033703592,0.000026809126,0.0001979514],"domain_scores_gemma":[0.9993115,0.00001578553,0.00010688696,0.00048427563,0.000048130707,0.000033397373],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022584428,0.00012825952,0.00018466041,0.00042997964,0.00007149864,0.0000074252307,0.00016251158,0.0005347066,0.000007232737],"category_scores_gemma":[0.00008566852,0.0001341147,0.00002942097,0.00021627253,0.0003821765,0.000005128774,0.00015219033,0.00006669125,4.4627478e-7],"study_design_candidate":"design_other","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":[0.00016609063,0.00016489383,0.018591553,0.000045450684,0.00020456735,4.5952532e-7,0.0006963424,0.000018794173,0.044296443,0.26113015,0.0006164081,0.67406887],"study_design_scores_gemma":[0.007880831,0.0026045756,0.43588,0.000114218055,0.00038598094,0.00017752628,0.0018160363,0.008043199,0.1682514,0.13946605,0.23325562,0.0021245605],"about_ca_topic_score_codex":0.00004642075,"about_ca_topic_score_gemma":0.00051377784,"teacher_disagreement_score":0.67194426,"about_ca_system_score_codex":0.000016293805,"about_ca_system_score_gemma":0.000016568487,"threshold_uncertainty_score":0.54690385},"labels":[],"label_agreement":null},{"id":"W2089483339","doi":"10.1016/j.chemphys.2008.08.001","title":"Positivity preserving chemical Langevin equations","year":2008,"lang":"en","type":"article","venue":"Chemical Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Brownian dynamics; Stochastic differential equation; Brownian motion; Statistical physics; Langevin equation; Independent equation; Applied mathematics; Chemistry; Mathematics; Differential equation; Physics; Mathematical analysis; Statistics","score_opus":0.01860482228711962,"score_gpt":0.23978935444582256,"score_spread":0.22118453215870293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089483339","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":[0.9905249,0.00023655733,0.005510026,0.00009394032,0.000031037696,0.000049415063,0.000008876049,0.000027882783,0.0035173728],"genre_scores_gemma":[0.997305,0.000020915246,0.0009429377,0.00013515228,0.00081030576,0.0000138480955,0.00026314432,0.000022978518,0.00048575137],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991416,0.000026207505,0.00013646747,0.00031083002,0.00015406626,0.0002308427],"domain_scores_gemma":[0.99932736,0.000023108183,0.000049603088,0.0004162087,0.0000792969,0.00010444754],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000048032412,0.00013875822,0.00015207258,0.000009331569,0.00006887742,0.000009307129,0.00020859658,0.00012618088,0.000019082858],"category_scores_gemma":[0.00008027915,0.00014417985,0.00016178332,0.00014301747,0.00012699477,0.0000050852022,0.00019125993,0.0001041495,0.00003078549],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000097345755,0.000079706144,0.0009469693,0.000006901686,0.00005317117,0.0000019403174,0.000019164474,0.00014073499,0.99262285,0.00011460164,0.005379122,0.0006251257],"study_design_scores_gemma":[0.00018581127,0.000012884916,0.00026795207,0.000005407612,0.000034303725,0.00000785838,0.0000042440693,0.0012111721,0.99516577,0.00042079488,0.0024884972,0.00019532972],"about_ca_topic_score_codex":0.000005930284,"about_ca_topic_score_gemma":8.482558e-7,"teacher_disagreement_score":0.006780075,"about_ca_system_score_codex":0.000022000353,"about_ca_system_score_gemma":0.000043653516,"threshold_uncertainty_score":0.5879483},"labels":[],"label_agreement":null},{"id":"W2089961542","doi":"10.1371/journal.pcbi.0020117","title":"Oscillatory Regulation of Hes1: Discrete Stochastic Delay Modelling and Simulation","year":2006,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":282,"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":"Australian Research Council; Universidad de Valladolid; Canadian Celiac Association","keywords":"HES1; Stochastic dynamics; Stochastic process; Computer science; Translation (biology); Statistical physics; Stochastic simulation; Stochastic modelling; Dynamics (music); Biological system; Molecular dynamics; Transcription (linguistics); Messenger RNA; Biology; Mathematics; Physics; Chemistry; Genetics; Statistics; Computational chemistry; Gene","score_opus":0.011803206873917144,"score_gpt":0.23528702130072246,"score_spread":0.22348381442680532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089961542","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":[0.5791591,0.00037809412,0.42030025,0.00001904089,0.000018287798,0.00006479301,0.000010135509,0.0000067054434,0.00004360169],"genre_scores_gemma":[0.99301153,0.0000044423205,0.006132181,0.000022444961,0.00016026001,0.0000049341734,0.0006173145,0.00001267202,0.000034214267],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99915385,0.00007172449,0.000271647,0.00027970842,0.00009530209,0.00012776838],"domain_scores_gemma":[0.9994861,0.00006244032,0.00014623864,0.000121937876,0.00015152783,0.000031782376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009393329,0.000113542505,0.00015729023,0.00007807299,0.000065248256,0.0000060618167,0.00005668991,0.000121918616,0.000009491965],"category_scores_gemma":[0.000015332094,0.000113084345,0.000057648867,0.00008840144,0.00014973963,0.000004112283,0.000045585428,0.000035666348,0.0000019259385],"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":[0.000029753826,0.000019995212,0.003017413,0.000007768982,0.000056944966,9.730474e-8,0.000007808743,0.9621146,0.033388563,0.0011276247,0.000016934262,0.00021250451],"study_design_scores_gemma":[0.00024634064,0.00007522935,0.006796039,0.000006597876,0.000042821,0.0000030932842,0.0000040905365,0.98084646,0.0018018206,0.009965397,0.00008951306,0.00012260304],"about_ca_topic_score_codex":0.000010394001,"about_ca_topic_score_gemma":0.000005470803,"teacher_disagreement_score":0.4141681,"about_ca_system_score_codex":0.00001163565,"about_ca_system_score_gemma":0.000033175183,"threshold_uncertainty_score":0.4611446},"labels":[],"label_agreement":null},{"id":"W2090609904","doi":"10.1021/sb4000564","title":"Tuning Response Curves for Synthetic Biology","year":2013,"lang":"en","type":"article","venue":"ACS Synthetic Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":170,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Synthetic biology; Systems biology; Context (archaeology); Set (abstract data type); Process (computing); Class (philosophy); Biological system; Computer science; Scaling; Biology; Computational biology; Biochemical engineering; Mathematics; Artificial intelligence; Engineering","score_opus":0.012316838022761048,"score_gpt":0.2592686424477256,"score_spread":0.24695180442496453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2090609904","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":[0.97464967,0.008541677,0.011677394,0.0034310983,0.00037527544,0.00076984643,0.000050888993,0.00005921579,0.0004449561],"genre_scores_gemma":[0.9945421,0.00071376545,0.0016683892,0.0011093454,0.00025284546,0.00040794548,0.0002166837,0.000057143956,0.0010317686],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9973581,0.0006039762,0.00044466084,0.0008212864,0.00006351361,0.00070848886],"domain_scores_gemma":[0.9982055,0.00030603012,0.0001907416,0.00093671685,0.00020634542,0.00015470968],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008023185,0.0003351559,0.000457398,0.00013226834,0.00017051472,0.000019649286,0.00052183063,0.0004883091,0.0002235777],"category_scores_gemma":[0.00085471314,0.00029384153,0.00027005415,0.00016329632,0.00045513274,0.0000048474835,0.00022578533,0.00011990202,0.0001390855],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016383546,0.00005374848,0.0018224607,0.000037027054,0.00021872626,5.657735e-7,0.000018463079,0.00002879508,0.9831135,0.0005414629,0.004810814,0.00919056],"study_design_scores_gemma":[0.0018241754,0.0028665185,0.004131316,0.00022247584,0.00053201645,0.00019656225,0.00021782769,0.0014762068,0.5071033,0.010131282,0.46940452,0.0018937945],"about_ca_topic_score_codex":0.000039731964,"about_ca_topic_score_gemma":0.000013997779,"teacher_disagreement_score":0.47601023,"about_ca_system_score_codex":0.000024419343,"about_ca_system_score_gemma":0.00010080552,"threshold_uncertainty_score":0.99995136},"labels":[],"label_agreement":null},{"id":"W2092701562","doi":"10.1007/s10439-006-9080-1","title":"On the Advantages of Multi-Input Single-Output Parallel Cascade Classifiers","year":2006,"lang":"en","type":"article","venue":"Annals of Biomedical Engineering","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cascade; Conventional PCI; Computer science; Weighting; Identification (biology); Nonlinear system; Machine learning; Artificial intelligence; Algorithm; Pattern recognition (psychology); Data mining; Engineering","score_opus":0.022888910171326524,"score_gpt":0.25420690679106855,"score_spread":0.23131799661974203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092701562","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":[0.9744014,0.0014661379,0.023125568,0.00072050793,0.00008443601,0.00007938612,0.000014548875,0.00001291661,0.00009510356],"genre_scores_gemma":[0.9983898,0.00008485748,0.0010468046,0.000106148786,0.00014571693,0.000005397086,0.00004113669,0.000018275477,0.0001618532],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99903077,0.000028726845,0.00029551378,0.00019025517,0.00022203506,0.00023267703],"domain_scores_gemma":[0.99942815,0.00005148186,0.000100215126,0.00029342226,0.00005404172,0.00007269226],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022197515,0.0001375733,0.00019617927,0.00008111636,0.00001991472,0.0000045234233,0.00020187031,0.00014324827,0.000010621623],"category_scores_gemma":[0.00012497451,0.00010213898,0.00018318175,0.00017444104,0.00014220418,0.0000019858428,0.000056793768,0.00008096165,0.000001850669],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026415379,0.0001781627,0.00016638765,0.000043799675,0.0001806828,0.0000040503287,0.000015825157,0.045058936,0.946043,0.00035843346,0.0059190895,0.0020052101],"study_design_scores_gemma":[0.0005550772,0.00043156027,0.005359828,0.000098713426,0.000054223463,0.000008057647,0.000040695082,0.025677484,0.9375129,0.0000691707,0.029870564,0.0003217484],"about_ca_topic_score_codex":0.00001789752,"about_ca_topic_score_gemma":0.0000031113063,"teacher_disagreement_score":0.023988416,"about_ca_system_score_codex":0.00000452801,"about_ca_system_score_gemma":0.00002005795,"threshold_uncertainty_score":0.41651067},"labels":[],"label_agreement":null},{"id":"W2093351336","doi":"10.1007/s11047-009-9167-3","title":"A synthetic genetic circuit whose signal-response curve is temperature-tunable from band-detection to sigmoidal behaviour","year":2009,"lang":"en","type":"article","venue":"Natural Computing","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"College of Family Physicians of Canada; University of Toronto","funders":"","keywords":"Sigmoid function; Electronic circuit; Biological system; Modular design; Computer science; SIGNAL (programming language); Synthetic biology; Frequency response; Step response; Biology; Artificial intelligence; Bioinformatics; Engineering; Control engineering; Electrical engineering; Artificial neural network","score_opus":0.005791972433579648,"score_gpt":0.2280615160182967,"score_spread":0.22226954358471704,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093351336","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":[0.9948427,0.002624838,0.0017245023,0.0002195236,0.0002491628,0.00023982617,0.000012724844,0.000053827054,0.000032880947],"genre_scores_gemma":[0.9971047,0.0000090966905,0.00074114004,0.00096701033,0.00068123965,0.000004113138,0.00004516547,0.000034040047,0.00041347276],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9977695,0.000260452,0.0003523834,0.00081163953,0.0003055776,0.0005004726],"domain_scores_gemma":[0.9989382,0.000047453846,0.00012973229,0.00051940855,0.00017473247,0.00019044806],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003354322,0.00032760258,0.00030329596,0.0001309209,0.00027726838,0.00012120706,0.0003278546,0.0002900968,0.000037676797],"category_scores_gemma":[0.00008611688,0.0003273736,0.0002572787,0.00039291824,0.000030687006,0.000006745552,0.00009865188,0.00031031546,0.00003313676],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023364509,0.000040303472,0.0013974743,0.000002892567,0.00006793743,0.000013371118,0.00014234659,0.0036046538,0.9788992,5.6676214e-7,0.00054992066,0.015047699],"study_design_scores_gemma":[0.0005279658,0.0004895973,0.09200879,0.000051754967,0.00013203584,0.000040448645,0.00006956277,0.0049997796,0.8998195,0.000069676535,0.0011858707,0.0006050319],"about_ca_topic_score_codex":0.000054784818,"about_ca_topic_score_gemma":0.000028141425,"teacher_disagreement_score":0.090611316,"about_ca_system_score_codex":0.00007561317,"about_ca_system_score_gemma":0.00006333669,"threshold_uncertainty_score":0.9999178},"labels":[],"label_agreement":null},{"id":"W2093631511","doi":"10.1109/cibcb.2006.330961","title":"A Systematic Approach for Identifying Regulatory Interactions in Large Temporal Gene Expression Datasets from Peripheral Blood","year":2006,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Dimensionality reduction; Computational biology; Gene regulatory network; Gene; Computer science; Set (abstract data type); Biological network; Expression (computer science); Curse of dimensionality; Artificial intelligence; Gene expression; Machine learning; Data mining; Biology; Genetics","score_opus":0.014771626570760412,"score_gpt":0.2641023982058193,"score_spread":0.2493307716350589,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093631511","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":[0.88662225,0.0016222785,0.110701114,0.000010076411,0.000086946195,0.0005510459,0.00025184755,0.000021795518,0.00013262361],"genre_scores_gemma":[0.9604705,0.0000063371826,0.029133517,0.000035631532,0.0003059837,0.00020460864,0.009088638,0.000029646468,0.00072511117],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984655,0.00012497937,0.00047453854,0.0005075463,0.00014439212,0.00028306193],"domain_scores_gemma":[0.99910456,0.000015524016,0.00016045889,0.00062408176,0.00004021962,0.000055183566],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029016222,0.00018990613,0.0002924012,0.000082710874,0.00010587348,0.00005142686,0.00020692665,0.00010481856,0.000033630266],"category_scores_gemma":[0.000021728936,0.00017248717,0.00018137509,0.00011094078,0.000022420796,0.00001210865,0.00012603443,0.0000656626,0.0000021371143],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040906772,0.000357626,0.01438226,0.00059173105,0.0001763288,0.0000033980753,0.00002957425,0.0022862344,0.9767959,0.00003157995,0.0052966364,0.00000783144],"study_design_scores_gemma":[0.003945596,0.00008498438,0.012466,0.0006932502,0.0006478562,0.00003859836,0.0008600707,0.035116818,0.94348705,0.00025113614,0.001420843,0.000987771],"about_ca_topic_score_codex":0.0001596086,"about_ca_topic_score_gemma":0.0007283399,"teacher_disagreement_score":0.08156759,"about_ca_system_score_codex":0.000027885648,"about_ca_system_score_gemma":0.000032035696,"threshold_uncertainty_score":0.70338225},"labels":[],"label_agreement":null},{"id":"W2093672751","doi":"10.1371/journal.pcbi.1000699","title":"Estimating the Stochastic Bifurcation Structure of Cellular Networks","year":2010,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of Ottawa; Ottawa Hospital","funders":"Mitacs; Ottawa Hospital Research Institute","keywords":"Bistability; Gene regulatory network; Computer science; Dynamical systems theory; Bifurcation; Bifurcation theory; Estimator; Systems biology; Bifurcation diagram; Biological system; Statistical physics; Mathematics; Nonlinear system; Biology; Physics; Bioinformatics; Gene expression; Statistics; Gene; Genetics","score_opus":0.005977839612634028,"score_gpt":0.22355672476603503,"score_spread":0.21757888515340099,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093672751","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":[0.71350604,0.0001348627,0.28598002,0.000086740474,0.00017757565,0.000084116065,0.000010341165,0.000006343258,0.000013953356],"genre_scores_gemma":[0.9880764,7.259308e-7,0.010663454,0.00009579179,0.00053747057,0.000005250833,0.0005977623,0.000011863785,0.00001126765],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99925214,0.000075118776,0.00021974335,0.0002275406,0.00008256375,0.00014288003],"domain_scores_gemma":[0.999328,0.00006820822,0.0001678927,0.00023548996,0.0001665817,0.000033786564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009525592,0.00010915354,0.00012855459,0.000037999736,0.00009794559,0.000007740416,0.00020853295,0.00015254816,0.000038971066],"category_scores_gemma":[0.00008418829,0.00008187417,0.00006979519,0.00012569196,0.00017447595,0.000001698605,0.00007714869,0.00013765694,0.0000024201493],"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":[0.000006731761,0.0000131902,0.0013776369,0.0000027777469,0.00006909205,6.1806496e-8,0.000010064519,0.5628049,0.43447208,0.00062875287,0.000048203132,0.00056651694],"study_design_scores_gemma":[0.00019778831,0.000082660306,0.0045191543,0.000004418967,0.000066631925,0.0000097210395,0.000008300353,0.96562296,0.023722183,0.0055180374,0.00010757016,0.00014058023],"about_ca_topic_score_codex":0.0000040302834,"about_ca_topic_score_gemma":0.000016840697,"teacher_disagreement_score":0.4107499,"about_ca_system_score_codex":0.000003876998,"about_ca_system_score_gemma":0.000051433846,"threshold_uncertainty_score":0.33387315},"labels":[],"label_agreement":null},{"id":"W2093860848","doi":"10.1098/rsif.2014.1106","title":"How spatial heterogeneity shapes multiscale biochemical reaction network dynamics","year":2015,"lang":"en","type":"article","venue":"Journal of The Royal Society Interface","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Homogeneity (statistics); Biological system; Statistical physics; Molecular dynamics; Spatial heterogeneity; Stochastic simulation; Computer science; Physics; Chemistry; Mathematics; Biology; Ecology; Computational chemistry","score_opus":0.010738148726749984,"score_gpt":0.24043366445862308,"score_spread":0.22969551573187308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093860848","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":[0.86610574,0.0017168121,0.13034949,0.0011270579,0.0005863029,0.00006438123,0.0000050891576,0.000005102768,0.000040048362],"genre_scores_gemma":[0.9959143,0.000041095802,0.0015908759,0.00010921942,0.0014015842,0.0000011605407,0.0000056230097,0.00001975824,0.000916414],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989128,0.000114985065,0.0002749644,0.00017532748,0.00029029217,0.00023163875],"domain_scores_gemma":[0.99893755,0.000010206747,0.0004092498,0.00024626317,0.00024843196,0.00014832085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041892083,0.00016176725,0.00021684381,0.000007969308,0.00008565563,0.000053393254,0.00041039952,0.00021514801,0.0000024961362],"category_scores_gemma":[0.00007975888,0.00011426039,0.0006763357,0.00009070713,0.00010382204,0.000006153571,0.00024032826,0.00026068292,0.0000017857809],"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":[0.0003549831,0.00019274892,0.014931816,0.000021644848,0.001492556,0.0000024716066,0.00020085805,0.56129956,0.17377715,0.0000034772565,0.24448963,0.00323313],"study_design_scores_gemma":[0.002023276,0.0007405532,0.008479211,0.000107646156,0.0006188221,0.00018406237,0.001007227,0.5323173,0.40356737,0.00015762537,0.05015462,0.0006422923],"about_ca_topic_score_codex":0.000023305813,"about_ca_topic_score_gemma":0.000076117845,"teacher_disagreement_score":0.22979024,"about_ca_system_score_codex":0.00015124085,"about_ca_system_score_gemma":0.000076239965,"threshold_uncertainty_score":0.46594036},"labels":[],"label_agreement":null},{"id":"W2093872708","doi":"10.1155/ijbi/2006/12186","title":"Probabilistic Model‐Based Cell Tracking","year":2006,"lang":"en","type":"article","venue":"International Journal of Biomedical Imaging","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia; University of Waterloo","keywords":"Computer science; Probabilistic logic; Tracking (education); Data mining; Statistical model; Data science; Artificial intelligence","score_opus":0.006112849503138805,"score_gpt":0.25165067415795483,"score_spread":0.24553782465481602,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093872708","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":[0.6876364,0.0009253938,0.3082169,0.0018950859,0.0005447072,0.00004621297,0.000008945132,0.000007959881,0.0007184404],"genre_scores_gemma":[0.9931017,0.000010389676,0.0053667016,0.0002802452,0.001066853,0.0000010213233,0.000044279845,0.000013745599,0.00011504744],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99875665,0.000033222004,0.00041282942,0.00014357294,0.0005043689,0.00014935527],"domain_scores_gemma":[0.99912846,0.00001514996,0.0002619903,0.00010528034,0.00040454828,0.000084548614],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029039348,0.000098589626,0.00012066852,0.00015801257,0.000028045231,0.00004716784,0.00036094536,0.000048575163,0.000027286571],"category_scores_gemma":[0.000058336125,0.00008693548,0.00019028239,0.00008070763,0.00011076608,0.000008430648,0.000049606468,0.00010070559,0.000002751317],"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":[0.00014836983,0.00046521475,0.0064359535,0.000015774021,0.00015013154,0.00015790958,0.000017228616,0.1196876,0.8435614,0.00007447467,0.013389078,0.015896829],"study_design_scores_gemma":[0.0031968663,0.0002013885,0.0030659765,0.00013948856,0.00020515469,0.00042801263,0.00004892955,0.7334635,0.2110326,0.0032356419,0.044465348,0.00051704346],"about_ca_topic_score_codex":0.000006103939,"about_ca_topic_score_gemma":0.0000024518279,"teacher_disagreement_score":0.63252884,"about_ca_system_score_codex":0.000045122062,"about_ca_system_score_gemma":0.0001597572,"threshold_uncertainty_score":0.35451257},"labels":[],"label_agreement":null},{"id":"W2093939816","doi":"10.1016/j.nonrwa.2012.11.008","title":"Polynomial representations of piecewise-linear differential equations arising from gene regulatory networks","year":2012,"lang":"en","type":"article","venue":"Nonlinear Analysis Real World Applications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Boolean network; Mathematics; Polynomial; Gene regulatory network; Ordinary differential equation; Multilinear map; Discontinuity (linguistics); Representation (politics); Piecewise; Limit (mathematics); Differential equation; Limit cycle; Pure mathematics; Discrete mathematics; Boolean function; Mathematical analysis; Gene","score_opus":0.012320264925282943,"score_gpt":0.2813863891505303,"score_spread":0.2690661242252474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093939816","genre_codex":"methods","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":[0.4439242,0.0008660856,0.55352074,0.00007507666,0.00008107322,0.0003319865,0.00028807597,0.00003989528,0.0008728702],"genre_scores_gemma":[0.97609806,0.00015561235,0.012988251,0.000039303115,0.0023325323,0.00012723762,0.006422126,0.000041474064,0.0017954059],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978444,0.00015486142,0.0007301199,0.000548752,0.00031436552,0.0004074984],"domain_scores_gemma":[0.9977349,0.000095306335,0.0004175683,0.0012770998,0.00021843617,0.00025666223],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022403723,0.00026133732,0.00047537335,0.0004054806,0.00027471565,0.000027169412,0.00034820774,0.00019154724,0.00021969454],"category_scores_gemma":[0.000026044103,0.0002777393,0.0006870367,0.002047705,0.00016597364,0.000015135122,0.00016648139,0.00016546613,0.000018554836],"study_design_candidate":"simulation_or_modeling","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":[0.00011395583,0.0014644905,0.23158272,0.0000137869165,0.010561263,6.022491e-7,0.00017504902,0.31633207,0.4265969,0.000626204,0.003971862,0.008561081],"study_design_scores_gemma":[0.0012330087,0.000054573342,0.34412417,0.000014694091,0.013703512,0.0000018397619,0.00024355033,0.47245196,0.13290575,0.00004302696,0.033948686,0.0012752699],"about_ca_topic_score_codex":0.0003479404,"about_ca_topic_score_gemma":0.0014933167,"teacher_disagreement_score":0.54053247,"about_ca_system_score_codex":0.000043688415,"about_ca_system_score_gemma":0.00006678329,"threshold_uncertainty_score":0.99996746},"labels":[],"label_agreement":null},{"id":"W2094107369","doi":"10.1142/s0217979203018028","title":"HOW CELLS AVOID ERRORS IN METABOLIC AND SIGNALING NETWORKS","year":2003,"lang":"en","type":"article","venue":"International Journal of Modern Physics B","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"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":"","keywords":"Sigmoid function; Proofreading; Computer science; Reliability (semiconductor); Sequence (biology); Metabolic network; Artificial intelligence; Biology; Computational biology; Artificial neural network; Genetics; Physics; Power (physics); Gene","score_opus":0.008750715095907389,"score_gpt":0.2289311553168243,"score_spread":0.2201804402209169,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2094107369","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":[0.87998056,0.0039886353,0.11551466,0.00012668267,0.00027665475,0.000030486164,0.000001976996,0.0000014093754,0.000078960045],"genre_scores_gemma":[0.99722064,0.00052940496,0.0014955306,0.00010086513,0.00052405556,0.000001027577,0.000005337905,0.000015242502,0.000107874024],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991934,0.000079227844,0.00022129044,0.00014148992,0.00023371073,0.0001309215],"domain_scores_gemma":[0.9993835,0.000012847501,0.0002284187,0.00010009379,0.00021373313,0.00006137183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023793582,0.00011075346,0.0001689037,0.0000661469,0.000020029238,0.000053240154,0.0001948978,0.00006413167,0.0000029131038],"category_scores_gemma":[0.000023816981,0.000105671534,0.00012871578,0.00006707249,0.000035144403,0.000014147018,0.000039613948,0.00013046975,3.4950386e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000664022,0.00011436878,0.008336051,0.0000037278069,0.0006006057,0.00002741146,0.000106530824,0.3895911,0.5836997,0.0007193231,0.00019563777,0.016539156],"study_design_scores_gemma":[0.0026236118,0.00016469204,0.0021676372,0.00008639107,0.0001967358,0.00019157046,0.00017694893,0.066554785,0.89654475,0.017231075,0.013472211,0.0005895843],"about_ca_topic_score_codex":0.0000016498908,"about_ca_topic_score_gemma":0.0000066108946,"teacher_disagreement_score":0.3230363,"about_ca_system_score_codex":0.000015609909,"about_ca_system_score_gemma":0.000048348607,"threshold_uncertainty_score":0.430916},"labels":[],"label_agreement":null},{"id":"W2095478187","doi":"10.1016/j.bpj.2011.11.1591","title":"Stochastic Hopf Bifurcation in Transcription Networks with Delayed Feedback","year":2012,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Statistical physics; Randomness; Hopf bifurcation; Negative feedback; Oscillation (cell signaling); Bifurcation diagram; Bifurcation; Physics; Stochastic process; Control theory (sociology); Mathematics; Computer science; Biology; Nonlinear system; Quantum mechanics; Statistics","score_opus":0.007602203584479732,"score_gpt":0.21970492432772445,"score_spread":0.2121027207432447,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095478187","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":[0.89841986,0.00033748607,0.10092732,0.00008093314,0.00012258712,0.00006934994,0.0000010694021,0.0000054260995,0.00003598326],"genre_scores_gemma":[0.9977769,0.000049783474,0.00043036442,0.000074524985,0.0015521005,0.00000680094,0.000034194967,0.000020997739,0.000054290766],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99903584,0.00008515489,0.0001993683,0.00016086931,0.00016539912,0.0003533684],"domain_scores_gemma":[0.9994966,0.000005904226,0.00009738245,0.00016128056,0.00006150664,0.00017733464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017790652,0.000143524,0.00014739341,0.00006121762,0.00007453224,0.000029353214,0.000112263624,0.00011151799,0.000014443781],"category_scores_gemma":[0.0000066333205,0.00011565263,0.00010857986,0.00022826639,0.00005400238,0.00001330517,0.000016523998,0.00018126884,0.000010284226],"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":[0.0004475102,0.00029265197,0.0037690613,0.000004096445,0.00015818303,0.000003050135,0.00007601228,0.0900415,0.9004343,0.0000549123,0.00043769798,0.0042810244],"study_design_scores_gemma":[0.01076467,0.0043021967,0.6361521,0.0002704854,0.0013475119,0.0013801727,0.00079027005,0.1445161,0.19018728,0.00019595494,0.006804862,0.0032884164],"about_ca_topic_score_codex":0.0000047715935,"about_ca_topic_score_gemma":0.000015415748,"teacher_disagreement_score":0.71024704,"about_ca_system_score_codex":0.00003643415,"about_ca_system_score_gemma":0.00003200661,"threshold_uncertainty_score":0.47161773},"labels":[],"label_agreement":null},{"id":"W2096159618","doi":"10.1109/iembs.2007.4352557","title":"Stability Analysis of Genetic Regulatory Networks with Multiple Time Delays","year":2007,"lang":"en","type":"article","venue":"Conference proceedings","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"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 Saskatchewan","funders":"","keywords":"Genetic network; Stability (learning theory); Gene regulatory network; Statistic; Computer science; Genetic algorithm; Nonlinear system; Control theory (sociology); Mathematics; Gene; Mathematical optimization; Biology; Genetics; Statistics; Gene expression; Artificial intelligence; Control (management); Physics","score_opus":0.009099273766632759,"score_gpt":0.2124406375171351,"score_spread":0.20334136375050235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096159618","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":[0.95713663,0.0003313428,0.041574582,0.00001222158,0.000016557857,0.00016381538,0.000005633654,0.000021615255,0.0007376195],"genre_scores_gemma":[0.9966377,0.000032543157,0.0029600055,0.000035793306,0.000088618945,0.000010008993,0.000060528015,0.00002407449,0.0001507118],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99832445,0.000014433987,0.0004274894,0.0005699514,0.00026106669,0.0004026008],"domain_scores_gemma":[0.99846596,0.000020333999,0.00028109463,0.00037781187,0.00068765966,0.00016716217],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005477525,0.00023433086,0.00041911632,0.00017524412,0.00007245728,0.000026093849,0.00030419687,0.00020763601,0.00010419964],"category_scores_gemma":[0.00005514675,0.00021126615,0.00020440287,0.0009492227,0.00025690618,0.0000072395246,0.00011146678,0.000100336394,0.0000030058895],"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":[0.00022562938,0.00007395732,0.74383646,0.000024026163,0.0013287264,0.0000013437067,0.00014032332,0.003182738,0.24899203,0.000046865185,0.0001709675,0.0019769135],"study_design_scores_gemma":[0.00054422737,0.0003480646,0.7658201,0.000023757577,0.0018510988,0.0000072367097,0.00031120854,0.10102712,0.12898953,0.000026927393,0.00053839025,0.00051235396],"about_ca_topic_score_codex":0.000016060965,"about_ca_topic_score_gemma":0.00013247623,"teacher_disagreement_score":0.120002486,"about_ca_system_score_codex":0.000027107018,"about_ca_system_score_gemma":0.00008170911,"threshold_uncertainty_score":0.8615184},"labels":[],"label_agreement":null},{"id":"W2096705138","doi":"10.1073/pnas.0803850105","title":"Analytical distributions for stochastic gene expression","year":2008,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":935,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Master equation; Messenger RNA; Statistical physics; Translation (biology); Budding yeast; Gene expression; Gene; Stochastic modelling; Variance (accounting); Biology; Expression (computer science); Physics; Biological system; Saccharomyces cerevisiae; Mathematics; Genetics; Computer science; Statistics; Quantum mechanics","score_opus":0.03683146789668673,"score_gpt":0.3022625359857907,"score_spread":0.265431068089104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096705138","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":[0.9984633,0.00015248588,0.0005239619,0.0004907168,0.00000787907,0.00010594345,0.000030668114,0.0000024586743,0.00022258786],"genre_scores_gemma":[0.99713343,0.0000136503995,0.0025307508,0.000042651245,0.000112930145,0.000011220425,0.0000016679716,0.000002538388,0.0001511649],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991293,0.0000031221,0.00017996966,0.00018629731,0.00039282383,0.000108466505],"domain_scores_gemma":[0.9995298,0.000021881562,0.00016932421,0.000008679344,0.00024046891,0.000029895165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000360322,0.00005901017,0.00009139021,0.000047014637,0.00022114009,0.0000041677276,0.00036340996,0.00006866654,0.0000030886192],"category_scores_gemma":[0.00033700714,0.00004056132,0.00011635509,0.0002929333,0.00057552266,0.000008260764,0.00009492433,0.00003794726,2.3545473e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013747566,0.000027643868,0.0027858336,0.000007855472,0.000018767314,8.3211477e-10,0.00000923156,0.001732317,0.9899879,0.002779451,0.0026085875,0.000028668626],"study_design_scores_gemma":[0.00012959774,0.00004601026,0.01686484,0.000012903563,0.00002224366,0.000009133109,0.00001606442,0.0039394987,0.97472423,0.0038894815,0.0002842571,0.00006171535],"about_ca_topic_score_codex":3.5182657e-7,"about_ca_topic_score_gemma":1.3800272e-8,"teacher_disagreement_score":0.015263641,"about_ca_system_score_codex":0.000009659525,"about_ca_system_score_gemma":0.000032884593,"threshold_uncertainty_score":0.21205373},"labels":[],"label_agreement":null},{"id":"W2099531989","doi":"10.1073/pnas.0610468104","title":"Deterministic characterization of stochastic genetic circuits","year":2007,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":84,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Bistability; Noise (video); Negative feedback; Feedback loop; Positive feedback; Stability (learning theory); Electronic circuit; Control theory (sociology); Computer science; Stochastic modelling; Master equation; Stochastic process; Statistical physics; Biological system; Mathematics; Physics; Control (management); Biology; Engineering; Quantum mechanics","score_opus":0.020812998922896515,"score_gpt":0.27640002380489875,"score_spread":0.25558702488200225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2099531989","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":[0.9991484,0.00007328365,0.00023987926,0.000065558146,0.000012978557,0.000083367355,0.0000063357934,0.0000017038274,0.0003684522],"genre_scores_gemma":[0.9994533,0.000009049008,0.00032472747,0.000050205017,0.00009013998,0.00000193148,6.147286e-7,0.000003670247,0.0000663477],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988967,0.0000039468987,0.00030749652,0.00017304569,0.00050636544,0.00011239908],"domain_scores_gemma":[0.99924576,0.000017819884,0.00044854535,0.000010348108,0.00025194153,0.000025602003],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006993701,0.00006653702,0.000108844506,0.000101445316,0.00006354296,0.000004833099,0.00040947224,0.00007514984,0.0000038357766],"category_scores_gemma":[0.0001975585,0.00005122116,0.00007179913,0.0004241407,0.00043739897,0.000008134463,0.000079712816,0.00003843719,2.8318615e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000058816026,0.000017151948,0.0042007472,0.000022984854,0.000015681886,1.6177425e-9,0.000023705108,0.0003001898,0.9941135,0.00047871334,0.00001192453,0.00080949237],"study_design_scores_gemma":[0.00007158551,0.00004871068,0.27465144,0.00002410388,0.000022035594,0.000005227547,0.000016012034,0.00074920274,0.72295284,0.0013818037,0.000025025902,0.000052010637],"about_ca_topic_score_codex":5.4759386e-7,"about_ca_topic_score_gemma":5.9949606e-8,"teacher_disagreement_score":0.2711607,"about_ca_system_score_codex":0.000007909482,"about_ca_system_score_gemma":0.000028242792,"threshold_uncertainty_score":0.20887382},"labels":[],"label_agreement":null},{"id":"W2099632205","doi":"10.1109/csb.2004.158","title":"State-space model for gene regulatory networks with time delays","year":2004,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"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 Saskatchewan","funders":"","keywords":"Gene regulatory network; Expression (computer science); Principal component analysis; Dynamic Bayesian network; Computer science; State space; State-space representation; Bayesian network; State (computer science); Probabilistic logic; Bayesian information criterion; Gene expression; Gene; Mathematics; Algorithm; Artificial intelligence; Statistics; Genetics; Biology","score_opus":0.005600707083865505,"score_gpt":0.20104259685031536,"score_spread":0.19544188976644986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2099632205","genre_codex":"methods","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":[0.3951977,0.00043871216,0.6037555,0.0000919361,0.000015854836,0.00019368558,0.0000069922557,0.000025728008,0.00027395476],"genre_scores_gemma":[0.94331104,0.00005994678,0.047008988,0.00029252152,0.00017946844,0.00004688029,0.00018726636,0.00006082899,0.008853069],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99880296,0.000016726894,0.00018369024,0.0004681566,0.00013464439,0.00039381682],"domain_scores_gemma":[0.99907017,0.0000051805223,0.00008065411,0.0005661411,0.00013368188,0.00014417086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015188113,0.00022176608,0.00020064577,0.000038744274,0.00010459238,0.000022292328,0.00018041104,0.0001525112,0.000012591802],"category_scores_gemma":[0.0000054971806,0.00018678287,0.00014496931,0.00012044125,0.00007631222,0.0000038517446,0.00006452215,0.000053660704,0.000009733499],"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":[0.00011808142,0.000032020573,0.00007666919,0.0000033117321,0.00015037463,0.0000012066746,0.000014065126,0.9046554,0.09217049,0.00009705079,0.0022698587,0.00041148538],"study_design_scores_gemma":[0.0016145469,0.0003491021,0.00019931298,0.000010570922,0.00014217336,0.000019719806,0.00001338464,0.78002787,0.21520965,0.0005402371,0.0013462597,0.000527176],"about_ca_topic_score_codex":0.000007247593,"about_ca_topic_score_gemma":0.00008248256,"teacher_disagreement_score":0.5567465,"about_ca_system_score_codex":0.000034688317,"about_ca_system_score_gemma":0.00013070116,"threshold_uncertainty_score":0.7616784},"labels":[],"label_agreement":null},{"id":"W2100818016","doi":"10.1109/acc.2013.6580543","title":"Sensitivity analysis in Petri net representation of biological systems","year":2013,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Petri net; Computer science; Sensitivity (control systems); Cascade; Systems biology; Measure (data warehouse); Representation (politics); Data mining; Distributed computing; Engineering; Computational biology; Biology; Electronic engineering","score_opus":0.015592213641090853,"score_gpt":0.25455875434397124,"score_spread":0.2389665407028804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2100818016","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":[0.99416506,0.00021750414,0.0047814124,0.00003095328,0.000023950011,0.00012104068,0.0000023877542,0.0000054944394,0.000652178],"genre_scores_gemma":[0.99912125,0.00005738985,0.00027164372,0.000015849871,0.000048371392,0.000011682662,0.000116598836,0.0000041236517,0.00035310807],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990286,0.00022301031,0.0002505097,0.00027156775,0.00009071353,0.00013555714],"domain_scores_gemma":[0.9994242,0.000023152446,0.000090743815,0.0003249796,0.00009549538,0.00004138927],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022717733,0.00008278282,0.00025152008,0.00014466346,0.000013419831,0.000011331091,0.000059643313,0.00011407425,0.00006407692],"category_scores_gemma":[0.000052868138,0.00006736021,0.00016224652,0.0007473201,0.00004353096,0.0000025020593,0.00005609466,0.000030520438,0.000009511155],"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":[0.000008525621,0.000040043487,0.6295741,0.000003971141,0.00034358486,0.0000013766411,0.000007397229,0.05351349,0.31567228,0.000037866375,0.0004903737,0.00030695833],"study_design_scores_gemma":[0.0002310827,0.00007316619,0.8791938,0.0000028625186,0.0001509315,0.0000039546326,0.00022679681,0.053112604,0.06663934,0.000020221596,0.00018138006,0.00016388873],"about_ca_topic_score_codex":0.001376224,"about_ca_topic_score_gemma":0.00036410431,"teacher_disagreement_score":0.24961965,"about_ca_system_score_codex":0.000008609273,"about_ca_system_score_gemma":0.000011605669,"threshold_uncertainty_score":0.27468696},"labels":[],"label_agreement":null},{"id":"W2101149758","doi":"10.48550/arxiv.nlin/0511018","title":"The Role of Redundancy in the Robustness of Random Boolean Networks","year":2005,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":36,"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 Calgary","funders":"","keywords":"Robustness (evolution); Redundancy (engineering); Fitness landscape; Conjecture; Computer science; Evolutionary algorithm; Boolean network; Theoretical computer science; Artificial intelligence; Mathematics; Boolean function; Biology; Algorithm; Gene; Discrete mathematics; Genetics","score_opus":0.016270531616867374,"score_gpt":0.16860074219840276,"score_spread":0.1523302105815354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101149758","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":[0.98298794,0.0043996135,0.011150791,0.000036983103,0.00010795167,0.00027443052,0.000007163915,0.0000050830718,0.001030027],"genre_scores_gemma":[0.9968666,0.0023885434,0.00003769223,0.000011995558,0.00021916904,0.0000015386184,0.00004365873,0.000016776628,0.00041401235],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99861616,0.0003311933,0.0002952108,0.00044049573,0.00007403855,0.00024288867],"domain_scores_gemma":[0.99827635,0.00006147827,0.00038306328,0.0011206804,0.00011904581,0.000039374274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055826217,0.00020882027,0.00032062235,0.000068708956,0.00008557099,0.0000132796795,0.001039496,0.0003140168,0.000007350185],"category_scores_gemma":[0.000026193427,0.00015988562,0.00036324223,0.00030066568,0.00026182155,0.0000028651161,0.00049894064,0.00028589054,6.3445356e-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":[0.00022170397,0.000055984856,0.0050525363,0.000014868822,0.0002032857,0.0000034156503,0.00003751118,0.99194336,0.00067598384,0.0006492627,0.00015482082,0.0009872714],"study_design_scores_gemma":[0.0028910583,0.0001638611,0.0077718818,0.000182496,0.0008968023,0.000007878992,0.0017235164,0.9647693,0.008534309,0.0029643844,0.009297158,0.00079736306],"about_ca_topic_score_codex":0.000055378317,"about_ca_topic_score_gemma":0.000454799,"teacher_disagreement_score":0.027174065,"about_ca_system_score_codex":0.000025146204,"about_ca_system_score_gemma":0.000104886756,"threshold_uncertainty_score":0.6519946},"labels":[],"label_agreement":null},{"id":"W2101996922","doi":"10.1016/j.mbs.2012.09.008","title":"Computing weakly reversible linearly conjugate chemical reaction networks with minimal deficiency","year":2012,"lang":"en","type":"article","venue":"Mathematical Biosciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Conjugate; Complex conjugate; Conjugacy class; Action (physics); Mass action law; Mathematics; Chemical reaction; Integer (computer science); Zero (linguistics); Stability (learning theory); Pure mathematics; Statistical physics; Applied mathematics; Physics; Chemistry; Computer science; Mathematical analysis; Quantum mechanics","score_opus":0.010669069994534038,"score_gpt":0.23484899758086686,"score_spread":0.22417992758633282,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101996922","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":[0.96785694,0.0006502167,0.029250836,0.00020309037,0.00009014328,0.00012096578,0.0000013487017,0.00002786038,0.0017985926],"genre_scores_gemma":[0.98726785,0.000016166749,0.012095839,0.00013785783,0.00028115782,0.0000037011962,0.00001243614,0.000011601253,0.0001733938],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985627,0.000052581745,0.00025629325,0.0003313101,0.00027900774,0.0005181066],"domain_scores_gemma":[0.9993189,0.000029762456,0.00013791677,0.00026046357,0.000052380834,0.00020058786],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006215942,0.00016357098,0.00020633789,0.000041641797,0.00017015601,0.000051480034,0.00023993102,0.00010129231,0.000017619612],"category_scores_gemma":[0.00006725062,0.00011911756,0.00008570825,0.00035405223,0.0003327781,0.000015291822,0.000112913665,0.00008662276,0.000028313274],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000079424746,0.0006179937,0.014081791,0.00009121017,0.0001016115,0.0000024789276,0.00042073693,0.0010250371,0.97346807,0.0022117388,0.0021241668,0.0057757352],"study_design_scores_gemma":[0.0022022924,0.003102379,0.022833645,0.0005289592,0.000583486,0.00077047496,0.0038641416,0.14385793,0.8006086,0.0009928786,0.016986739,0.0036685013],"about_ca_topic_score_codex":0.0000040958143,"about_ca_topic_score_gemma":0.000001957775,"teacher_disagreement_score":0.1728595,"about_ca_system_score_codex":0.000018490744,"about_ca_system_score_gemma":0.000049974158,"threshold_uncertainty_score":0.48574734},"labels":[],"label_agreement":null},{"id":"W2102552310","doi":"10.1109/icbbe.2009.5162334","title":"An MM-Based Optimization Algorithm for Sparse Linear Modeling on Microarray Data Analysis","year":2009,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Lasso (programming language); Feature selection; Computer science; Algorithm; Estimator; Context (archaeology); Data mining; Artificial intelligence; Mathematics; Statistics","score_opus":0.026854307070502285,"score_gpt":0.28870215813746125,"score_spread":0.26184785106695896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102552310","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":[0.030240899,0.00010839343,0.9692053,0.00012554675,0.000023689152,0.00014808543,0.00006741987,0.000024302437,0.000056349298],"genre_scores_gemma":[0.5371001,0.00002465107,0.4536491,0.0005964379,0.00025998417,0.0000054063776,0.008213466,0.000016951832,0.0001339222],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986806,0.00004631307,0.00024023335,0.0006826366,0.0001238979,0.00022632883],"domain_scores_gemma":[0.99829423,0.0000059844424,0.000070231195,0.0013940106,0.00013176582,0.00010379598],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028034675,0.0001711513,0.00021030496,0.0001400809,0.000096204705,0.000034379365,0.00040410235,0.0001438762,0.000030512076],"category_scores_gemma":[0.000016651591,0.00016195627,0.00017759178,0.00034387285,0.000015156733,0.000006360519,0.000028143744,0.00003915181,0.0000021119406],"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":[0.000027048924,0.00010690422,0.000045715125,0.0000012552988,0.00024667248,3.2554874e-7,0.000002122327,0.9690847,0.021892646,0.0000033061588,0.00030357935,0.008285761],"study_design_scores_gemma":[0.00035444263,0.00022875603,0.000012554677,0.0000018852254,0.00056374253,3.1741712e-7,0.0000113722745,0.9623906,0.03567962,0.000008091061,0.00054883276,0.00019978668],"about_ca_topic_score_codex":0.000010862117,"about_ca_topic_score_gemma":0.0000319463,"teacher_disagreement_score":0.5155562,"about_ca_system_score_codex":0.000012219454,"about_ca_system_score_gemma":0.000051599094,"threshold_uncertainty_score":0.6604385},"labels":[],"label_agreement":null},{"id":"W2102869475","doi":"10.1073/pnas.0608963104","title":"Noisy information processing through transcriptional regulation","year":2007,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":106,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Mitacs","keywords":"Inference; Bayes' theorem; Operon; Computer science; State (computer science); Computational biology; Occupancy; Artificial intelligence; Biology; Machine learning; Gene; Data mining; Bayesian probability; Genetics; Ecology; Algorithm","score_opus":0.023182912893601425,"score_gpt":0.28620597707253886,"score_spread":0.26302306417893745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102869475","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":[0.9916772,0.00023283418,0.0004426276,0.00067416916,0.000014532394,0.00010707759,0.0000045909755,0.0000052147234,0.0068417382],"genre_scores_gemma":[0.99591404,0.000014147141,0.0036472033,0.00021457729,0.00011848611,0.0000023842215,0.0000016368926,0.0000023825726,0.000085162064],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987074,0.0000032896153,0.000317811,0.00013154227,0.0007237711,0.00011617774],"domain_scores_gemma":[0.99924093,0.000008487412,0.00036293486,0.000007006527,0.00036221766,0.000018442928],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011284592,0.00006861104,0.000077655706,0.00008324012,0.00015600112,0.000016073376,0.0003225705,0.000093363524,0.000005970574],"category_scores_gemma":[0.00010312518,0.00005092832,0.000079782425,0.0005278901,0.00036727404,0.000089535795,0.000043566804,0.00005503723,6.382764e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023939221,0.00001589858,0.0039671604,0.00003485035,0.000014216448,3.9928097e-10,0.00011676533,0.0011577075,0.9810199,0.011624718,0.0004604493,0.001564368],"study_design_scores_gemma":[0.00015160252,0.000033119417,0.17164622,0.00003176165,0.000017149863,0.0000059849685,0.00014554581,0.0011314763,0.8112254,0.011774442,0.00375401,0.000083271225],"about_ca_topic_score_codex":0.0000014369143,"about_ca_topic_score_gemma":1.2658927e-7,"teacher_disagreement_score":0.16979451,"about_ca_system_score_codex":0.00001601988,"about_ca_system_score_gemma":0.0000335359,"threshold_uncertainty_score":0.20767966},"labels":[],"label_agreement":null},{"id":"W2103173634","doi":"10.1093/bioinformatics/btl497","title":"Cell++—simulating biochemical pathways","year":2006,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":55,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Hospital for Sick Children","keywords":"Computer science; Computational biology; Biology","score_opus":0.007429909915520843,"score_gpt":0.20236138685553787,"score_spread":0.19493147694001703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103173634","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":[0.9760568,0.0007981959,0.011893315,0.000019930223,0.000079603284,0.0001057301,0.000011829677,0.000037776656,0.010996831],"genre_scores_gemma":[0.9833036,0.00001640642,0.0153595405,0.00010740385,0.00035445398,0.0000050061044,0.000284661,0.000018753415,0.0005501716],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99904585,0.0000144286805,0.0003549279,0.00014709788,0.00016243663,0.00027524354],"domain_scores_gemma":[0.9993628,0.000007886086,0.00013051853,0.00037395695,0.00005877712,0.000066013374],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011808752,0.00015710044,0.00013250494,0.000045009972,0.00008515285,0.00003338723,0.00016883,0.00015532094,0.000018291716],"category_scores_gemma":[0.000017041719,0.00014942304,0.00013490955,0.00013778303,0.000048235856,0.000004376698,0.00010936033,0.000058318743,0.000060728413],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034534627,0.00019003177,0.012175158,0.0001654038,0.0000965807,0.0000044774415,0.00011989215,0.034028582,0.80246115,0.00038629016,0.14607711,0.004260782],"study_design_scores_gemma":[0.0011696144,0.00017684494,0.0026325595,0.00002324248,0.00010762881,0.000025026427,0.00029335238,0.14739135,0.78162324,0.00032314367,0.065322824,0.0009111813],"about_ca_topic_score_codex":0.0000061347105,"about_ca_topic_score_gemma":0.0000022874624,"teacher_disagreement_score":0.11336276,"about_ca_system_score_codex":0.000014898462,"about_ca_system_score_gemma":0.000042107786,"threshold_uncertainty_score":0.6093295},"labels":[],"label_agreement":null},{"id":"W2103776834","doi":"10.1016/j.drudis.2007.02.013","title":"Computational systems biology in drug discovery and development: methods and applications","year":2007,"lang":"en","type":"review","venue":"Drug Discovery Today","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":164,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; National Institute for Nanotechnology","funders":"","keywords":"Drug discovery; Systems biology; Modelling biological systems; Computer science; Petri net; Cellular automaton; Computational biology; Data science; Computational model; Drug development; Complex system; Biology; Artificial intelligence; Bioinformatics; Drug; Distributed computing","score_opus":0.022420638257823537,"score_gpt":0.34635196867688745,"score_spread":0.3239313304190639,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103776834","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00078203855,0.9565756,0.041537944,0.000007862572,0.000120519166,0.0006596296,0.000097407006,0.000010065761,0.00020894106],"genre_scores_gemma":[0.0015310345,0.98877007,0.0044414084,0.000038855836,0.00032429665,0.0003182204,0.002734547,0.00006290587,0.0017786766],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9973305,0.0004865491,0.00077910256,0.00091681955,0.00012293569,0.0003641091],"domain_scores_gemma":[0.99892294,0.00018363245,0.00033579115,0.00040926217,0.000040969724,0.00010741686],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009662168,0.00047157658,0.0010819491,0.00028454568,0.00012223668,0.00014552614,0.00025320728,0.00033048482,0.0000022574884],"category_scores_gemma":[0.000020638492,0.00041262677,0.00016897061,0.00030353188,0.00019589167,0.000019336105,0.00035535594,0.00021397437,0.0000052992045],"study_design_candidate":"not_applicable","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":[0.00001394974,0.00011376755,0.00079355255,0.004743771,0.0008127161,0.0000054745274,0.000100604906,0.001262543,0.000048366215,0.0024545318,0.0006598788,0.98899084],"study_design_scores_gemma":[0.00017079644,0.000008610009,0.00007624887,0.0005396182,0.00018649914,0.00003308244,0.000063300366,0.000048922637,0.000028092849,0.000103553975,0.9982664,0.00047484745],"about_ca_topic_score_codex":0.000038678845,"about_ca_topic_score_gemma":0.00008300893,"teacher_disagreement_score":0.9976066,"about_ca_system_score_codex":0.00006709038,"about_ca_system_score_gemma":0.00035509124,"threshold_uncertainty_score":0.9998326},"labels":[],"label_agreement":null},{"id":"W2104566280","doi":"10.51847/ohbyzcy","title":"10.51847/OhBYZCy","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Chemotaxis; Biological system; Noise (video); Parametric statistics; Escherichia coli; Physics; Flow (mathematics); Chemistry; Biophysics; Biology; Mechanics; Mathematics; Computer science; Biochemistry; Statistics; Artificial intelligence; Gene","score_opus":0.0036161009659552547,"score_gpt":0.17815894593799986,"score_spread":0.17454284497204461,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104566280","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07326256,0.00038972343,0.0000055922887,0.00014600062,0.0000023160508,0.00010813813,0.0000073414926,0.0000317579,0.92604655],"genre_scores_gemma":[0.015418827,0.000002334275,0.00014658683,0.00009591238,0.00025154668,0.000010708172,0.00006946499,0.000022546943,0.9839821],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992654,0.000034379187,0.00012032478,0.0002671844,0.000096550284,0.00021619201],"domain_scores_gemma":[0.999414,0.0000031434206,0.000019134033,0.0004079176,0.000033891774,0.000121887155],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00008436063,0.000115943745,0.00011298761,0.000029372984,0.000049587285,0.000015843643,0.00017360739,0.00008360159,0.92976266],"category_scores_gemma":[0.000010386041,0.000117344665,0.000096911106,0.00013486746,0.000023198972,0.0000012482059,0.00004588828,0.000032176515,0.83223367],"study_design_candidate":"not_applicable","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":[0.000071045084,0.000037081438,0.0000041166586,0.0000025514275,0.000088618,0.000002692839,0.0000029035682,0.0020178775,0.022733547,3.3249842e-7,0.086084984,0.8889542],"study_design_scores_gemma":[0.00012034538,0.00010920723,0.00009972691,0.0000024487572,0.000027320304,0.0000055138066,3.4173718e-7,0.0001298823,0.0028156952,9.074619e-7,0.9965368,0.00015181769],"about_ca_topic_score_codex":0.000003801845,"about_ca_topic_score_gemma":3.3078734e-7,"teacher_disagreement_score":0.9104518,"about_ca_system_score_codex":0.000007857946,"about_ca_system_score_gemma":0.00002193125,"threshold_uncertainty_score":0.47851768},"labels":[],"label_agreement":null},{"id":"W2105057212","doi":"10.1126/science.1106914","title":"Gene Regulation at the Single-Cell Level","year":2005,"lang":"en","type":"article","venue":"Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1130,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"William Osler Health System","funders":"","keywords":"Gene; Reporter gene; Biology; Function (biology); Escherichia coli; Fusion gene; Transcription (linguistics); Fusion protein; Computational biology; Cell biology; Limiting; Green fluorescent protein; Transcription factor; Cell; Genetics; Gene expression; Recombinant DNA","score_opus":0.020183849613835205,"score_gpt":0.23496227226499716,"score_spread":0.21477842265116195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105057212","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":[0.99526143,0.0008560007,0.0012828376,0.0004581807,0.0000641891,0.0000522313,0.0000019296954,0.0000058950095,0.0020173087],"genre_scores_gemma":[0.98795813,0.000017386788,0.0014971386,0.00022797333,0.00023891783,0.0000028094946,0.000009849603,0.0000055635974,0.010042204],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99918014,0.000020553814,0.000094003655,0.00028703143,0.00021913418,0.00019913596],"domain_scores_gemma":[0.9993827,0.000003987833,0.000051308525,0.00044001426,0.0000695957,0.000052417145],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003641408,0.000066537454,0.00004606332,0.00002683192,0.00027935865,0.000028357612,0.00030239482,0.000035456927,0.000050739585],"category_scores_gemma":[0.000023070434,0.00004816601,0.000046224694,0.00027567393,0.0003347503,0.00000475609,0.0001686703,0.000023816132,0.00006796397],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000029024663,0.000011717346,0.0005513217,4.7607884e-7,0.000002410634,7.839571e-8,0.000017533277,0.0048191124,0.98639417,0.0000062065433,0.0011719267,0.007022157],"study_design_scores_gemma":[0.00006937148,0.000022644981,0.010833449,7.5116566e-7,0.000007687482,0.0000058348096,0.000008567648,0.0010018981,0.9375763,0.000020266405,0.050381947,0.00007130942],"about_ca_topic_score_codex":0.0000016051083,"about_ca_topic_score_gemma":0.00006141107,"teacher_disagreement_score":0.04921002,"about_ca_system_score_codex":0.0000448133,"about_ca_system_score_gemma":0.0000635324,"threshold_uncertainty_score":0.21486291},"labels":[],"label_agreement":null},{"id":"W2105998918","doi":"10.1098/rstb.2011.0008","title":"Systems biology of stem cells: three useful perspectives to help overcome the paradigm of linear pathways","year":2011,"lang":"en","type":"review","venue":"Philosophical Transactions of the Royal Society B Biological Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":125,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Alberta Innovates","keywords":"Counterintuitive; Systems biology; Biology; Cognitive science; Causation; Epistemology; Computer science; Computational biology; Psychology","score_opus":0.10896132552759515,"score_gpt":0.2995616655499684,"score_spread":0.19060034002237325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105998918","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009372885,0.9834252,0.005391246,0.00026542583,0.0002785183,0.00083318446,0.00031789375,0.000012697864,0.00010294022],"genre_scores_gemma":[0.48128483,0.51816285,0.0002324835,0.000017963062,0.00020688053,0.00005493408,0.0000055298233,0.000013254515,0.000021267622],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99717474,0.00060181983,0.00086246623,0.00072081445,0.00027229261,0.00036789317],"domain_scores_gemma":[0.9981182,0.00023677254,0.0006435724,0.0007558404,0.00013262674,0.00011298695],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0010168885,0.0003920773,0.001300796,0.000042141106,0.00033603262,0.000010736208,0.0018774293,0.0007046912,0.000029941357],"category_scores_gemma":[0.000029318682,0.0001809896,0.0023606857,0.0007816531,0.002771358,0.000003819636,0.00018914539,0.00034731044,0.0000028478903],"study_design_candidate":"not_applicable","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":[0.00081625517,0.010484434,0.007232149,0.026258346,0.032827284,0.000003889145,0.0050064074,0.13123603,0.035237223,0.17130849,0.00092495966,0.57866454],"study_design_scores_gemma":[0.0027292368,0.025923725,0.0015836516,0.012737102,0.016780239,0.00011666034,0.006668186,0.010973264,0.026431825,0.05329343,0.833924,0.008838706],"about_ca_topic_score_codex":0.00008030093,"about_ca_topic_score_gemma":0.000006004481,"teacher_disagreement_score":0.832999,"about_ca_system_score_codex":0.0000334007,"about_ca_system_score_gemma":0.00018157787,"threshold_uncertainty_score":0.99994254},"labels":[],"label_agreement":null},{"id":"W2107181602","doi":"10.1371/journal.pone.0074324","title":"A Model for Cell Population Size Control Using Asymmetric Division","year":2013,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Simon Fraser University","funders":"","keywords":"Cell division; Multicellular organism; Division (mathematics); Population; Asymmetric cell division; Biology; Cell cycle; Biological system; Cell; Cell biology; Genetics; Mathematics","score_opus":0.028049466989097573,"score_gpt":0.22487561862257285,"score_spread":0.19682615163347528,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107181602","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":[0.94273585,0.00036262997,0.056368005,0.000039754417,0.000012008345,0.0004047759,0.000008190941,0.000009885907,0.000058895825],"genre_scores_gemma":[0.9814241,0.00001624699,0.017545743,0.00010940336,0.0001289804,0.00004820346,0.00006404187,0.000024719147,0.00063857366],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992237,0.00002764634,0.00016800218,0.00024417278,0.00014307682,0.00019340016],"domain_scores_gemma":[0.99941635,0.000021594798,0.000090331494,0.00025148486,0.00015529967,0.00006492895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000092983435,0.00010615746,0.00016825613,0.000050892682,0.000072650975,0.000022867116,0.0000884707,0.00011064465,0.000012766981],"category_scores_gemma":[0.00009065368,0.0001052024,0.000103897924,0.00012240653,0.000010386927,0.000004607144,0.000033960816,0.000031326996,0.000008404041],"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":[0.000016437549,0.0002968513,0.013884104,0.000031599833,0.00014139335,5.201428e-8,0.0000053668487,0.023630677,0.96135706,0.000004382822,0.00014565469,0.00048644215],"study_design_scores_gemma":[0.00064003764,0.000076540295,0.0055753808,0.000009767985,0.00021086863,1.3170545e-7,0.0000031382774,0.91074204,0.082394004,0.00020181015,0.000008486354,0.00013777129],"about_ca_topic_score_codex":0.000028637667,"about_ca_topic_score_gemma":0.0000060453017,"teacher_disagreement_score":0.88711137,"about_ca_system_score_codex":0.000019342302,"about_ca_system_score_gemma":0.000016881331,"threshold_uncertainty_score":0.42900294},"labels":[],"label_agreement":null},{"id":"W2109027308","doi":"10.1002/prot.22024","title":"Dark proteins: Effect of inclusion body formation on quantification of protein expression","year":2008,"lang":"en","type":"article","venue":"Proteins Structure Function and Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":34,"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":"Green fluorescent protein; Plasmid; Biology; Inclusion bodies; Gene expression; TetR; Gene; Escherichia coli; Computational biology; Synthetic biology; Cell biology; Molecular biology; Biochemistry; Repressor","score_opus":0.006125069600122186,"score_gpt":0.21174847970213262,"score_spread":0.20562341010201043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109027308","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":[0.9615519,0.00020366734,0.03668451,0.000022906077,0.000054936158,0.0012906763,0.000023018043,0.000016467955,0.00015193468],"genre_scores_gemma":[0.9947715,0.000052378513,0.0047014165,0.000019576255,0.00006331857,0.00004954603,0.00028127275,0.000013322048,0.000047683934],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99870235,0.000099479774,0.00053109415,0.00017666312,0.00034528243,0.00014510691],"domain_scores_gemma":[0.99883956,0.00000892145,0.00055874337,0.00038136664,0.0001532366,0.000058187485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024764246,0.00020522618,0.0002580546,0.00015246494,0.00026597668,0.0000086831415,0.00011274445,0.00021943223,0.000011188052],"category_scores_gemma":[0.00009075833,0.00015048777,0.00009487909,0.0002098514,0.000108303255,0.00003028998,0.00016917092,0.00010100136,0.000001333088],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00057676877,0.00003138343,0.0006584411,0.0005005597,0.000033906712,1.2783725e-7,0.00016081404,0.00035271654,0.9911486,0.0000519087,0.0001038608,0.0063809324],"study_design_scores_gemma":[0.0007698025,0.0017629788,0.0020529444,0.00012281748,0.000038150814,0.000011791867,0.0000342106,0.0033626535,0.9909982,0.00012314573,0.0005691858,0.00015408585],"about_ca_topic_score_codex":0.0000050888057,"about_ca_topic_score_gemma":0.0000034420887,"teacher_disagreement_score":0.033219602,"about_ca_system_score_codex":0.000015843349,"about_ca_system_score_gemma":0.000037159894,"threshold_uncertainty_score":0.6136713},"labels":[],"label_agreement":null},{"id":"W2109229530","doi":"10.1057/palgrave.ivs.9500055","title":"GeneVis: Simulation and Visualization of Genetic Networks","year":2003,"lang":"en","type":"article","venue":"Information Visualization","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Calgary","funders":"Canadian Institutes of Health Research; Health Research","keywords":"Representation (politics); Computer science; Context (archaeology); Visualization; Process (computing); Theoretical computer science; Artificial intelligence; Biology; Programming language","score_opus":0.007647089185397043,"score_gpt":0.26986271948794194,"score_spread":0.2622156303025449,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109229530","genre_codex":"methods","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":[0.32501024,0.00035404105,0.67407227,0.000002625522,0.000060276612,0.00015869286,0.0000018733698,0.000014861703,0.000325147],"genre_scores_gemma":[0.9984508,0.00023075755,0.0006926477,0.00011322695,0.000052833573,0.000010024348,0.0004044811,0.000013813661,0.000031403502],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898,0.00010976679,0.00047646405,0.00013406592,0.0001711383,0.00012855772],"domain_scores_gemma":[0.99914074,0.000011540754,0.0003125713,0.00019439508,0.00028886856,0.000051867966],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002293823,0.00012357361,0.00012483218,0.00014011985,0.000078177094,0.000035873,0.00005391393,0.00014490906,0.0000247998],"category_scores_gemma":[0.00013782269,0.0001340072,0.000046028432,0.00033235422,0.00003976338,0.000044461012,0.000024444531,0.000021405893,0.0000038787884],"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":[0.000018587825,0.000020760139,0.027784355,0.000039344177,0.000044802273,4.9723422e-8,0.00014450957,0.962348,0.0022712585,0.0036658675,0.00018280734,0.0034796954],"study_design_scores_gemma":[0.0006399392,0.00014886593,0.025863599,0.000019449588,0.000074769465,0.000005869842,0.00011274841,0.938899,0.013864201,0.00012082033,0.019975647,0.00027512832],"about_ca_topic_score_codex":0.0000028698764,"about_ca_topic_score_gemma":0.0000030434123,"teacher_disagreement_score":0.6734406,"about_ca_system_score_codex":0.000013263802,"about_ca_system_score_gemma":0.000034992,"threshold_uncertainty_score":0.5464655},"labels":[],"label_agreement":null},{"id":"W2109271243","doi":"10.1101/005629","title":"Extensive Regulation of Metabolism and Growth during the Cell Division Cycle","year":2014,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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":"National Institute of General Medical Sciences; National Institutes of Health","keywords":"Biology; Cell division; Gene expression; Gene; Cell cycle; Metabolism; Cell biology; Cellular respiration; Population; Carbon cycle; Genetics; Cell; Biochemistry; Mitochondrion; Ecology","score_opus":0.0042784250733068074,"score_gpt":0.18609929898711358,"score_spread":0.18182087391380677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109271243","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":[0.99312496,0.0041146358,0.0020507805,0.000065034714,0.00024349928,0.0003287594,0.000035198802,0.000030866126,0.000006283564],"genre_scores_gemma":[0.9977454,0.0006486191,0.00095861603,0.000053655847,0.00046066512,0.000039094746,0.000001161069,0.000081055594,0.00001176687],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99792224,0.00022203648,0.00043965763,0.00081038004,0.00028700705,0.00031868138],"domain_scores_gemma":[0.9974385,0.000022569875,0.0005494728,0.0012976851,0.0005624501,0.00012933274],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004806354,0.00039648608,0.00046861012,0.00012141942,0.00016926491,0.000062291096,0.00038926085,0.0004475464,0.000007522323],"category_scores_gemma":[0.00010664753,0.0003439679,0.00020801497,0.00020580683,0.00018125022,0.000006814298,0.00078026846,0.0002582163,0.000004067303],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021562471,0.000030152549,0.006220637,0.00021136588,0.00014958212,0.0000011556752,0.0000048750517,0.0021456047,0.9910709,0.00007040191,0.0000722289,0.0000014977608],"study_design_scores_gemma":[0.00023252734,0.000017269207,0.3828656,0.000047146805,0.0001573352,1.0663436e-8,0.0000012945553,0.0006427781,0.6153764,0.0000055119863,0.0003971823,0.00025692026],"about_ca_topic_score_codex":0.000023595572,"about_ca_topic_score_gemma":0.0000016551687,"teacher_disagreement_score":0.37664497,"about_ca_system_score_codex":0.00002758389,"about_ca_system_score_gemma":0.00010568296,"threshold_uncertainty_score":0.99990124},"labels":[],"label_agreement":null},{"id":"W2109949635","doi":"10.1109/iembs.2008.4649115","title":"Dynamic analysis of Probabilistic Boolean Network for fMRI study in Parkinson's Disease","year":2008,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"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":"","keywords":"Probabilistic logic; Computer science; Parkinson's disease; Disease; Functional connectivity; Abnormality; Neuroscience; Artificial intelligence; Machine learning; Psychology; Medicine; Psychiatry; Pathology","score_opus":0.010534456705989528,"score_gpt":0.24966584077126083,"score_spread":0.2391313840652713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109949635","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":[0.9944775,0.00057021884,0.004251803,0.00002412206,0.000027973252,0.00056563056,0.000016206759,0.000008603921,0.000057935104],"genre_scores_gemma":[0.9980933,0.00006160054,0.0010258938,0.000032018088,0.000041471565,0.00010099124,0.0002374228,0.00001850967,0.00038875802],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986361,0.00011752892,0.00035892354,0.00046696837,0.00014288766,0.00027759312],"domain_scores_gemma":[0.9990767,0.000030753174,0.00010824252,0.0005861177,0.0000888482,0.00010931667],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003332303,0.0001613778,0.00038892374,0.0001599044,0.00006108207,0.0000050341387,0.0001920711,0.00006461702,0.000021433965],"category_scores_gemma":[0.00006123207,0.00015109683,0.00034102018,0.0008414847,0.00007389283,0.0000018606727,0.00007074169,0.000036323338,8.45372e-7],"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":[0.00022018963,0.00037331466,0.72216946,0.000017429866,0.0011847513,0.000005643994,0.000026722628,0.2744281,0.0010261647,0.000019515915,0.00038202584,0.00014666216],"study_design_scores_gemma":[0.00066139485,0.00023311301,0.9317887,0.000004882921,0.0014678536,5.637921e-7,0.00006747935,0.064140074,0.00016156603,0.000093696144,0.0011603248,0.00022035642],"about_ca_topic_score_codex":0.000032023916,"about_ca_topic_score_gemma":0.0020993554,"teacher_disagreement_score":0.21028803,"about_ca_system_score_codex":0.000023679195,"about_ca_system_score_gemma":0.00008292244,"threshold_uncertainty_score":0.616155},"labels":[],"label_agreement":null},{"id":"W2110102919","doi":"10.1109/ccece.2008.4564564","title":"Complexity analysis and optimal experimental design for parameter estimation of biological systems","year":2008,"lang":"en","type":"article","venue":"Conference proceedings - Canadian Conference on Electrical and Computer Engineering","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nonlinear system; Computer science; Process (computing); Differential equation; Mathematical optimization; Estimation theory; Applied mathematics; Algorithm; Mathematics","score_opus":0.04338230205438941,"score_gpt":0.23128079133107018,"score_spread":0.1878984892766808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110102919","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":[0.61665654,0.00018752253,0.38293192,0.000020793297,0.000016791077,0.00016092854,0.000006043956,0.00000965979,0.000009782979],"genre_scores_gemma":[0.9826908,0.00006693226,0.01706554,0.000026146985,0.000054186934,0.000046495108,0.000029114753,0.000009292723,0.000011494795],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898905,0.000012381262,0.00021260131,0.00039364773,0.00008800103,0.0003043136],"domain_scores_gemma":[0.9994115,0.00002767936,0.000067002016,0.000081875674,0.00015233574,0.00025956525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009998546,0.00019353974,0.000329571,0.00022356484,0.00009527042,0.000056683726,0.00012274367,0.00013812087,0.0000039645065],"category_scores_gemma":[0.00002865841,0.0001826035,0.00007198986,0.0002462535,0.0001038007,0.000009311776,0.000032113683,0.00007662399,2.7039715e-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":[0.0010358536,0.0006015535,0.075763024,0.00050484645,0.006170116,0.000034829252,0.0021323375,0.43682763,0.31033522,0.1232634,0.0016628887,0.04166832],"study_design_scores_gemma":[0.00020531441,0.00061524246,0.0069869584,0.0000134779175,0.00006288763,0.000022473705,0.000014149987,0.98195887,0.009815782,0.000041555017,0.00004708949,0.00021621179],"about_ca_topic_score_codex":0.00032105288,"about_ca_topic_score_gemma":0.000032528616,"teacher_disagreement_score":0.54513127,"about_ca_system_score_codex":0.00002794435,"about_ca_system_score_gemma":0.000102000486,"threshold_uncertainty_score":0.74463546},"labels":[],"label_agreement":null},{"id":"W2110177138","doi":"10.1109/tcbb.2008.38","title":"A Trade-Off between Sample Complexity and Computational Complexity in Learning Boolean Networks from Time-Series Data","year":2009,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Computational Biology and Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Ottawa Hospital","funders":"","keywords":"Inference; Boolean network; Computational complexity theory; Series (stratigraphy); Expression (computer science); Maximum satisfiability problem; Mathematics; Boolean expression; Time complexity; Computer science; Boolean function; Algorithm; Time series; Gene regulatory network; Artificial intelligence; Machine learning; Gene; Biology; Gene expression","score_opus":0.03778213872369173,"score_gpt":0.28246628535343854,"score_spread":0.2446841466297468,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110177138","genre_codex":"methods","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":[0.317307,0.000297753,0.6804082,0.00088350347,0.000056747864,0.00018036373,0.0008004641,0.000034654637,0.00003132422],"genre_scores_gemma":[0.8878614,0.00014619093,0.10367254,0.00035675394,0.00011559384,0.0000032434855,0.007823064,0.000009832915,0.000011380447],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99855417,0.00015703554,0.0005039674,0.00039338143,0.00012988549,0.00026157883],"domain_scores_gemma":[0.9990635,0.00029822232,0.00015573822,0.00031998308,0.00004777841,0.00011477217],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00027339664,0.00024857416,0.00034011167,0.00012738847,0.00034861,0.00004972597,0.00028435324,0.00023782649,0.000023904235],"category_scores_gemma":[0.000033844004,0.00024849296,0.00006206886,0.0001836757,0.00042375334,0.000037634753,0.00003588,0.0002906333,0.000004834886],"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":[0.0002806979,0.0001903508,0.020683078,0.000023087572,0.00042619175,0.000001829653,0.00030846713,0.85530835,0.00028960212,0.00035262504,0.00033914953,0.12179655],"study_design_scores_gemma":[0.0010753435,0.00052601047,0.09863585,0.000027771404,0.000093809926,0.000021722053,0.00013148825,0.87537104,0.000115690804,0.022407385,0.001175879,0.00041798758],"about_ca_topic_score_codex":0.000027933562,"about_ca_topic_score_gemma":0.00008525421,"teacher_disagreement_score":0.5767357,"about_ca_system_score_codex":0.000018821862,"about_ca_system_score_gemma":0.000057341353,"threshold_uncertainty_score":0.9999967},"labels":[],"label_agreement":null},{"id":"W2110436410","doi":"10.1016/j.biosystems.2006.01.004","title":"Network topology and the evolution of dynamics in an artificial genetic regulatory network model created by whole genome duplication and divergence","year":2006,"lang":"en","type":"article","venue":"Biosystems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":91,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Evolvability; Network topology; Topology (electrical circuits); Computer science; Natural selection; Gene regulatory network; Divergence (linguistics); Biological network; Gene duplication; Genome; Network dynamics; Selection (genetic algorithm); Computational biology; Artificial intelligence; Biology; Mathematics; Evolutionary biology; Gene; Genetics; Computer network","score_opus":0.005007222817534633,"score_gpt":0.1976831929573428,"score_spread":0.19267597013980817,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110436410","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":[0.98084974,0.011442532,0.0072253346,0.00006957624,0.000059167538,0.0002801982,0.000023112196,0.000008020773,0.000042323423],"genre_scores_gemma":[0.99894094,0.000100620935,0.0002571025,0.00001743745,0.00032610056,0.000025734178,0.0002033859,0.000015433305,0.0001132239],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998705,0.00019834342,0.00038835756,0.00036569356,0.00009852137,0.00024407094],"domain_scores_gemma":[0.9993009,0.00001111925,0.00019513938,0.00038237273,0.00006546927,0.000044977496],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039961174,0.0001421391,0.00023855262,0.000032821637,0.00011117368,0.000016545291,0.0001331639,0.00019803253,9.5194855e-7],"category_scores_gemma":[0.0000061988235,0.0001225289,0.000041230403,0.00020051553,0.00025142846,0.000005131227,0.000081890685,0.000049975515,4.929515e-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":[0.00023946729,0.00006150667,0.2227741,0.00003879926,0.00006435078,6.8356974e-7,0.000044518252,0.4689654,0.30067953,0.0059937118,0.0007994832,0.00033842682],"study_design_scores_gemma":[0.00073150476,0.00012742325,0.11447998,0.00002048814,0.00010606627,0.00001285951,0.00016094508,0.87915975,0.0009809162,0.0036022114,0.0003163851,0.00030146967],"about_ca_topic_score_codex":0.00052675616,"about_ca_topic_score_gemma":0.0024159518,"teacher_disagreement_score":0.41019434,"about_ca_system_score_codex":0.00006673279,"about_ca_system_score_gemma":0.0000363624,"threshold_uncertainty_score":0.49965838},"labels":[],"label_agreement":null},{"id":"W2110482684","doi":"10.1142/9789812836939_0018","title":"DENSE GRAPHLET STATISTICS OF PROTEIN INTERACTION AND RANDOM NETWORKS","year":2008,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Bipartite graph; Inference; Computer science; Theoretical computer science; Random graph; Biological network; Statistical inference; Class (philosophy); Artificial intelligence; Mathematics; Statistics; Combinatorics; Graph","score_opus":0.007157168106747165,"score_gpt":0.2184539025583155,"score_spread":0.21129673445156835,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110482684","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":[0.89701134,0.0006572789,0.10195645,0.000012922721,0.000027683724,0.00010776362,0.000003640351,0.0000046767786,0.00021821364],"genre_scores_gemma":[0.99490064,0.0004070843,0.0038349726,0.000030073605,0.00006839394,0.000007665361,0.00004927952,0.0000089323885,0.00069295045],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994776,0.000048031055,0.00015774708,0.0001539021,0.00006331522,0.00009940648],"domain_scores_gemma":[0.99964637,0.000009045622,0.000072282564,0.00016080843,0.00006812877,0.0000433752],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000079076184,0.00007954752,0.00012410167,0.00003188225,0.000043275275,0.000003827341,0.00004277132,0.00006781072,0.00002490239],"category_scores_gemma":[0.000019530857,0.0000712285,0.000046740766,0.000067529785,0.000086123175,0.0000015176352,0.000036555855,0.000037391892,8.356046e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017335016,0.00027546735,0.06808675,0.00008492549,0.0011141786,0.000034042263,0.00015224954,0.022646692,0.85729307,0.0010864798,0.028979989,0.018512676],"study_design_scores_gemma":[0.010295792,0.001717331,0.04905162,0.000082682025,0.0005028948,0.0004996168,0.00037554174,0.083448954,0.81321645,0.00081272627,0.038479637,0.001516758],"about_ca_topic_score_codex":0.000017807668,"about_ca_topic_score_gemma":0.00004590681,"teacher_disagreement_score":0.09812148,"about_ca_system_score_codex":0.0000026975051,"about_ca_system_score_gemma":0.000014986977,"threshold_uncertainty_score":0.2904614},"labels":[],"label_agreement":null},{"id":"W2110690451","doi":"10.1146/annurev.micro.091208.073229","title":"Noise and Robustness in Prokaryotic Regulatory Networks","year":2010,"lang":"en","type":"review","venue":"Annual Review of Microbiology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":134,"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":"York University","keywords":"Robustness (evolution); Rotation formalisms in three dimensions; Gene regulatory network; Computer science; Synthetic biology; Architecture; Network topology; Topology (electrical circuits); Biology; Computational biology; Mathematics; Gene; Gene expression; Computer network; Genetics","score_opus":0.00807952240345158,"score_gpt":0.26811010882473285,"score_spread":0.2600305864212813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110690451","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00047140694,0.9982143,0.000048416412,0.000022027429,0.0002072159,0.0008954339,0.00008128642,0.0000066765265,0.000053253145],"genre_scores_gemma":[0.00007845679,0.9976561,0.00026124748,0.0001469133,0.00026593785,0.000087263725,0.0012017919,0.00006687869,0.00023542072],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99685067,0.00059906155,0.0012001204,0.00083938293,0.000058929,0.00045184285],"domain_scores_gemma":[0.9979709,0.000053344433,0.0007542603,0.0009622347,0.00015566967,0.000103585044],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00093918864,0.000571113,0.0026747184,0.00013138044,0.000033851942,0.000005367834,0.0005160634,0.0011614525,0.00002853369],"category_scores_gemma":[0.00013431473,0.0004693076,0.0006186647,0.00035485838,0.00037352229,0.000003763083,0.00040111298,0.0005305423,0.0000059806675],"study_design_candidate":"not_applicable","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":[0.000010312921,0.000084615465,0.000058294554,0.07722084,0.00032870934,0.00001123533,0.0000057557704,0.000042182564,0.0007244386,0.00002194903,0.005034291,0.91645736],"study_design_scores_gemma":[0.00013478,0.00009237206,0.000017499899,0.028484434,0.00072193803,0.00027523554,0.0000032664398,0.0000042600595,0.000031259075,0.0000014399797,0.96980673,0.0004268112],"about_ca_topic_score_codex":0.000004163127,"about_ca_topic_score_gemma":0.000045639175,"teacher_disagreement_score":0.9647724,"about_ca_system_score_codex":0.00002259236,"about_ca_system_score_gemma":0.00028786476,"threshold_uncertainty_score":0.9997759},"labels":[],"label_agreement":null},{"id":"W2111071122","doi":"10.1109/cec.2008.4631257","title":"Evolutionary exploration of Boolean networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Calgary","funders":"","keywords":"Attractor; Boolean network; Boolean function; Computer science; Heuristic; Evolutionary algorithm; Gene regulatory network; Evolutionary dynamics; Graph; Theoretical computer science; Entropy (arrow of time); Mathematics; Artificial intelligence; Biology; Algorithm; Gene; Genetics; Gene expression","score_opus":0.016148913593853644,"score_gpt":0.22123502522711236,"score_spread":0.2050861116332587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111071122","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":[0.8732911,0.0017516518,0.12100753,0.000074859956,0.00007420349,0.000079698366,0.0000013371013,0.000014895737,0.0037047577],"genre_scores_gemma":[0.9958886,0.00038303062,0.00148008,0.000057242214,0.00019319703,0.0000048565475,0.000087207016,0.000008494328,0.0018972991],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995004,0.000028281307,0.0001422389,0.0001470221,0.00008129407,0.00010074308],"domain_scores_gemma":[0.99960834,0.0000027074843,0.000051273208,0.00023268447,0.00006917633,0.000035839916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005043031,0.000065763415,0.00008248483,0.000026286385,0.000050513907,0.0000012696777,0.000074272975,0.00007315156,0.00004395925],"category_scores_gemma":[0.000008013131,0.00006280019,0.00008364033,0.00009928375,0.0000618875,0.0000035295677,0.000040054405,0.00002374473,0.0000056355334],"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":[0.0001713886,0.00027451344,0.086520396,0.000017317283,0.00046133588,0.000008805133,0.000109265275,0.43829244,0.32210037,0.0012893672,0.146026,0.0047287666],"study_design_scores_gemma":[0.0024184734,0.0013066508,0.17017914,0.000032803688,0.00025421282,0.00018911714,0.0004791157,0.14955436,0.54142296,0.0010601479,0.13152257,0.0015804596],"about_ca_topic_score_codex":0.0000063009916,"about_ca_topic_score_gemma":0.0000104359515,"teacher_disagreement_score":0.2887381,"about_ca_system_score_codex":0.00000509336,"about_ca_system_score_gemma":0.00002870317,"threshold_uncertainty_score":0.2560917},"labels":[],"label_agreement":null},{"id":"W2111931353","doi":"10.1186/1471-2105-10-s12-i1","title":"Trends in modeling Biomedical Complex Systems","year":2009,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":30,"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":"Ministero dell’Istruzione, dell’Università e della Ricerca; World Anti-Doping Agency","keywords":"Computer science; Data science; Multidisciplinary approach; Inference; Informatics; Management science; Complex system; Health informatics; Artificial intelligence; Engineering; Medicine","score_opus":0.028375283573716284,"score_gpt":0.2678424997625228,"score_spread":0.2394672161888065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111931353","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":[0.5026902,0.0011079789,0.48877102,0.0001838211,0.0002385775,0.00022030532,0.000022061962,0.00006154755,0.0067044757],"genre_scores_gemma":[0.97845125,0.000035689452,0.020566542,0.00014601508,0.00016676485,0.0000038042267,0.00041115523,0.000008844973,0.00020991768],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988966,0.000029778774,0.00046367163,0.00014018005,0.00019039559,0.0002793966],"domain_scores_gemma":[0.9994246,0.0000038127866,0.00008338309,0.00034939565,0.00003646928,0.0001023703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022416192,0.00014352614,0.00019644288,0.00021708898,0.000042256528,0.000033631248,0.0001930877,0.00016555462,0.000013047676],"category_scores_gemma":[0.00001621206,0.00013095688,0.00010775926,0.00035160076,0.000032476168,0.000005525665,0.000045152545,0.00006798049,0.000016710836],"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":[0.000074033014,0.00023004554,0.003553949,0.00010814576,0.000092580914,0.000004428596,0.0002794179,0.9337648,0.009984666,0.0005127583,0.01442504,0.036970098],"study_design_scores_gemma":[0.0003709184,0.000094752104,0.0012923316,0.000013550568,0.000015108601,0.000013546633,0.00016109107,0.9928091,0.00007769756,0.000019111752,0.004967002,0.00016575218],"about_ca_topic_score_codex":0.000008149133,"about_ca_topic_score_gemma":0.000021582593,"teacher_disagreement_score":0.47576106,"about_ca_system_score_codex":0.000023034163,"about_ca_system_score_gemma":0.000040741023,"threshold_uncertainty_score":0.5340266},"labels":[],"label_agreement":null},{"id":"W2112180211","doi":"10.1007/s11538-012-9766-5","title":"Deterministic Versus Stochastic Cell Polarisation Through Wave-Pinning","year":2012,"lang":"en","type":"article","venue":"Bulletin of Mathematical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":55,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Biotechnology and Biological Sciences Research Council; National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Royal Society","keywords":"CDC42; Cell polarity; GTPase; Polarization (electrochemistry); Stochastic modelling; Physics; Statistical physics; Motility; Biophysics; Biology; Biological system; Cell; Chemistry; Mathematics; Cell biology; Genetics","score_opus":0.02556545527888143,"score_gpt":0.2676125196223256,"score_spread":0.24204706434344414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112180211","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":[0.8610066,0.0020970756,0.12722756,0.00039590572,0.0003497664,0.00028849902,0.000021370732,0.000029744522,0.008583493],"genre_scores_gemma":[0.9871486,0.000015924848,0.012053426,0.00010970804,0.00029232306,0.000015231997,0.00007396123,0.000021927974,0.00026888828],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99880195,0.00013145231,0.0003611749,0.0002373305,0.00009545361,0.0003726526],"domain_scores_gemma":[0.99916375,0.00015212558,0.0001750267,0.00036217176,0.000056588302,0.00009034565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003356975,0.00017256232,0.0002875773,0.000032220487,0.000053514377,0.0000053105473,0.00014814008,0.00024306479,0.00048505326],"category_scores_gemma":[0.00034456968,0.00015349733,0.0001438402,0.000060551192,0.00018637061,0.0000013624015,0.0001329389,0.00008077104,0.00016599066],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011642706,0.0017735644,0.002638625,0.00062342273,0.0009272556,0.0000044151393,0.00087997766,0.0008301541,0.93413734,0.033392794,0.017766748,0.0058614286],"study_design_scores_gemma":[0.011242,0.0060633332,0.004899582,0.0002531691,0.002382197,0.00025032507,0.0011192096,0.0038580042,0.6046528,0.022827335,0.33875942,0.003692572],"about_ca_topic_score_codex":0.0000051768816,"about_ca_topic_score_gemma":4.810396e-7,"teacher_disagreement_score":0.3294845,"about_ca_system_score_codex":0.000012868813,"about_ca_system_score_gemma":0.000022239608,"threshold_uncertainty_score":0.62594396},"labels":[],"label_agreement":null},{"id":"W2112332161","doi":"10.1142/s0219720004000764","title":"MODELING AND SIMULATION OF MOLECULAR BIOLOGY SYSTEMS USING PETRI NETS: MODELING GOALS OF VARIOUS APPROACHES","year":2004,"lang":"en","type":"article","venue":"Journal of Bioinformatics and Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":138,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Petri net; Computer science; Concurrency; Process architecture; Stochastic Petri net; Representation (politics); Synchronization (alternating current); Systems biology; Theoretical computer science; Modeling and simulation; Distributed computing; Event (particle physics); Programming language; Computational biology; Simulation; Biology","score_opus":0.026486863741333418,"score_gpt":0.2677644995817309,"score_spread":0.24127763584039746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112332161","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":[0.50984734,0.0020712689,0.4879862,0.000012328948,0.000027954964,0.000041179406,0.00000661849,7.877351e-7,0.000006339826],"genre_scores_gemma":[0.95655334,0.00014757446,0.04318351,0.000021901391,0.000044092154,4.913934e-7,0.000041610023,0.0000070588503,3.9956558e-7],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99875927,0.000054661847,0.0008579495,0.00010434713,0.00009877158,0.00012502131],"domain_scores_gemma":[0.99890786,0.000029387144,0.0005755126,0.00008897077,0.00034049014,0.000057764726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037008128,0.00012502671,0.00036413447,0.00019406724,0.000044410845,0.000011731555,0.00009145174,0.0001622042,4.0650798e-7],"category_scores_gemma":[0.00004158734,0.000107186286,0.000095742434,0.00010549138,0.00009727175,0.000013059106,0.000068986024,0.00007064725,5.9830015e-8],"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":[0.00003846788,0.000024316902,0.0004462575,0.000059990787,0.0002050932,3.737689e-7,0.00009547715,0.9820989,0.015003216,0.0013066633,2.535651e-7,0.0007210162],"study_design_scores_gemma":[0.00060604705,0.00031426852,0.000019495119,0.000039570015,0.00008137962,0.00007938366,0.00019367528,0.99268085,0.00072882534,0.005153422,0.0000054997918,0.00009760578],"about_ca_topic_score_codex":0.00001880653,"about_ca_topic_score_gemma":9.1477375e-7,"teacher_disagreement_score":0.44670606,"about_ca_system_score_codex":0.000014927218,"about_ca_system_score_gemma":0.00012111885,"threshold_uncertainty_score":0.437093},"labels":[],"label_agreement":null},{"id":"W2113892406","doi":"10.1093/bioinformatics/btm491","title":"<i>CellLine</i>, a stochastic cell lineage simulator","year":2007,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"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 Calgary","funders":"","keywords":"Lineage (genetic); Computer science; Cellular differentiation; Cell fate determination; Bistability; Gene regulatory network; Biology; Gene; Biological system; Computational biology; Genetics; Physics; Gene expression","score_opus":0.0066561639445456245,"score_gpt":0.2249542220159751,"score_spread":0.21829805807142946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113892406","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":[0.5468209,0.0006047121,0.44865066,0.000017462628,0.00020925101,0.0002126097,0.000013403164,0.000042502408,0.0034284908],"genre_scores_gemma":[0.9849575,0.000028474848,0.012692756,0.00037365512,0.00044332363,0.0000029228524,0.00013446488,0.000028223103,0.0013386923],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99871933,0.000013554791,0.00047790242,0.00017200847,0.00021554442,0.00040166793],"domain_scores_gemma":[0.9989994,0.00002414759,0.00017229028,0.00051709486,0.0001023984,0.00018464187],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043720708,0.00020378028,0.0001772722,0.00008224772,0.000088625085,0.000028825489,0.00023467642,0.00018789784,0.000027683027],"category_scores_gemma":[0.000044742643,0.00019193922,0.00016485846,0.00020348406,0.000059261078,0.000005434195,0.00011565617,0.000090887974,0.00013879295],"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":[0.0005924909,0.00091046636,0.005771137,0.0006577333,0.00082462723,0.00003580624,0.0014578091,0.5142111,0.384041,0.0002761897,0.063205,0.028016645],"study_design_scores_gemma":[0.0027555756,0.00065382133,0.0011700267,0.00003938327,0.00031335844,0.000047096673,0.0007654967,0.32303372,0.49554664,0.000041427375,0.17408015,0.0015533029],"about_ca_topic_score_codex":0.000002058264,"about_ca_topic_score_gemma":0.000012334314,"teacher_disagreement_score":0.43813658,"about_ca_system_score_codex":0.000018542303,"about_ca_system_score_gemma":0.0000602341,"threshold_uncertainty_score":0.7827054},"labels":[],"label_agreement":null},{"id":"W2114704739","doi":"10.1109/iembs.2006.259377","title":"Inverting Amplifier Genetic Circuit Performance","year":2006,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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":"Computer science; Amplifier; Electronic engineering; Engineering; Telecommunications; Bandwidth (computing)","score_opus":0.00768477070998617,"score_gpt":0.19440573476063597,"score_spread":0.1867209640506498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114704739","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":[0.9807052,0.0004706452,0.005528115,0.000021986893,0.000047386573,0.00005345864,6.0253757e-7,0.000018552542,0.013154062],"genre_scores_gemma":[0.9931897,0.0000347392,0.0011333178,0.00019073824,0.00041464105,0.000008132357,0.00003565233,0.00001836014,0.004974717],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991827,0.000020643876,0.00018365342,0.0002686069,0.000104890336,0.00023952968],"domain_scores_gemma":[0.9995284,0.0000024908427,0.000048567737,0.0003300003,0.00004584536,0.000044700686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007772224,0.000113331414,0.00009327983,0.000032742842,0.00007858053,0.000018451674,0.0001336235,0.00008588262,0.00009814543],"category_scores_gemma":[0.0000058582073,0.00010771093,0.00008345771,0.00011525896,0.000038600298,0.0000015689127,0.00006015688,0.000037251248,0.000058418165],"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":[0.000008721934,0.000038963724,0.32305545,0.000016094538,0.00006413006,0.000002108936,0.0000066537395,0.010574883,0.64509344,0.00023188765,0.010547448,0.010360228],"study_design_scores_gemma":[0.0005287983,0.00013023858,0.4850052,0.000010047748,0.000080058264,0.000040065064,0.000024811003,0.007726409,0.42392272,0.0004758862,0.081419885,0.00063589227],"about_ca_topic_score_codex":0.00003270275,"about_ca_topic_score_gemma":0.00005244859,"teacher_disagreement_score":0.22117074,"about_ca_system_score_codex":0.000009804016,"about_ca_system_score_gemma":0.000027021182,"threshold_uncertainty_score":0.4392324},"labels":[],"label_agreement":null},{"id":"W2115740561","doi":"10.1098/rsif.2008.0086.focus","title":"Quantitative approaches to the study of bistability in the <i>lac</i> operon of <i>Escherichia coli</i>","year":2008,"lang":"en","type":"review","venue":"Journal of The Royal Society Interface","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":75,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Operon; Bistability; lac operon; trp operon; L-arabinose operon; Biology; Physics; Computational biology; Escherichia coli; Genetics; Gene; Quantum mechanics","score_opus":0.07556329113577047,"score_gpt":0.3091714371022537,"score_spread":0.23360814596648322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115740561","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1688974,0.8289762,0.00071356754,0.00025938236,0.00015256731,0.00092644925,0.000019365229,9.3738225e-7,0.00005409148],"genre_scores_gemma":[0.42036435,0.578734,0.00039193407,0.000102944425,0.0001713632,0.000029416624,0.0000030100975,0.0000370441,0.00016591522],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9964951,0.0014297736,0.0011535775,0.0002581319,0.00046105566,0.00020233972],"domain_scores_gemma":[0.9973441,0.00014247467,0.0014499348,0.00084445515,0.00017520685,0.000043822532],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016790441,0.0003173527,0.0011738028,0.000023204693,0.00009808388,0.000017467471,0.0018252378,0.00021020816,0.0000034812595],"category_scores_gemma":[0.00012592354,0.00014170389,0.0016835862,0.0005104031,0.00022313106,0.0000032372648,0.00040016163,0.0005998672,8.591926e-7],"study_design_candidate":"not_applicable","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":[0.0012940442,0.010883875,0.002906787,0.009745628,0.02452163,0.000009478641,0.075167306,0.64540005,0.0021624654,0.00004555324,0.14943287,0.0784303],"study_design_scores_gemma":[0.0011168063,0.0040779305,0.000577286,0.0026692478,0.0034518165,0.00005037617,0.028568,0.0010268504,0.0018724652,0.000013145046,0.95589423,0.0006818621],"about_ca_topic_score_codex":0.000058098052,"about_ca_topic_score_gemma":0.000105006824,"teacher_disagreement_score":0.80646133,"about_ca_system_score_codex":0.00007255754,"about_ca_system_score_gemma":0.0002601395,"threshold_uncertainty_score":0.5778517},"labels":[],"label_agreement":null},{"id":"W2116042682","doi":"10.5402/2012/419419","title":"Hybrid-Controlled Neurofuzzy Networks Analysis Resulting in Genetic Regulatory Networks Reconstruction","year":2012,"lang":"en","type":"article","venue":"ISRN Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Gene regulatory network; Computer science; Data mining; Fuzzy logic; Genetic algorithm; Artificial intelligence; Expression (computer science); Machine learning; Algorithm; Gene; Gene expression; Biology; Genetics","score_opus":0.00622289787016415,"score_gpt":0.21425115470494682,"score_spread":0.20802825683478268,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116042682","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":[0.9242999,0.002236217,0.07155507,0.000027771152,0.000504928,0.00039790937,0.000005480194,0.00004359601,0.0009291211],"genre_scores_gemma":[0.99096674,0.0004984269,0.0070010386,0.00024595822,0.0008275335,0.00003701238,0.00019000749,0.0000404278,0.0001928327],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970279,0.00020936804,0.0012309873,0.0003367548,0.00027942692,0.0009155813],"domain_scores_gemma":[0.9980824,0.00005120443,0.00057999644,0.0009161646,0.00011547657,0.000254755],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010509527,0.00038138652,0.0006897366,0.00044983465,0.00015987658,0.000069160466,0.000313825,0.00031150188,0.000024811767],"category_scores_gemma":[0.00011778117,0.00037215694,0.0005456223,0.00096031587,0.000115821786,0.0000371092,0.0001706463,0.00027788302,0.000014144511],"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":[0.00019578963,0.00006527405,0.23014107,0.000018411409,0.0010177947,0.000002644177,0.00008205959,0.7445353,0.0004658647,0.00002184596,0.00064429775,0.022809599],"study_design_scores_gemma":[0.0019596836,0.00005722239,0.10242839,0.000019373105,0.0008257779,0.000058592585,0.00014113548,0.8928151,0.00050083554,0.000014938975,0.00068924547,0.0004896959],"about_ca_topic_score_codex":0.000017690454,"about_ca_topic_score_gemma":0.000117750504,"teacher_disagreement_score":0.14827977,"about_ca_system_score_codex":0.000071256916,"about_ca_system_score_gemma":0.00005258822,"threshold_uncertainty_score":0.99987304},"labels":[],"label_agreement":null},{"id":"W2116830222","doi":"10.1109/iembs.2005.1616522","title":"Design of a Genetic Differential Amplifier","year":2005,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Computer science; Differential amplifier; Differential (mechanical device); Amplifier; Physics; Telecommunications; Bandwidth (computing)","score_opus":0.010779629984634602,"score_gpt":0.2249814667238386,"score_spread":0.21420183673920398,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116830222","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":[0.6239776,0.0003527012,0.37517983,0.00003159437,0.000021555072,0.000063421285,5.8005594e-7,0.0000053589524,0.00036734313],"genre_scores_gemma":[0.9807515,0.0000612329,0.01708693,0.00006265224,0.00022766613,0.000005899823,0.00001013834,0.000011780137,0.0017821853],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999385,0.000040642124,0.0001653885,0.0001834067,0.00008704315,0.00013854068],"domain_scores_gemma":[0.9995673,0.0000040600135,0.00004802515,0.00029144943,0.000042300002,0.000046904344],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004667831,0.00008736644,0.00010818145,0.000029298708,0.00002037119,0.0000053174276,0.00012069948,0.00007504031,0.00029970106],"category_scores_gemma":[0.000006163972,0.000076642034,0.00008322917,0.000059068454,0.000038385926,6.850372e-7,0.0000513801,0.00002140047,0.000017711618],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030821335,0.0000538228,0.0025059741,0.0000030726744,0.00011516452,2.9573874e-7,0.00001085631,0.020715684,0.9648996,0.00003015071,0.0029796201,0.008654943],"study_design_scores_gemma":[0.00058634824,0.00019907995,0.014070793,0.0000039503225,0.00011437733,0.00000989331,0.000014681455,0.01283094,0.9576859,0.000067353976,0.014137632,0.00027907497],"about_ca_topic_score_codex":0.0000031819561,"about_ca_topic_score_gemma":0.000010047961,"teacher_disagreement_score":0.3580929,"about_ca_system_score_codex":0.00000437327,"about_ca_system_score_gemma":0.000024722252,"threshold_uncertainty_score":0.32815164},"labels":[],"label_agreement":null},{"id":"W2119218276","doi":"10.1109/icdmw.2006.120","title":"Modeling Multiple Time Units Delayed Gene Regulatory Network Using Dynamic Bayesian Network","year":2006,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":35,"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 Windsor","funders":"","keywords":"Dynamic Bayesian network; Gene regulatory network; Computer science; Heuristic; Bayesian network; Variable-order Bayesian network; Markov process; Markov chain; Bayesian probability; Computational biology; Gene; Artificial intelligence; Machine learning; Gene expression; Data mining; Bayesian inference; Biology; Genetics; Mathematics","score_opus":0.007470035747196858,"score_gpt":0.2082924613794242,"score_spread":0.20082242563222735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2119218276","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":[0.71416336,0.0027967626,0.28221172,0.000015268733,0.00013231524,0.00017751729,0.0000065941895,0.00006512948,0.00043136216],"genre_scores_gemma":[0.9655588,0.000038592312,0.030137336,0.00019940676,0.0016849882,0.000009469817,0.00057264796,0.00010300259,0.0016957325],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974372,0.00016088727,0.00055765675,0.00071855396,0.00025682247,0.0008689037],"domain_scores_gemma":[0.9985978,0.000015078093,0.00014306503,0.0008675479,0.00021265831,0.00016386462],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00040507008,0.00039593034,0.00037122387,0.00006421588,0.00035718788,0.000049542636,0.00031584591,0.00036581632,0.000065471],"category_scores_gemma":[0.000015204128,0.0004148254,0.0002257699,0.0006444265,0.00007361265,0.000007921053,0.00021300712,0.0001304297,0.000022661623],"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":[0.000050276194,0.000021405534,0.0015563389,0.0000030706215,0.000155379,0.000004318028,0.000002650047,0.8686525,0.12680134,0.000028287568,0.0023739717,0.00035042912],"study_design_scores_gemma":[0.000446745,0.00004615166,0.0004197626,0.000016409287,0.00015732482,0.000024834062,0.000008538183,0.9923183,0.0048487703,0.00031378376,0.00089074764,0.0005086632],"about_ca_topic_score_codex":0.00018427463,"about_ca_topic_score_gemma":0.0006765752,"teacher_disagreement_score":0.2520744,"about_ca_system_score_codex":0.00007109613,"about_ca_system_score_gemma":0.00013538892,"threshold_uncertainty_score":0.99983037},"labels":[],"label_agreement":null},{"id":"W2120625059","doi":"10.1093/bioinformatics/btn246","title":"Estimating dynamic models for gene regulation networks","year":2008,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; National Science Foundation","keywords":"Ode; Gene regulatory network; Ordinary differential equation; Computer science; Smoothing; Systems biology; Biological network; Mathematical optimization; Process (computing); Algorithm; Theoretical computer science; Applied mathematics; Mathematics; Differential equation; Computational biology; Biology; Gene; Gene expression","score_opus":0.013247565527927451,"score_gpt":0.2320814970041585,"score_spread":0.21883393147623106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2120625059","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":[0.16165663,0.000304023,0.837361,0.000019812498,0.00013255877,0.00022047391,0.000008816393,0.000025892574,0.00027080084],"genre_scores_gemma":[0.7173173,0.000069380614,0.2812428,0.00009427863,0.00021869481,0.000025706213,0.0006225068,0.0000220089,0.00038736497],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990759,0.000013545726,0.0003668857,0.00015457855,0.00012474596,0.00026437372],"domain_scores_gemma":[0.9992439,0.000011034143,0.00017874748,0.0003772599,0.00011566958,0.000073360185],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016057232,0.00015366811,0.00015774589,0.000049613547,0.0002136464,0.00001729955,0.00014839221,0.00015780838,0.0000037650475],"category_scores_gemma":[0.000027276647,0.00015264573,0.00014540831,0.00011611932,0.00005538366,0.000013045168,0.00006171224,0.00004229227,0.000004989488],"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":[0.00001869745,0.000012898189,0.00011183561,0.000022719125,0.00006302364,2.7554606e-7,0.00007431234,0.99065655,0.002679457,0.000044760876,0.0023631013,0.0039523654],"study_design_scores_gemma":[0.00030885002,0.00006413229,0.0002940096,0.0000071860204,0.000036442332,0.000032397395,0.000018514002,0.99602324,0.0018371253,0.00021605298,0.0009747797,0.00018729818],"about_ca_topic_score_codex":0.0000016189534,"about_ca_topic_score_gemma":0.000004436702,"teacher_disagreement_score":0.5561182,"about_ca_system_score_codex":0.000024235918,"about_ca_system_score_gemma":0.000047265716,"threshold_uncertainty_score":0.6224713},"labels":[],"label_agreement":null},{"id":"W2120748206","doi":"10.1109/isb.2011.6033114","title":"Inferring gene regulatory networks from multiple time course gene expression datasets","year":2011,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Inference; Computer science; Gene regulatory network; Constraint (computer-aided design); Data mining; Scheme (mathematics); Machine learning; Artificial intelligence; Gene; Gene expression; Mathematics; Biology; Genetics","score_opus":0.012248466514259586,"score_gpt":0.21622474495555452,"score_spread":0.20397627844129493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2120748206","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":[0.9761422,0.0019728881,0.020881997,0.000007699137,0.00014527355,0.00015152682,0.00012349772,0.000055285822,0.0005196075],"genre_scores_gemma":[0.979624,0.00011335103,0.014259621,0.00017611227,0.0005787455,0.000017261344,0.004579226,0.00005269846,0.00059898227],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983337,0.0001027761,0.00032184614,0.00066008815,0.00018548834,0.00039608605],"domain_scores_gemma":[0.9982838,0.000013836549,0.00013790227,0.001284513,0.000059246828,0.00022068615],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00019252753,0.00027874543,0.0002527594,0.00004057883,0.00012629977,0.00002116149,0.00039111503,0.00029359918,0.00059413863],"category_scores_gemma":[0.000020465457,0.00026140065,0.00015934472,0.00010315136,0.00008549018,0.0000093314,0.00040096577,0.00010291772,0.00009174831],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006670824,0.00009481961,0.014079203,0.0000014926478,0.00015714011,0.000009627072,0.000021782287,0.0027123739,0.96825,0.0000020889022,0.013193782,0.0014109861],"study_design_scores_gemma":[0.00052231725,0.00005123961,0.037794724,0.000012763951,0.00011312335,0.000006739513,0.000013498622,0.013085685,0.94423604,0.000025150826,0.0037468832,0.00039180895],"about_ca_topic_score_codex":0.00010155391,"about_ca_topic_score_gemma":0.000058552127,"teacher_disagreement_score":0.02401393,"about_ca_system_score_codex":0.000015507127,"about_ca_system_score_gemma":0.000038752434,"threshold_uncertainty_score":0.99998385},"labels":[],"label_agreement":null},{"id":"W2121653135","doi":"10.1093/bioinformatics/btr472","title":"Conserved and differential gene interactions in dynamical biological systems","year":2011,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"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":"Core Research for Evolutional Science and Technology; National Cancer Institute; U.S. Department of Agriculture; New Mexico State University; National Science Foundation","keywords":"Computational biology; Differential (mechanical device); Gene; Biology; Computer science; Genetics; Physics","score_opus":0.02893718377708309,"score_gpt":0.23776513239720018,"score_spread":0.20882794862011708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121653135","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":[0.9939089,0.00018819245,0.0050495765,0.00000894871,0.00013097326,0.00010582259,0.000010089133,0.000010546132,0.0005869942],"genre_scores_gemma":[0.9973057,0.000115061834,0.0023042937,0.0000305671,0.000053610183,0.0000115804005,0.000091988026,0.0000063505563,0.00008086642],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99932885,0.00003918079,0.0002926435,0.000119021955,0.000055187513,0.00016511316],"domain_scores_gemma":[0.99962497,0.000007770127,0.000075438875,0.00019323865,0.000028366292,0.00007019679],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000080240454,0.00011023259,0.00014690006,0.000058302183,0.000035808753,0.000018674202,0.000095086165,0.00009486022,0.000020798025],"category_scores_gemma":[0.000021616954,0.00009088919,0.000051870567,0.000068159,0.00008205989,0.000004712125,0.00010568084,0.00006413788,0.000009696395],"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":[0.0006054107,0.00082572084,0.5865868,0.00028222732,0.0009555919,0.000030454808,0.0019867094,0.000626844,0.39385313,0.0025184564,0.002844225,0.008884463],"study_design_scores_gemma":[0.0034089792,0.0008134348,0.50549865,0.000104217754,0.00020901993,0.0004198564,0.0023380395,0.43758157,0.03904913,0.0002046308,0.008815193,0.0015572632],"about_ca_topic_score_codex":0.000029977975,"about_ca_topic_score_gemma":0.00006112522,"teacher_disagreement_score":0.43695474,"about_ca_system_score_codex":0.000011830404,"about_ca_system_score_gemma":0.000017802377,"threshold_uncertainty_score":0.37063536},"labels":[],"label_agreement":null},{"id":"W2121763778","doi":"10.1101/gr.088260.108","title":"Incorporating nucleosomes into thermodynamic models of transcription regulation","year":2009,"lang":"en","type":"article","venue":"Genome Research","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":104,"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":"Azrieli Foundation; Israel Science Foundation","keywords":"Nucleosome; Biology; Promoter; Cooperativity; Transcription (linguistics); Transcription factor; Computational biology; Genetics; Histone; DNA; Cell biology; Gene expression; Gene","score_opus":0.03219821159713682,"score_gpt":0.3042016877291,"score_spread":0.2720034761319632,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121763778","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":[0.98609596,0.001613336,0.010127917,0.00020357041,0.000014543965,0.00017825051,0.000002592579,0.000009548516,0.001754254],"genre_scores_gemma":[0.99752253,0.00016893781,0.0017279927,0.00001516812,0.00013355259,0.000007060851,0.000104670915,0.000015708572,0.00030435243],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9986164,0.00020554989,0.00024536264,0.00030358063,0.00037112305,0.00025800584],"domain_scores_gemma":[0.9991554,0.0000080146865,0.000070865826,0.00042580426,0.00027231086,0.000067579465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008670043,0.00009901742,0.00014530933,0.00018422854,0.00012709637,0.000018564646,0.00022864726,0.00013020581,0.000019114284],"category_scores_gemma":[0.000017936114,0.000098381366,0.00010188457,0.00040149956,0.00010578681,0.000008677581,0.000045317316,0.000108995715,0.000006221477],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046645484,0.00003690798,0.00010750313,0.000015641845,0.00003208812,4.7853763e-7,0.00013806648,0.017593477,0.9716794,0.0010630697,0.000029466039,0.009257277],"study_design_scores_gemma":[0.001571848,0.0020806135,0.08071068,0.00008109833,0.00008845727,0.000015218248,0.00079796585,0.23183584,0.4797811,0.20034513,0.0018112715,0.00088079186],"about_ca_topic_score_codex":0.000024076684,"about_ca_topic_score_gemma":0.000028565079,"teacher_disagreement_score":0.4918983,"about_ca_system_score_codex":0.00004049188,"about_ca_system_score_gemma":0.00008147298,"threshold_uncertainty_score":0.40118757},"labels":[],"label_agreement":null},{"id":"W2121800741","doi":"10.1016/j.febslet.2005.02.039","title":"<i>FEBS Letters</i> Updates","year":2005,"lang":"sah","type":"article","venue":"FEBS Letters","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Office of the Chief Medical Examiner","funders":"","keywords":"Editorial board; Theme (computing); Publication; Computer science; Reading (process); Special section; Library science; World Wide Web; Engineering ethics; Political science; Engineering; Law","score_opus":0.005121012719526617,"score_gpt":0.2072006087801551,"score_spread":0.20207959606062847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121800741","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":[0.94258547,0.0067889276,0.0015654258,0.047409162,0.00064553856,0.00026857996,0.000053287255,0.000052046395,0.0006315561],"genre_scores_gemma":[0.93446815,0.00065686344,0.0018687982,0.055638164,0.005184609,0.000025652002,0.000491171,0.00012269245,0.0015438915],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99640656,0.00024256886,0.0006472604,0.0011645263,0.00043504348,0.0011040577],"domain_scores_gemma":[0.997928,0.000024542314,0.00029567254,0.0013646737,0.00007414438,0.00031291833],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003323592,0.0006686045,0.00054264505,0.0001572209,0.0002638798,0.00015799665,0.00075506594,0.00036129847,0.0004308833],"category_scores_gemma":[0.000029223951,0.00072417787,0.0006615383,0.00035558338,0.00030768893,0.000019015231,0.00033599997,0.00033309165,0.0008912206],"study_design_candidate":"not_applicable","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":[0.00004673985,0.000059278504,0.002925294,0.000028229657,0.00047976125,0.000024040573,0.000064247564,0.007426463,0.677435,0.000014109304,0.30840912,0.0030877192],"study_design_scores_gemma":[0.0008813084,0.00008379466,0.0014276505,0.000041317493,0.00042442617,0.000044289565,0.000043556982,0.00066766434,0.2469696,0.000004269388,0.74846244,0.0009497071],"about_ca_topic_score_codex":0.000032985496,"about_ca_topic_score_gemma":0.0000974834,"teacher_disagreement_score":0.44005328,"about_ca_system_score_codex":0.0001555782,"about_ca_system_score_gemma":0.000087526074,"threshold_uncertainty_score":0.9998867},"labels":[],"label_agreement":null},{"id":"W2121806138","doi":"10.1038/msb4100187","title":"Programming gene expression with combinatorial promoters","year":2007,"lang":"en","type":"article","venue":"Molecular Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":381,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Sandia National Laboratories; National Institute of General Medical Sciences; National Institutes of Health; Fondation pour la Recherche Médicale; Alberta Heritage Foundation for Medical Research; National Physical Science Consortium; California Institute of Technology","keywords":"Promoter; Biology; Computational biology; Synthetic biology; Gene; Genetics; Cis-regulatory module; Regulation of gene expression; Transcription factor; Gene expression","score_opus":0.004974958743792781,"score_gpt":0.22577532538790268,"score_spread":0.2208003666441099,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121806138","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":[0.81831956,0.0016551039,0.17876756,0.000019614235,0.0004925129,0.00042716975,0.000003088596,0.000037445363,0.00027796716],"genre_scores_gemma":[0.99651814,0.000009241159,0.002574437,0.000045588073,0.00043780264,0.00005064027,0.0002093189,0.000047828875,0.00010703505],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9981404,0.00018838141,0.00034020634,0.0006172637,0.0001636065,0.0005501322],"domain_scores_gemma":[0.9989023,0.0000082232855,0.00018386256,0.0006082735,0.00013613106,0.0001611611],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005834578,0.0002650437,0.00029638718,0.00009970136,0.00010299272,0.000029996987,0.00025999077,0.00034848097,0.0000030479257],"category_scores_gemma":[0.000025161042,0.00021476182,0.00012087883,0.0002082579,0.00013346825,0.0000026531059,0.000116129806,0.000104683924,0.0000080533855],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013619606,0.000055961944,0.010402909,0.00002010416,0.000164878,0.0000504125,0.000016678065,0.00035138294,0.9870397,0.00022017905,0.00009447805,0.0014471405],"study_design_scores_gemma":[0.0010409295,0.00082783244,0.0003193515,0.00003077534,0.00006353407,0.00014619711,0.00007935688,0.00006798645,0.96484977,0.00002598998,0.032129783,0.00041847365],"about_ca_topic_score_codex":0.00004955323,"about_ca_topic_score_gemma":0.000017972794,"teacher_disagreement_score":0.17819858,"about_ca_system_score_codex":0.00003088063,"about_ca_system_score_gemma":0.000056506495,"threshold_uncertainty_score":0.87577325},"labels":[],"label_agreement":null},{"id":"W2123027306","doi":"10.5555/2693848.2694278","title":"Neuron time warp","year":2014,"lang":"en","type":"article","venue":"Winter Simulation Conference","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Neuron; Fidelity; Monte Carlo method; Scale (ratio); Biological neuron model; Biological system; Artificial intelligence; Artificial neural network; Neuroscience; Mathematics; Physics","score_opus":0.01142769606616179,"score_gpt":0.2421679467061566,"score_spread":0.23074025063999481,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123027306","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":[0.810447,0.00003113492,0.1841144,0.00025494272,0.00012006761,0.00008821774,0.0000029446107,0.000032667347,0.0049086786],"genre_scores_gemma":[0.99502003,0.0000014451188,0.00024874727,0.00027576124,0.00024412174,0.0000027833873,0.00010319038,0.000013229476,0.0040906733],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992826,0.00007766438,0.00014117236,0.00026805038,0.00009393052,0.00013658374],"domain_scores_gemma":[0.9994243,0.000012761117,0.00005701527,0.00034294243,0.00010665551,0.00005632769],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009821925,0.00010553216,0.00010010322,0.00003117692,0.000041197127,0.00002927081,0.00014367,0.00007263451,0.00025379634],"category_scores_gemma":[0.000039474042,0.00010416372,0.000071744595,0.0000552662,0.000033146476,0.0000035265862,0.00006591615,0.000040334784,0.00025487898],"study_design_candidate":"simulation_or_modeling","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":[0.00007886444,0.000057577883,0.008003149,0.000010570765,0.00010574401,9.1515346e-7,0.000086933156,0.37693802,0.5773353,0.0002761521,0.005722307,0.03138448],"study_design_scores_gemma":[0.00033626065,0.00014943191,0.0096841175,0.000007809094,0.0000297133,0.0000017861336,0.000004935928,0.7841158,0.014794485,0.0001956307,0.19044429,0.00023575916],"about_ca_topic_score_codex":0.0000013538519,"about_ca_topic_score_gemma":0.000005118513,"teacher_disagreement_score":0.5625408,"about_ca_system_score_codex":0.000005097904,"about_ca_system_score_gemma":0.000017093333,"threshold_uncertainty_score":0.42476732},"labels":[],"label_agreement":null},{"id":"W2123715799","doi":"","title":"A graph theoretical approach for analysis of protein flexibility change at protein complex formation.","year":2005,"lang":"en","type":"article","venue":"PubMed","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hatch (Canada)","funders":"","keywords":"Computer science; Rigidity (electromagnetism); Biological system; Monomer; Intermolecular force; Graph; Complex network; Chemistry; Algorithm; Theoretical computer science; Molecule; Materials science; Biology","score_opus":0.047494084793967044,"score_gpt":0.25444678882164357,"score_spread":0.20695270402767652,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123715799","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":[0.96002936,0.00037107882,0.03546314,0.0002548279,0.0000065915424,0.003217369,0.00008205614,0.00001742349,0.0005581194],"genre_scores_gemma":[0.9849887,0.0000055798864,0.0057808305,0.00007597478,0.00015620708,0.007974961,0.0007285883,0.000015626545,0.00027351355],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99861646,0.000104986335,0.00035544185,0.00038206493,0.00018470874,0.00035634649],"domain_scores_gemma":[0.99902695,0.000007305314,0.00017309315,0.00054331083,0.00013570834,0.00011361091],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061967387,0.0001569347,0.00032404615,0.00015837308,0.00008379103,0.00001186306,0.0002085099,0.00013580482,0.000031484677],"category_scores_gemma":[0.00006269602,0.0001398003,0.000454752,0.00052012544,0.00021284049,0.0000070498036,0.00011084052,0.00003847267,7.530393e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0044786935,0.0037290403,0.02099358,0.0014516447,0.01908942,0.0000013292376,0.00085053296,0.02517256,0.5322612,0.044663616,0.0043769004,0.34293148],"study_design_scores_gemma":[0.002889743,0.00027918402,0.16467693,0.00000968893,0.0036818855,0.00000539554,0.00010946215,0.14641403,0.65817076,0.001908212,0.020661669,0.0011930277],"about_ca_topic_score_codex":0.0000043281348,"about_ca_topic_score_gemma":0.000045858545,"teacher_disagreement_score":0.34173843,"about_ca_system_score_codex":0.000043167744,"about_ca_system_score_gemma":0.000010537595,"threshold_uncertainty_score":0.57008904},"labels":[],"label_agreement":null},{"id":"W2124614690","doi":"10.1098/rsta.2010.0139","title":"Robust dynamics in minimal hybrid models of genetic networks","year":2010,"lang":"en","type":"article","venue":"Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Ottawa Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Ottawa Hospital Research Institute","keywords":"Robustness (evolution); Computer science; Gene regulatory network; Transcription factor; Systems biology; Computational biology; Evolutionary dynamics; Transcription (linguistics); Gene; Biology; Theoretical computer science; Genetics; Gene expression","score_opus":0.01179837581547695,"score_gpt":0.2069994470288164,"score_spread":0.19520107121333946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124614690","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":[0.808708,0.00005662346,0.19076815,0.00029056144,0.000033342465,0.000064273365,0.000004802218,0.0000050300027,0.00006922195],"genre_scores_gemma":[0.99215835,0.0000125717515,0.0077132327,0.000009241536,0.000082510975,0.000007333002,7.5963106e-7,0.00000792393,0.000008094583],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99921703,0.000015000499,0.00021495835,0.0002033324,0.00017815076,0.0001715226],"domain_scores_gemma":[0.99963224,0.00005489377,0.00004614539,0.00018076482,0.000024768418,0.00006121188],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015814474,0.00011445781,0.00021059862,0.000015640442,0.00006562957,0.000008790073,0.00024745348,0.000076717144,0.00000388019],"category_scores_gemma":[0.000019887691,0.00008144679,0.0002656256,0.00020745184,0.0005316017,0.0000059730087,0.00003716012,0.00020606832,1.3888695e-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":[0.0000042797687,0.00014187592,0.0001095485,0.00005241281,0.00003577796,8.407534e-8,0.00002952067,0.9870523,0.00617885,0.006215464,0.0000023140071,0.00017755342],"study_design_scores_gemma":[0.00009364001,0.000055824625,0.00047850268,0.000020208963,0.000038793172,0.0000026052392,0.0000151614495,0.97400516,0.0015300256,0.023671199,0.0000010264956,0.00008785969],"about_ca_topic_score_codex":0.0000054542834,"about_ca_topic_score_gemma":0.0000031493753,"teacher_disagreement_score":0.18345034,"about_ca_system_score_codex":0.0000065257873,"about_ca_system_score_gemma":0.000017455568,"threshold_uncertainty_score":0.3321304},"labels":[],"label_agreement":null},{"id":"W2126217289","doi":"10.1007/s00285-013-0661-y","title":"Adiabatic reduction of a model of stochastic gene expression with jump Markov process","year":2013,"lang":"en","type":"article","venue":"Journal of Mathematical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; McGill University Health Centre","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; National Natural Science Foundation of China","keywords":"Jump process; Adiabatic process; Statistical physics; Bursting; Mathematics; Markov process; Ordinary differential equation; Stochastic differential equation; Stochastic process; Jump; Scaling; Applied mathematics; Compound Poisson process; Markov chain; Expression (computer science); Differential equation; Poisson distribution; Physics; Mathematical analysis; Computer science; Statistics; Biology; Poisson process; Thermodynamics; Quantum mechanics","score_opus":0.010661882309970727,"score_gpt":0.24748381909310416,"score_spread":0.23682193678313343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2126217289","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":[0.85758305,0.00025726363,0.14188637,0.00004920993,0.000020558924,0.000110542336,0.0000024372414,0.0000014324372,0.00008914812],"genre_scores_gemma":[0.9766265,0.000019045372,0.02316328,0.000008362528,0.00008068544,0.00000798944,0.000003842136,0.000012537815,0.00007771708],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99892545,0.000070381735,0.0005807946,0.00013351592,0.00014102628,0.00014881448],"domain_scores_gemma":[0.9985971,0.000027226411,0.00065717637,0.0002156236,0.00041839128,0.00008448758],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025035476,0.000120778685,0.00041366002,0.000094368166,0.0000172828,0.0000032454504,0.00017905986,0.00014440951,0.00008601799],"category_scores_gemma":[0.00011741155,0.00007769087,0.00013262808,0.00009666115,0.00017284171,0.0000067636197,0.000037600625,0.000084081774,0.0000017788409],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000116182324,0.00015529916,0.00013630881,0.000112579386,0.00015340622,3.00777e-7,0.000060748804,0.010696697,0.9879247,0.000056468652,0.00021477517,0.00037253278],"study_design_scores_gemma":[0.00087676244,0.0015511822,0.00014057994,0.00023148216,0.00028763266,0.00025390118,0.00026126264,0.034871906,0.94297236,0.018351225,0.0000035967937,0.00019810734],"about_ca_topic_score_codex":8.039408e-7,"about_ca_topic_score_gemma":2.650516e-7,"teacher_disagreement_score":0.1190435,"about_ca_system_score_codex":0.0000084850435,"about_ca_system_score_gemma":0.00009319848,"threshold_uncertainty_score":0.31681418},"labels":[],"label_agreement":null},{"id":"W2127006594","doi":"10.1529/biophysj.105.073098","title":"A Fluctuation Method to Quantify In Vivo Fluorescence Data","year":2006,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":80,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Canadian Aeronautics and Space Institute; Searle Scholars Program; Burroughs Wellcome Fund","keywords":"Fluorescence; Biological system; Partition (number theory); Division (mathematics); Computer science; Calibration; Algorithm; Data set; Set (abstract data type); In vivo; Chemistry; Fluorescent protein; Biophysics; Biology; Green fluorescent protein; Mathematics; Physics; Artificial intelligence; Statistics; Biochemistry; Genetics","score_opus":0.020400886872871348,"score_gpt":0.3045739280081658,"score_spread":0.28417304113529446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2127006594","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":[0.90624464,0.000082070444,0.09282582,0.00049873505,0.0001042003,0.000089020796,0.000016535043,0.000006591558,0.0001323981],"genre_scores_gemma":[0.96877146,0.000014851174,0.02958221,0.000101165766,0.0012957547,0.0000026142843,0.000053541513,0.000014561901,0.00016383914],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988279,0.00013153687,0.00025232666,0.00034117207,0.00020853848,0.00023855398],"domain_scores_gemma":[0.9992739,0.0000113590895,0.00007824268,0.00047068603,0.000064161,0.000101638165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037428204,0.00011876506,0.000152755,0.00007615985,0.00006267922,0.0000505617,0.000438712,0.000078610115,0.00002222996],"category_scores_gemma":[0.000038811573,0.000107396714,0.000078880905,0.00027907625,0.000025233612,0.0000076816395,0.000193825,0.00011327604,0.000020622238],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003329487,0.00006832823,0.00103866,0.0000019458137,0.000018511748,0.000008021079,0.0000052668674,0.0020168645,0.986491,0.000083375584,0.0062327255,0.004001978],"study_design_scores_gemma":[0.0005365238,0.00017144253,0.03148966,0.000024609479,0.00005874589,0.00007447209,0.000026447364,0.021306949,0.916513,0.0003176446,0.02911844,0.00036203233],"about_ca_topic_score_codex":0.00004535683,"about_ca_topic_score_gemma":0.000052384665,"teacher_disagreement_score":0.06997799,"about_ca_system_score_codex":0.000021931313,"about_ca_system_score_gemma":0.000055321943,"threshold_uncertainty_score":0.4379511},"labels":[],"label_agreement":null},{"id":"W2127187697","doi":"10.1515/jib-2006-23","title":"Noise in Genetic Toggle Switch Models","year":2006,"lang":"en","type":"article","venue":"Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"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 Calgary","funders":"","keywords":"Computer science; Noise (video); Simple (philosophy); Exponential growth; Genetic algorithm; Stochastic modelling; Translation (biology); Genetic network; Control theory (sociology); Biological system; Simulation; Mathematics; Artificial intelligence; Statistics; Machine learning; Biology","score_opus":0.008865228370200989,"score_gpt":0.24060306308139973,"score_spread":0.23173783471119874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2127187697","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":[0.71565926,0.0070790322,0.23051916,0.00037834392,0.0011505123,0.0013857952,0.00012546028,0.00007962793,0.043622803],"genre_scores_gemma":[0.8265981,0.0011048416,0.16970186,0.0009928304,0.0006501079,0.00004437856,0.00039695224,0.00007986195,0.00043106536],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99321777,0.00009156504,0.004328952,0.00022671335,0.0011795752,0.0009554202],"domain_scores_gemma":[0.99467444,0.000088733745,0.002760382,0.0007685325,0.0013371636,0.0003707322],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0011345042,0.00086520397,0.0011290936,0.0010152159,0.00016724739,0.00025223717,0.0011577235,0.0005249761,0.000053597516],"category_scores_gemma":[0.00022296107,0.0006340529,0.00058687857,0.0013593234,0.00034397768,0.0005956506,0.00033059545,0.0006852763,0.000086231616],"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":[0.0038420437,0.002618941,0.04407591,0.0027708372,0.008777632,0.00026620243,0.060199834,0.46004573,0.02806553,0.009684961,0.22153018,0.1581222],"study_design_scores_gemma":[0.016286148,0.0053004143,0.020434849,0.0016096471,0.0017756728,0.0029407025,0.035725996,0.58657,0.08030234,0.0034302121,0.23982003,0.0058039734],"about_ca_topic_score_codex":0.0000664661,"about_ca_topic_score_gemma":0.00017095021,"teacher_disagreement_score":0.15231822,"about_ca_system_score_codex":0.00019811727,"about_ca_system_score_gemma":0.0008152439,"threshold_uncertainty_score":0.9996111},"labels":[],"label_agreement":null},{"id":"W2127314261","doi":"10.1186/1471-2105-13-318","title":"On the contributions of topological features to transcriptional regulatory network robustness","year":2012,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research; Fonds Québécois de la Recherche sur la Nature et les Technologies; Compute Canada; Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Robustness (evolution); Gene regulatory network; Computational biology; DNA microarray; Topology (electrical circuits); Computer science; Biology; Systems biology; Gene; Genetics; Gene expression; Mathematics; Combinatorics","score_opus":0.0145162027474679,"score_gpt":0.24526934500809067,"score_spread":0.23075314226062277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2127314261","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":[0.84380436,0.001002448,0.15273446,0.00045865963,0.0003169811,0.00035425244,0.00006181155,0.00001801208,0.0012490202],"genre_scores_gemma":[0.9865897,0.000016351234,0.011986449,0.0006077554,0.00041978838,0.000021701355,0.00008811628,0.000008637912,0.00026147597],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9990127,0.00007402497,0.00029355055,0.000089970585,0.00020337131,0.0003263647],"domain_scores_gemma":[0.99921376,0.00005554355,0.00010402649,0.00040568638,0.00009865726,0.00012231276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004766456,0.0001350311,0.00015993239,0.00003132702,0.0001388506,0.0000117619975,0.00021635629,0.00016168132,0.00005675756],"category_scores_gemma":[0.00011552885,0.00008943795,0.00017336062,0.00018298786,0.00011599277,0.0000055191313,0.00006135471,0.00008699689,0.00001444224],"study_design_candidate":"simulation_or_modeling","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":[0.00027432558,0.00027776006,0.012558034,0.000075283344,0.00038822542,2.3064341e-7,0.0003144593,0.64866215,0.014760057,0.17618968,0.14568907,0.00081072276],"study_design_scores_gemma":[0.002970143,0.0017243003,0.6430773,0.00022595726,0.0008732675,0.00013636984,0.0022489794,0.059787378,0.15454037,0.002624559,0.12938923,0.0024021512],"about_ca_topic_score_codex":0.0000010594774,"about_ca_topic_score_gemma":0.0000079840665,"teacher_disagreement_score":0.6305193,"about_ca_system_score_codex":0.000017967714,"about_ca_system_score_gemma":0.00004986085,"threshold_uncertainty_score":0.36471736},"labels":[],"label_agreement":null},{"id":"W2127403997","doi":"10.1242/dev.035139","title":"Non-genetic heterogeneity of cells in development: more than just noise","year":2009,"lang":"en","type":"review","venue":"Development","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":526,"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 Calgary","funders":"Air Force Office of Scientific Research; U.S. Air Force; National Institutes of Health","keywords":"Biology; Genetic heterogeneity; Computational biology; Evolutionary biology; Cell fate determination; Genetics; Gene; Phenotype; Transcription factor","score_opus":0.023285349953512197,"score_gpt":0.2833089284356818,"score_spread":0.2600235784821696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2127403997","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.054192495,0.9447034,0.000105663516,0.0000031714885,0.00013613023,0.000662247,0.000011065735,0.000010113311,0.0001757013],"genre_scores_gemma":[0.0068372022,0.98259467,0.008949764,0.000036038986,0.00011673744,0.00013853889,0.000724474,0.000085719235,0.00051685626],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9967137,0.0001021503,0.0013753152,0.000891577,0.00036112053,0.00055613474],"domain_scores_gemma":[0.9984293,0.000008983369,0.00054177584,0.00075779215,0.00009154516,0.00017061824],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00033008904,0.0006954394,0.0015358359,0.00033750085,0.00006995872,0.000018441438,0.00065188,0.0005800342,0.00001550304],"category_scores_gemma":[0.000009093369,0.00065476325,0.00042964506,0.00048958446,0.0000642078,0.00000235288,0.0003189072,0.00018882783,0.000048558362],"study_design_candidate":"design_other","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":[0.000011814912,0.0002182584,0.0006539504,0.0039814827,0.0006897639,0.00002728792,0.00025286202,0.0002495014,0.000811399,4.1183196e-7,0.0004601182,0.9926432],"study_design_scores_gemma":[0.00024829715,0.00003438828,0.004463924,0.0020273747,0.00022721622,0.000014532718,0.000016033757,0.0000043779855,0.024467716,6.6918597e-7,0.9677195,0.00077597145],"about_ca_topic_score_codex":0.000004786157,"about_ca_topic_score_gemma":0.00013368485,"teacher_disagreement_score":0.9918672,"about_ca_system_score_codex":0.00017141225,"about_ca_system_score_gemma":0.001397713,"threshold_uncertainty_score":0.99959034},"labels":[],"label_agreement":null},{"id":"W2128341708","doi":"","title":"Comparative Analysis of Prostate Cancer Gene Regulatory Networks via Hub Type Variation.","year":2015,"lang":"en","type":"article","venue":"PubMed","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Gene regulatory network; Prostate cancer; Computational biology; Disease; Biology; Transcription factor; Gene; Cancer; Systems biology; Regulation of gene expression; Biological network; Computer science; Genetics; Gene expression; Medicine; Internal medicine","score_opus":0.020884009317899275,"score_gpt":0.2473155318081446,"score_spread":0.22643152249024534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128341708","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":[0.99028873,0.0053008366,0.0034176128,0.00004739594,0.00020374525,0.0003300664,0.000016644644,0.000012988922,0.00038196557],"genre_scores_gemma":[0.9979535,0.00014333932,0.00025099222,0.000072810886,0.0002252811,0.00024799546,0.00024000827,0.0000133565245,0.0008527422],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9987555,0.00011680908,0.0002961347,0.00033878582,0.00020622945,0.00028654287],"domain_scores_gemma":[0.9987109,0.000008034873,0.00023677759,0.00045994582,0.0004067377,0.00017764716],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039600462,0.00015085441,0.00037775838,0.000109881934,0.000036684844,0.000012785923,0.00016818535,0.00012468583,0.000013773713],"category_scores_gemma":[0.000022006496,0.00014512222,0.00016525315,0.001037989,0.00007736712,0.000004836425,0.000081660524,0.000054221808,0.0000015734648],"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":[0.0003041041,0.000114967006,0.087721445,0.0000072125963,0.008026089,0.0000016106573,0.00029694915,0.8722685,0.013146812,0.000032684748,0.005483455,0.012596201],"study_design_scores_gemma":[0.00046952718,0.000045795772,0.9377838,0.0000018609114,0.0020618432,0.0000010868426,0.000033928554,0.027703706,0.028474417,0.000036155354,0.0031147616,0.00027315514],"about_ca_topic_score_codex":0.00006394867,"about_ca_topic_score_gemma":0.00016818293,"teacher_disagreement_score":0.8500623,"about_ca_system_score_codex":0.00004681335,"about_ca_system_score_gemma":0.00007324857,"threshold_uncertainty_score":0.5917912},"labels":[],"label_agreement":null},{"id":"W2130416225","doi":"10.1155/2009/484601","title":"Using a State-Space Model and Location Analysis to Infer Time-Delayed Regulatory Networks","year":2009,"lang":"en","type":"article","venue":"EURASIP Journal on Bioinformatics and Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Plant Biotechnology Institute; University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Gene regulatory network; Computer science; A priori and a posteriori; Set (abstract data type); Computational biology; Regulation of gene expression; Data mining; Regulatory sequence; Biological network; Gene; Gene expression; Biology; Genetics","score_opus":0.014709907370647356,"score_gpt":0.26049030062690026,"score_spread":0.2457803932562529,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2130416225","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":[0.80200744,0.0014314216,0.19607407,0.00012068326,0.00007633053,0.00016085981,0.000008846956,0.000009655831,0.00011068106],"genre_scores_gemma":[0.9959861,0.0003859294,0.0027354383,0.00046420124,0.00017229894,0.0000021915796,0.000049274764,0.0000138573705,0.0001906906],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99845654,0.00014323728,0.00065565895,0.00024780797,0.00014340963,0.00035333575],"domain_scores_gemma":[0.99869347,0.000018154755,0.00038398767,0.00032669268,0.00027575018,0.0003019723],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074717053,0.00025693126,0.00045152186,0.00037412936,0.00022083802,0.00013232701,0.00013852524,0.00022708066,0.0000022132942],"category_scores_gemma":[0.000043985274,0.00020931098,0.000109576824,0.00051728176,0.00006030739,0.000016356958,0.000060505285,0.0001610201,0.0000038030732],"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":[0.00011393823,0.000021466367,0.0019465991,0.0000097166585,0.0006978396,0.0000017517333,0.00013501305,0.9795769,0.014385287,0.00019166883,0.00065331924,0.002266533],"study_design_scores_gemma":[0.0003199796,0.00053772086,0.0036142368,0.000024241832,0.00026733597,0.000111345966,0.000066723274,0.99387443,0.00017551395,0.00006213284,0.000670116,0.00027620536],"about_ca_topic_score_codex":0.000006142757,"about_ca_topic_score_gemma":0.00000653675,"teacher_disagreement_score":0.19397867,"about_ca_system_score_codex":0.00003958095,"about_ca_system_score_gemma":0.00007054334,"threshold_uncertainty_score":0.8535454},"labels":[],"label_agreement":null},{"id":"W2131250960","doi":"10.1371/journal.pone.0002922","title":"Noise-Driven Stem Cell and Progenitor Population Dynamics","year":2008,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":102,"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 Calgary","funders":"Air Force Office of Scientific Research; National Institutes of Health; National Cancer Institute; Bundesministerium für Bildung und Forschung; Deutsche Forschungsgemeinschaft; Harvard University","keywords":"Attractor; Progenitor; Population; Progenitor cell; Cellular differentiation; Stem cell; Biology; Physics; Biological system; Statistical physics; Cell biology; Genetics; Mathematics","score_opus":0.01561356596805339,"score_gpt":0.1907041052280743,"score_spread":0.1750905392600209,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131250960","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":[0.9989271,0.00059099356,0.00010965708,0.000035118122,0.000013587995,0.00013044874,0.0000071218833,0.000014719105,0.00017126322],"genre_scores_gemma":[0.996418,0.00021450322,0.0016058082,0.000025637824,0.00018444796,0.000012551358,0.00015634697,0.000020175497,0.0013625459],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993511,0.00003063258,0.000121893354,0.0002290983,0.000131584,0.00013571409],"domain_scores_gemma":[0.9995951,0.0000029053485,0.00005779644,0.00022361687,0.000052498912,0.00006808401],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003285342,0.00009608606,0.00012790167,0.000028579178,0.00008399616,0.0000076126526,0.00006768389,0.00009647296,0.000005053342],"category_scores_gemma":[0.000003324612,0.00010084472,0.000044248736,0.0000668141,0.000032390417,0.000002312764,0.000054773587,0.000039912677,0.000008279734],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000252599,0.00034615633,0.48181006,0.0000497231,0.0002299765,0.000003793873,0.00003301517,0.00024704856,0.5165029,0.000009210521,0.00015357696,0.0005892533],"study_design_scores_gemma":[0.0009574273,0.00039488522,0.17451453,0.00003799019,0.0005465364,0.000023796028,0.00006045602,0.033157982,0.78924,0.000029606419,0.0003813878,0.0006553877],"about_ca_topic_score_codex":0.0000071555996,"about_ca_topic_score_gemma":0.000030240773,"teacher_disagreement_score":0.3072955,"about_ca_system_score_codex":0.000017714257,"about_ca_system_score_gemma":0.000015935299,"threshold_uncertainty_score":0.41123286},"labels":[],"label_agreement":null},{"id":"W2131550814","doi":"10.1002/widm.1068","title":"Reverse engineering of gene regulatory networks from biological data","year":2012,"lang":"en","type":"article","venue":"Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"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 Saskatchewan","funders":"","keywords":"Biological network; Gene regulatory network; Biological data; Reverse engineering; Computer science; Inference; Network topology; Data mining; Data science; Machine learning; Artificial intelligence; Computational biology; Biology; Bioinformatics; Gene","score_opus":0.06458627543732233,"score_gpt":0.3164829617760331,"score_spread":0.25189668633871076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131550814","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":[0.6528322,0.33557752,0.0097898645,0.000021474534,0.0005796324,0.00021716909,0.0008102724,0.000016347773,0.0001555263],"genre_scores_gemma":[0.95634377,0.019583223,0.0069478774,0.00003623885,0.0019198516,0.00001688978,0.01490612,0.00004367698,0.00020237596],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99775904,0.00021502402,0.00066352566,0.00086472475,0.0000951587,0.00040252807],"domain_scores_gemma":[0.99625534,0.00006403259,0.0002716327,0.0031970784,0.000032934287,0.0001790049],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001230123,0.00033783852,0.00064055703,0.000062869476,0.000099558245,0.00003568957,0.0012599265,0.0002141596,0.000020890284],"category_scores_gemma":[0.00016031117,0.00027693997,0.00013344068,0.00017863639,0.00016338636,0.000105847954,0.0066451123,0.00012963281,0.000009075033],"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":[0.00048259678,0.0011690714,0.11559342,0.00058710383,0.0020633035,0.000015683296,0.001648342,0.00041896172,0.20967376,0.000051821135,0.39623645,0.27205947],"study_design_scores_gemma":[0.0031952707,0.0011346461,0.09475028,0.0077696773,0.0036824932,0.00031583526,0.0031473297,0.117472194,0.01693245,0.000040128474,0.7461799,0.005379826],"about_ca_topic_score_codex":0.000004364824,"about_ca_topic_score_gemma":0.000019683424,"teacher_disagreement_score":0.3499434,"about_ca_system_score_codex":0.000014359192,"about_ca_system_score_gemma":0.000038442857,"threshold_uncertainty_score":0.9999683},"labels":[],"label_agreement":null},{"id":"W2131869007","doi":"10.1016/j.febslet.2005.02.013","title":"Synthetic modular systems – reverse engineering of signal transduction","year":2005,"lang":"en","type":"review","venue":"FEBS Letters","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital","funders":"","keywords":"Synthetic biology; Modular design; Reverse engineering; Computational biology; Systems biology; Signal transduction; Computer science; Protein engineering; Transduction (biophysics); Proteomics; Biological network; Biology; Gene; Cell biology; Genetics; Biochemistry","score_opus":0.01218252295687504,"score_gpt":0.23032005186095056,"score_spread":0.2181375289040755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131869007","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011277023,0.9947621,0.0035163285,0.000027781345,0.00021890245,0.00029893962,0.000018479514,0.000014926332,0.000014794929],"genre_scores_gemma":[0.003180353,0.9949509,0.00027185504,0.000032532927,0.001060446,0.000049406022,0.00022920311,0.000079832345,0.00014545296],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984828,0.00011888382,0.0005034455,0.0004571416,0.00018413647,0.00025356477],"domain_scores_gemma":[0.9990705,0.000010357618,0.0002616763,0.0005579899,0.000031077583,0.00006836117],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00020023777,0.00034848464,0.00089068874,0.0001549614,0.000026389358,0.000013988692,0.00025063107,0.0003090365,0.00002598039],"category_scores_gemma":[0.000009101673,0.00033775502,0.000727911,0.00018451439,0.000041180825,0.0000025959034,0.000033353324,0.00014683315,0.000012778578],"study_design_candidate":"not_applicable","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":[0.000020638498,0.00010686106,0.0000053614845,0.025783125,0.004056684,0.000031212563,0.00004006783,0.29743776,0.1299087,0.000027957509,0.010945374,0.53163624],"study_design_scores_gemma":[0.00007101232,0.000024536716,8.258109e-7,0.0016037145,0.001063978,0.00005494724,0.000003139424,0.00042673672,0.00046503477,6.9296085e-8,0.99596804,0.00031794072],"about_ca_topic_score_codex":0.0000071686227,"about_ca_topic_score_gemma":7.494322e-7,"teacher_disagreement_score":0.98502266,"about_ca_system_score_codex":0.00005194712,"about_ca_system_score_gemma":0.000047158905,"threshold_uncertainty_score":0.99990743},"labels":[],"label_agreement":null},{"id":"W2132449013","doi":"10.1109/ccece.2011.6030522","title":"Control theoretic modeling of a genetic switch","year":2011,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Psychological repression; Control (management); Gene regulatory network; Gene; Artificial intelligence; Biology; Genetics; Gene expression","score_opus":0.010548436542006115,"score_gpt":0.2039282067360697,"score_spread":0.1933797701940636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2132449013","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":[0.8293303,0.0004442681,0.1647279,0.00000797134,0.000024825735,0.00007402372,0.0000013123181,0.0000071626173,0.0053822123],"genre_scores_gemma":[0.9957948,0.000049445425,0.0038214384,0.000074265095,0.000057778285,0.0000074719023,0.0000041194876,0.0000154667,0.00017521976],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993048,0.000039128536,0.0002093321,0.00020499284,0.000082770865,0.00015897454],"domain_scores_gemma":[0.9994322,0.0000028243944,0.0000542249,0.0003734722,0.00008320152,0.000054058477],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011037945,0.00009874067,0.00014181275,0.000033093376,0.00002133138,0.000002718335,0.00015656077,0.00008206244,0.00016737722],"category_scores_gemma":[0.000012818131,0.00008401364,0.00012664782,0.00006829812,0.000052162653,7.427196e-7,0.000040251718,0.00002708082,0.000008255373],"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":[0.00039525714,0.00030717795,0.08954093,0.000065119,0.0011178573,0.0000074869054,0.0002833925,0.08589213,0.8109955,0.0070265154,0.0004926088,0.0038759883],"study_design_scores_gemma":[0.0022151142,0.0006796512,0.009860507,0.000020947426,0.0005717033,0.00003258521,0.00023143154,0.62407076,0.35417685,0.0069637364,0.0004380398,0.00073867344],"about_ca_topic_score_codex":0.00003197063,"about_ca_topic_score_gemma":0.000021547612,"teacher_disagreement_score":0.5381786,"about_ca_system_score_codex":0.0000029234245,"about_ca_system_score_gemma":0.000029051946,"threshold_uncertainty_score":0.3425977},"labels":[],"label_agreement":null},{"id":"W2134233117","doi":"10.1063/1.2397073","title":"A graph-theoretic method for detecting potential Turing bifurcations","year":2006,"lang":"en","type":"article","venue":"The Journal of Chemical Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":30,"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 Lethbridge","funders":"","keywords":"Turing; Bipartite graph; Graph; Mathematics; Computer science; Discrete mathematics","score_opus":0.005922680633313394,"score_gpt":0.24505198032454775,"score_spread":0.23912929969123436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134233117","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":[0.6028555,0.00035932712,0.39651123,0.00012254673,0.00004342787,0.000047790145,0.0000017615214,0.000002289946,0.00005614471],"genre_scores_gemma":[0.9860315,0.000015103673,0.012342278,0.000044461878,0.0015040068,0.000002375177,0.000007711753,0.00001605075,0.0000365216],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99931794,0.00006318994,0.0002552947,0.00008674598,0.00012522023,0.00015162295],"domain_scores_gemma":[0.9993055,0.000052471343,0.00025513297,0.00018268696,0.00016784163,0.00003638923],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039298978,0.000094048686,0.00013990831,0.000020025891,0.000071862094,0.000012889499,0.00021773051,0.000058362813,0.0000022458107],"category_scores_gemma":[0.0000402657,0.0000678782,0.0002851016,0.00012186686,0.00006240515,0.000003300592,0.00004155356,0.00010565511,5.191776e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055527355,0.000030732852,0.00001659255,0.000007415128,0.000095479445,2.2110977e-7,0.00001131687,0.015010459,0.98253036,0.00018368718,0.00055032043,0.0015079075],"study_design_scores_gemma":[0.00028889868,0.00004799385,0.000026326838,0.000007888384,0.0002939654,0.00004239782,0.000021426644,0.0025296593,0.96593064,0.030356571,0.00036820714,0.000086002925],"about_ca_topic_score_codex":0.0000028198176,"about_ca_topic_score_gemma":6.9026254e-7,"teacher_disagreement_score":0.38416895,"about_ca_system_score_codex":0.000011815798,"about_ca_system_score_gemma":0.00003063937,"threshold_uncertainty_score":0.2767993},"labels":[],"label_agreement":null},{"id":"W2136340808","doi":"10.1073/pnas.98.4.1364","title":"Dynamic regulation of the tryptophan operon: A modeling study and comparison with experimental data","year":2001,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":128,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"trp operon; Operon; Tryptophan; Escherichia coli; Psychological repression; Biological system; Enzyme; Mutant; lac operon; Chemistry; Physics; Biophysics; Biology; Biochemistry; Amino acid; Gene","score_opus":0.05037229116484444,"score_gpt":0.32969600825806283,"score_spread":0.2793237170932184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136340808","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":[0.9990981,0.00034616943,0.000010096592,0.00025742076,0.000004327726,0.00014339635,0.0000031716875,0.0000011574116,0.00013613082],"genre_scores_gemma":[0.9993054,0.000012719127,0.0006029163,0.000019454566,0.00001909859,0.0000029449825,5.4805867e-7,0.000002675586,0.000034206725],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99902296,0.000008757668,0.00019336402,0.00021786691,0.0004909328,0.00006612886],"domain_scores_gemma":[0.9996209,0.000005396057,0.0002320445,0.000026797556,0.00010144543,0.000013420793],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004924135,0.000060838116,0.00010098611,0.000034276054,0.00011720258,0.000009426632,0.00063832744,0.00003630934,0.0000015680299],"category_scores_gemma":[0.000032884145,0.000034132372,0.000024244331,0.00029559713,0.00033739986,0.000021842205,0.00031959976,0.000040827606,2.3930228e-8],"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":[0.00003791615,0.000098125296,0.06017934,0.000008526368,0.00004233816,8.5261187e-10,0.00015268392,0.014710601,0.92449,0.000106087384,0.00004040508,0.00013401685],"study_design_scores_gemma":[0.0003990687,0.00019508395,0.112611614,0.00004387473,0.00005324548,0.00000832269,0.001916408,0.52451295,0.35974333,0.00039397855,0.000028640778,0.00009349384],"about_ca_topic_score_codex":0.000004607923,"about_ca_topic_score_gemma":0.0000011933784,"teacher_disagreement_score":0.5647466,"about_ca_system_score_codex":0.0000076031947,"about_ca_system_score_gemma":0.0000185108,"threshold_uncertainty_score":0.13918778},"labels":[],"label_agreement":null},{"id":"W2136415035","doi":"10.1109/iembs.2006.259927","title":"A Neural Network Based Approach for Inference and Verification of Transcriptional Regulatory Interactions","year":2006,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Queen's University","funders":"","keywords":"Computer science; Inference; Artificial neural network; Gene regulatory network; Artificial intelligence; Computational biology; Machine learning; Gene; Biology; Gene expression; Genetics","score_opus":0.01303722505497405,"score_gpt":0.23888487137802386,"score_spread":0.22584764632304982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136415035","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":[0.6299895,0.0003861786,0.36880624,0.00005025281,0.000035332963,0.0001464379,0.000009570492,0.000007873496,0.0005686185],"genre_scores_gemma":[0.9803457,0.0000044790704,0.018599741,0.000041853902,0.0001775027,0.00003812344,0.0004023267,0.000008021226,0.00038223332],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99945825,0.000026295413,0.00016202856,0.00019347199,0.00005860882,0.00010136618],"domain_scores_gemma":[0.9996558,0.000012207586,0.00006145973,0.00016824213,0.00007782616,0.000024486935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009245164,0.000075000935,0.00009035289,0.00002700415,0.000050173294,0.000007721568,0.0000528977,0.000053944004,0.000010244922],"category_scores_gemma":[0.000006374473,0.0000733279,0.000081332175,0.00007289138,0.000057846788,0.000003048086,0.000008719551,0.000023686816,1.194735e-7],"study_design_candidate":"simulation_or_modeling","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":[0.00011031522,0.000104468745,0.016039291,0.00003690782,0.000059301015,3.679717e-8,0.000004990572,0.31233814,0.6639921,0.0037509631,0.0023100716,0.0012533878],"study_design_scores_gemma":[0.0012677277,0.00022266537,0.19643058,0.000011405154,0.00019306761,0.000004798809,0.00004444588,0.6882707,0.096550554,0.00067213905,0.015938908,0.00039303163],"about_ca_topic_score_codex":0.000012045673,"about_ca_topic_score_gemma":0.000033256925,"teacher_disagreement_score":0.5674416,"about_ca_system_score_codex":0.0000051836505,"about_ca_system_score_gemma":0.000027769931,"threshold_uncertainty_score":0.2990225},"labels":[],"label_agreement":null},{"id":"W2136794800","doi":"10.1002/bit.22969","title":"An active intracellular device to prevent lethal disease outcomes in virus‐infected bacterial cells","year":2010,"lang":"en","type":"article","venue":"Biotechnology and Bioengineering","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"College of Family Physicians of Canada; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Lytic cycle; Intracellular; Disease; Bacteriophage; Systems biology; Escherichia coli; Model system; Virus; Bacteriophage MS2; Virology; Biology; Computational biology; Computer science; Cell biology; Medicine; Genetics","score_opus":0.0035479972759687806,"score_gpt":0.21265718164969097,"score_spread":0.2091091843737222,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136794800","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":[0.99805194,0.000109955865,0.00101095,0.000305955,0.00023059934,0.00018859902,0.000018387675,0.000081663515,0.0000019682652],"genre_scores_gemma":[0.99832726,0.000042543958,0.0013661232,0.00003495464,0.00012164526,0.000023313185,0.000043045162,0.000026729975,0.000014366621],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990691,0.00002538597,0.00016511895,0.00040680025,0.000056202603,0.00027741576],"domain_scores_gemma":[0.99938536,0.00000646402,0.00003490903,0.00039643876,0.000020243711,0.00015656059],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010482818,0.00019352499,0.00018943705,0.0001692861,0.000034680466,0.000016177542,0.000184427,0.00042265473,0.000010273411],"category_scores_gemma":[0.00003364071,0.00018770747,0.00005109037,0.00018050143,0.0000659362,0.000006283715,0.000121158046,0.0002195259,0.0000034380512],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004795845,0.000100022065,0.0025342694,0.0000083813875,0.000056450477,0.000010793965,0.000013040838,0.0006268333,0.99449,0.000037446538,0.000007689038,0.0020670833],"study_design_scores_gemma":[0.0001998587,0.000113853566,0.02093644,0.0000056010454,0.000032015698,0.00000487402,0.0000124817925,0.0008572647,0.97471386,0.000008314571,0.0028843954,0.00023101471],"about_ca_topic_score_codex":0.000015732563,"about_ca_topic_score_gemma":0.00028881457,"teacher_disagreement_score":0.019776147,"about_ca_system_score_codex":0.00001102096,"about_ca_system_score_gemma":0.000025602918,"threshold_uncertainty_score":0.76544887},"labels":[],"label_agreement":null},{"id":"W2136879715","doi":"10.1111/evo.12732","title":"Robustness to noise in gene expression evolves despite epistatic constraints in a model of gene networks","year":2015,"lang":"en","type":"article","venue":"Evolution","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Epistasis; Robustness (evolution); Biology; Counterintuitive; Fitness landscape; Gene regulatory network; Gene; Genetics; Computational biology; Phenotype; Gene expression; Evolutionary biology; Population; Physics","score_opus":0.01662606165531739,"score_gpt":0.24098823867031938,"score_spread":0.224362177015002,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136879715","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":[0.62794966,0.00072952994,0.3711065,0.000017620354,0.000035362522,0.00012737235,0.000004273629,0.0000038563176,0.000025835963],"genre_scores_gemma":[0.9796777,0.000024100264,0.020039095,0.000021845128,0.00006800934,0.000031460404,0.000068334535,0.000016366484,0.000053087024],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988003,0.00011734848,0.00033938885,0.0003259635,0.00015602661,0.0002609779],"domain_scores_gemma":[0.9993315,0.000006638077,0.000101187616,0.0003215723,0.000112144044,0.00012699982],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003950835,0.00013928658,0.00021447218,0.00015741737,0.000018259076,0.0000061099777,0.00014196268,0.00015643191,0.0000035065789],"category_scores_gemma":[0.0000724455,0.00014713965,0.000060602055,0.0003170269,0.00006267737,0.0000069129946,0.0000759419,0.00006775392,0.0000014831393],"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":[0.00006768317,0.00005606961,0.009216035,0.0000055109226,0.0000073894294,0.0000013691787,0.00005115489,0.6612328,0.32902572,0.0000068889644,0.00013318009,0.00019615443],"study_design_scores_gemma":[0.00075001747,0.000092418806,0.007268595,0.000050945262,0.000016341106,0.0000034566424,0.00008593213,0.9058494,0.0855923,0.00009785498,0.0000075637477,0.00018519198],"about_ca_topic_score_codex":0.00003905276,"about_ca_topic_score_gemma":0.0002432474,"teacher_disagreement_score":0.35172808,"about_ca_system_score_codex":0.00011559329,"about_ca_system_score_gemma":0.00014134904,"threshold_uncertainty_score":0.6000181},"labels":[],"label_agreement":null},{"id":"W2137063199","doi":"10.1016/j.biosystems.2004.12.003","title":"UML as a cell and biochemistry modeling language","year":2005,"lang":"en","type":"article","venue":"Biosystems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":49,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; TRIUMF","funders":"","keywords":"Unified Modeling Language; Computer science; Computational biology; Cell; Programming language; Natural language processing; Chemistry; Biology; Biochemistry; Software","score_opus":0.004650990759434293,"score_gpt":0.21631181214013032,"score_spread":0.21166082138069603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137063199","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":[0.987267,0.010169476,0.0003859945,0.00007065038,0.000042326585,0.00007525907,0.0000058493865,0.000018984021,0.001964419],"genre_scores_gemma":[0.9960703,0.000106030006,0.000365237,0.00009274631,0.00071617734,0.0000082092565,0.0000451421,0.000021034111,0.002575082],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991907,0.000024901581,0.0001673401,0.00032380325,0.00010066743,0.00019262],"domain_scores_gemma":[0.9994678,0.000002139703,0.00005207997,0.00034322194,0.00003278425,0.000101992046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012279788,0.0001359885,0.0001300722,0.000027551081,0.000054338518,0.000027116628,0.00011172217,0.00014701624,0.000013243196],"category_scores_gemma":[0.000010511059,0.00013114631,0.00007418642,0.00006584073,0.00002132967,0.000002058913,0.00007441229,0.00004308468,0.000034478468],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009717892,0.000020235935,0.00063791015,0.000039416518,0.00003884769,0.000002249111,0.000060107537,0.0011495508,0.9959203,0.000003820252,0.0006856971,0.001432124],"study_design_scores_gemma":[0.0003761027,0.000046409918,0.000021506763,0.000020284162,0.000043892906,0.00004848739,0.00037535108,0.033683203,0.9508663,0.0000027757198,0.014233707,0.00028198925],"about_ca_topic_score_codex":0.000037994945,"about_ca_topic_score_gemma":0.00002384951,"teacher_disagreement_score":0.045054033,"about_ca_system_score_codex":0.000014512288,"about_ca_system_score_gemma":0.00003443423,"threshold_uncertainty_score":0.53479916},"labels":[],"label_agreement":null},{"id":"W2137112190","doi":"10.1093/bioinformatics/btm004","title":"SGN Sim, a Stochastic Genetic Networks Simulator","year":2007,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":65,"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 Calgary","funders":"","keywords":"Computer science; Set (abstract data type); Gene regulatory network; Stochastic simulation; Master regulator; Translation (biology); Stochastic modelling; Stochastic process; Simulation; Algorithm; Theoretical computer science; Gene; Transcription factor; Genetics; Mathematics; Gene expression; Programming language; Biology; Messenger RNA","score_opus":0.0066315848812003135,"score_gpt":0.2278340997158765,"score_spread":0.2212025148346762,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137112190","genre_codex":"methods","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":[0.38966602,0.00084336085,0.6084004,0.000014074788,0.00021261591,0.00019867894,0.000004499202,0.000036893263,0.00062342035],"genre_scores_gemma":[0.9880878,0.0000336396,0.010461356,0.00033583594,0.0005806698,0.000005252143,0.000070727016,0.000035082026,0.00038963777],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99841315,0.000019891497,0.0005573303,0.00021501094,0.00024308564,0.000551528],"domain_scores_gemma":[0.99880445,0.000028632136,0.0001919764,0.00063184224,0.00011201545,0.00023106426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035765613,0.00024915548,0.00021677707,0.00009896496,0.00012335331,0.000041302985,0.00028605803,0.00024936875,0.00003085533],"category_scores_gemma":[0.00006571206,0.00023925136,0.00018228093,0.00027166406,0.000090683665,0.0000061100054,0.00014927449,0.000109017616,0.00006815102],"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":[0.000084847205,0.00008329745,0.0027139243,0.00003921,0.00025795272,0.0000072397984,0.000120781406,0.9693455,0.002382574,0.00005847092,0.0048222817,0.02008392],"study_design_scores_gemma":[0.00094185915,0.00035699288,0.008397883,0.000025437337,0.0001765771,0.0000577278,0.00023884034,0.96568817,0.0027139361,0.000043586948,0.020595737,0.0007632389],"about_ca_topic_score_codex":0.0000030253004,"about_ca_topic_score_gemma":0.000026107966,"teacher_disagreement_score":0.59842175,"about_ca_system_score_codex":0.000030357347,"about_ca_system_score_gemma":0.00006184615,"threshold_uncertainty_score":0.97563875},"labels":[],"label_agreement":null},{"id":"W2137804356","doi":"10.1007/s11538-006-9091-y","title":"Asymptotic Methods for Reaction-Diffusion Systems: Past and Present","year":2006,"lang":"en","type":"review","venue":"Bulletin of Mathematical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Scope (computer science); Diffusion; Reaction–diffusion system; Key (lock); Computer science; Statistical physics; Data science; Operations research; Calculus (dental); Mathematics; Physics; Mathematical analysis; Thermodynamics; Medicine","score_opus":0.02831357122702656,"score_gpt":0.3502726387147658,"score_spread":0.3219590674877393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137804356","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000041441162,0.9730466,0.025190096,0.00005854058,0.00011542201,0.00094052625,0.0000382033,0.000011556527,0.00055764226],"genre_scores_gemma":[0.00003194835,0.968501,0.028058695,0.000012005306,0.0006380199,0.00035538463,0.0005342702,0.00006515382,0.0018035435],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975715,0.0005835397,0.00089496555,0.0005820462,0.000069922375,0.00029799587],"domain_scores_gemma":[0.9981923,0.00051768095,0.00055208063,0.00054530974,0.00010542939,0.00008720913],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008290101,0.00037673552,0.0016699284,0.00009686801,0.000053525062,0.000012725989,0.00023889162,0.0007744805,0.00003058381],"category_scores_gemma":[0.00025057074,0.0002798621,0.00053373835,0.00006997673,0.0002053946,3.7397194e-7,0.00022114774,0.0001107714,0.000015980178],"study_design_candidate":"not_applicable","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":[0.00004817148,0.00043579264,0.0000097642205,0.052805208,0.001762997,0.0000014746169,0.000008844505,0.000012774424,0.0025938738,0.006620082,0.04203292,0.8936681],"study_design_scores_gemma":[0.0001652483,0.0001925732,9.4757706e-7,0.0009278725,0.000943994,0.000057742738,0.000005989389,0.000060887294,0.000049717208,0.00053774094,0.9968045,0.0002527818],"about_ca_topic_score_codex":0.000009007146,"about_ca_topic_score_gemma":4.1627015e-7,"teacher_disagreement_score":0.9547716,"about_ca_system_score_codex":0.000018674158,"about_ca_system_score_gemma":0.00004760941,"threshold_uncertainty_score":0.99996537},"labels":[],"label_agreement":null},{"id":"W2138031414","doi":"10.1016/j.tree.2012.04.008","title":"Physiological regulatory networks: ecological roles and evolutionary constraints","year":2012,"lang":"en","type":"article","venue":"Trends in Ecology & Evolution","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":221,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Hôpital Fleurimont","funders":"","keywords":"Ecological network; Ecology; Gene regulatory network; Evolutionary biology; Biology; Gene; Ecosystem; Genetics","score_opus":0.010891802689685075,"score_gpt":0.24466985009536643,"score_spread":0.23377804740568137,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138031414","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":[0.9949205,0.003798696,0.00034099267,0.000108600456,0.00024406744,0.00008501722,0.0000049255073,0.000029759172,0.00046742364],"genre_scores_gemma":[0.9981788,0.00016250285,0.0005073268,0.00011893731,0.0005554427,0.000045211753,0.00017237462,0.000014929975,0.00024451353],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981366,0.000342637,0.00032123175,0.00046039457,0.0000995975,0.00063955487],"domain_scores_gemma":[0.99936944,0.000031435586,0.00011650609,0.00028867,0.000039691036,0.0001542463],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044968555,0.00022575092,0.00029660048,0.00017083713,0.00013365864,0.000006034761,0.00013950258,0.00056727923,0.00019328669],"category_scores_gemma":[0.000058628317,0.0002135812,0.00011851871,0.00025654997,0.0006826888,0.000013319278,0.0001934486,0.00019051357,0.000013154931],"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":[0.000072561794,0.0003513783,0.96974117,0.0000034237871,0.000091234826,0.0000027332135,0.00001854563,0.009676836,0.009180841,0.0009997239,0.0052735927,0.0045879763],"study_design_scores_gemma":[0.0004831275,0.00020210072,0.99495953,0.0000036011565,0.00004426395,0.00005807137,0.000056892415,0.0028577426,0.00010415465,0.00029433944,0.00071244093,0.00022371522],"about_ca_topic_score_codex":0.0000034418922,"about_ca_topic_score_gemma":0.0001253383,"teacher_disagreement_score":0.0252184,"about_ca_system_score_codex":0.00012754825,"about_ca_system_score_gemma":0.000034100023,"threshold_uncertainty_score":0.87095886},"labels":[],"label_agreement":null},{"id":"W2138228997","doi":"10.1109/mwscas.2004.1354048","title":"High speed emulation of gene regulatory networks using FPGAs","year":2004,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Emulation; Field-programmable gate array; Computer science; Embedded system; Computer architecture","score_opus":0.010155744541913038,"score_gpt":0.22928929916016058,"score_spread":0.21913355461824754,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138228997","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":[0.91845,0.00054204976,0.08063305,0.000021541204,0.00010198494,0.000086046624,0.0000014987182,0.00001227781,0.0001515414],"genre_scores_gemma":[0.9865937,0.000029499812,0.012616104,0.000064870874,0.00038137354,8.240945e-7,0.0000867687,0.000024623492,0.0002022185],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99903667,0.000034856446,0.00028678216,0.00028641036,0.00014913143,0.00020616216],"domain_scores_gemma":[0.9992121,0.0000030271165,0.00014144518,0.00046633565,0.0001075705,0.00006955468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014445218,0.00014316283,0.00019427147,0.000057165893,0.000054425815,0.000008464703,0.00012488956,0.00017635452,0.000036998998],"category_scores_gemma":[0.000009610964,0.0001421299,0.00014894034,0.000187907,0.000068824935,0.0000033003612,0.00005509832,0.000043555927,0.0000025406894],"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":[0.000014122957,0.000018404091,0.0007485066,0.0000021270134,0.00005783432,6.1335993e-7,0.000004367785,0.5533944,0.4452836,0.00015825343,0.000038948227,0.00027886714],"study_design_scores_gemma":[0.00071396667,0.00008362668,0.0126854535,0.000012938906,0.00010976317,0.0000128889615,0.000022575985,0.022241753,0.96346635,0.00028718932,0.000123347,0.00024014093],"about_ca_topic_score_codex":0.00008664761,"about_ca_topic_score_gemma":0.000034995814,"teacher_disagreement_score":0.5311526,"about_ca_system_score_codex":0.00003187241,"about_ca_system_score_gemma":0.000057900626,"threshold_uncertainty_score":0.5795889},"labels":[],"label_agreement":null},{"id":"W2138288543","doi":"10.1109/aim.2008.4601795","title":"Robust stability of stochastic genetic regulatory networks with disturbance attenuation","year":2008,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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 Guelph","funders":"","keywords":"Linear matrix inequality; Stability (learning theory); Convex optimization; Mathematical optimization; Stability theory; Control theory (sociology); Computer science; Exponential stability; Regular polygon; Mathematics; Nonlinear system; Control (management); Artificial intelligence","score_opus":0.014106427737552742,"score_gpt":0.19508765303791464,"score_spread":0.1809812253003619,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138288543","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":[0.7461451,0.00082349184,0.2527096,0.000014765936,0.000029330098,0.00012768208,0.0000020477116,0.000010758695,0.00013720822],"genre_scores_gemma":[0.9961434,0.000035428093,0.0032487214,0.000035118515,0.0001517506,0.000015440915,0.000053394215,0.00002283388,0.00029392663],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9988381,0.00006574725,0.00026924946,0.00039872545,0.00020736425,0.00022079019],"domain_scores_gemma":[0.9989224,0.000011799497,0.0001465304,0.0006592381,0.00017856996,0.000081436214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012255146,0.00016583572,0.00021204409,0.000030050282,0.00008476105,0.000004115273,0.00015193856,0.000112787515,0.000043436492],"category_scores_gemma":[0.00001843378,0.00013911765,0.000096002026,0.00019710315,0.0002674215,0.0000030362714,0.0000549014,0.000058812082,0.0000019018399],"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":[0.00015020468,0.00010481672,0.13603498,0.000018149507,0.0001735151,0.0000026930834,0.000038184022,0.83630383,0.025624465,0.000022682902,0.00094433984,0.0005821231],"study_design_scores_gemma":[0.0011503136,0.0006091725,0.88960177,0.00002870378,0.00020511945,0.000082177714,0.000084948,0.06217138,0.045148518,0.000025680056,0.00022519368,0.0006670386],"about_ca_topic_score_codex":0.000015295904,"about_ca_topic_score_gemma":0.000083133746,"teacher_disagreement_score":0.7741325,"about_ca_system_score_codex":0.000019994122,"about_ca_system_score_gemma":0.000080817794,"threshold_uncertainty_score":0.5673053},"labels":[],"label_agreement":null},{"id":"W2138470019","doi":"10.1146/annurev.genet.39.073003.114751","title":"Systematic Mapping of Genetic Interaction Networks","year":2008,"lang":"en","type":"review","venue":"Annual Review of Genetics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":302,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research; Genome Canada","keywords":"Biology; Genetic screen; Schizosaccharomyces pombe; Model organism; Drosophila melanogaster; Caenorhabditis elegans; Genetics; Computational biology; Saccharomyces cerevisiae; Phenotype; Yeast; Schizosaccharomyces; Systems biology; Saccharomyces; Gene","score_opus":0.01838316429866416,"score_gpt":0.3028971268588111,"score_spread":0.28451396256014694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138470019","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000027171523,0.996712,0.0015433956,0.0000030075569,0.00023408725,0.0012962222,0.000046512683,0.000006862719,0.00013069194],"genre_scores_gemma":[0.0000949458,0.9978062,0.0010113186,0.0000634913,0.00034261326,0.00009870727,0.0003305745,0.00009249392,0.00015964116],"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","domain_scores_codex":[0.99545413,0.0006448391,0.0026310077,0.000561533,0.00037969113,0.0003287736],"domain_scores_gemma":[0.9953482,0.00007589946,0.0025982156,0.0013675347,0.0004947424,0.00011539476],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003974588,0.0005865848,0.0035422537,0.000184961,0.00004316734,0.000006032808,0.00067679764,0.00046192005,0.000018638697],"category_scores_gemma":[0.00020561274,0.00049842714,0.0017768656,0.00060888054,0.00013816495,0.000002911965,0.00028569807,0.00020888624,0.00001275114],"study_design_candidate":"systematic_review","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":[0.0000018805606,0.000050189083,0.000007151562,0.7710267,0.0012166998,0.0000039715137,0.000015170906,0.00025758095,0.000009309756,0.0000023126267,0.0032415567,0.22416753],"study_design_scores_gemma":[0.00005598535,0.00012822422,0.000004912114,0.35085136,0.0022845322,0.000169453,0.000018297087,0.000059547092,0.000022026106,9.2852366e-7,0.64604974,0.0003549939],"about_ca_topic_score_codex":0.0000030206918,"about_ca_topic_score_gemma":0.0000022426145,"teacher_disagreement_score":0.6428082,"about_ca_system_score_codex":0.000035981164,"about_ca_system_score_gemma":0.00027258968,"threshold_uncertainty_score":0.99974674},"labels":[],"label_agreement":null},{"id":"W2139900569","doi":"10.1016/j.ejps.2011.06.006","title":"Emergence of the silicon human and network targeting drugs","year":2011,"lang":"en","type":"article","venue":"European Journal of Pharmaceutical Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Biotechnology and Biological Sciences Research Council; AstraZeneca","keywords":"Computational biology; Homeostasis; Mechanism (biology); Drug development; Neuroscience; Drug discovery; Computer science; Biology; Drug; Bioinformatics; Cell biology; Pharmacology; Epistemology","score_opus":0.03948531263592515,"score_gpt":0.300671318594687,"score_spread":0.26118600595876185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139900569","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":[0.99168545,0.002627187,0.00016632609,0.000089479116,0.00016857343,0.000028990682,3.5238148e-7,0.0000013353231,0.0052322783],"genre_scores_gemma":[0.9985914,0.00022075362,0.0007339965,0.000108632055,0.00030105814,9.5144884e-8,1.381761e-7,0.0000055537585,0.000038368224],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987688,0.00039916084,0.00032234317,0.00013187423,0.00020181516,0.0001760054],"domain_scores_gemma":[0.9994604,0.0000100736515,0.00026348722,0.00009234362,0.00007232816,0.00010138203],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019911828,0.00007526193,0.0001079862,0.000020343725,0.00017916778,0.000010833755,0.0004422556,0.000013993205,0.00010387195],"category_scores_gemma":[0.00005003933,0.000046248304,0.0001043543,0.00019725575,0.0005328552,0.000006496189,0.0001830878,0.00009577876,0.0000010428059],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004062285,0.00006362364,0.08859429,0.000015082678,0.00011512039,0.0000082761135,0.00044350934,0.001182234,0.89422756,0.00034620208,0.0053222124,0.009641261],"study_design_scores_gemma":[0.0010619243,0.0012837662,0.14192173,0.00013748322,0.0003755153,0.00011683783,0.0013770899,0.0015557371,0.8146688,0.0006548839,0.036335047,0.0005112099],"about_ca_topic_score_codex":0.0000012123788,"about_ca_topic_score_gemma":7.41367e-7,"teacher_disagreement_score":0.0795588,"about_ca_system_score_codex":0.0000014267624,"about_ca_system_score_gemma":0.00002431341,"threshold_uncertainty_score":0.19633272},"labels":[],"label_agreement":null},{"id":"W2140247984","doi":"10.1109/jstsp.2008.2007816","title":"Probabilistic Boolean Network Analysis of Brain Connectivity in Parkinson's Disease","year":2008,"lang":"en","type":"article","venue":"IEEE Journal of Selected Topics in Signal Processing","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":24,"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":"","keywords":"Probabilistic logic; Computer science; Functional magnetic resonance imaging; Robustness (evolution); Artificial intelligence; Functional connectivity; Parkinson's disease; Neuroimaging; Machine learning; Computational model; Neuroscience; Disease; Psychology; Medicine; Pathology; Biology","score_opus":0.012673672819597796,"score_gpt":0.24698586591490052,"score_spread":0.2343121930953027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140247984","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":[0.992231,0.0024582008,0.005064453,0.00008362027,0.00004019658,0.000084518026,0.0000021210078,0.0000031921932,0.00003271286],"genre_scores_gemma":[0.9987995,0.000114688286,0.0006081012,0.000054158794,0.0003650082,0.000002835767,0.000009584027,0.000014930119,0.0000312068],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9981504,0.00029407121,0.00071266,0.00025809414,0.00028933093,0.00029543263],"domain_scores_gemma":[0.9986776,0.000069370115,0.00054594607,0.00016709429,0.0004205942,0.00011937384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073273043,0.00016708417,0.0005376516,0.0004038426,0.000061852304,0.000013920319,0.0002259303,0.00012613465,0.000008949815],"category_scores_gemma":[0.00022476962,0.00016274942,0.00020621224,0.0022273124,0.00011484827,0.000015841284,0.000027804093,0.0002576649,1.18536704e-7],"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":[0.0003844483,0.00022226218,0.47247487,0.00007365178,0.00038877895,0.00008577308,0.000109284534,0.49831828,0.025228329,0.000006365311,0.00017348987,0.0025344416],"study_design_scores_gemma":[0.0012660469,0.00033050365,0.9271621,0.0002770842,0.00076615415,0.00005224594,0.00004055251,0.056820173,0.0113021415,0.00069942384,0.0008744301,0.00040911007],"about_ca_topic_score_codex":0.000010423272,"about_ca_topic_score_gemma":0.00020396138,"teacher_disagreement_score":0.45468727,"about_ca_system_score_codex":0.000071181435,"about_ca_system_score_gemma":0.00052927795,"threshold_uncertainty_score":0.66367286},"labels":[],"label_agreement":null},{"id":"W2140540053","doi":"10.1109/csb.2004.22","title":"A genetic algorithm for inferring time delays in gene regulatory networks","year":2004,"lang":"en","type":"article","venue":"Computational Systems Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"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 Saskatchewan","funders":"","keywords":"Gene regulatory network; Computer science; Boolean network; Genetic algorithm; Algorithm; Genetic network; Mathematical optimization; Gene; Boolean function; Mathematics; Machine learning; Gene expression; Biology; Genetics","score_opus":0.006372010540183468,"score_gpt":0.21374779745909755,"score_spread":0.2073757869189141,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140540053","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":[0.16608894,0.0010045843,0.8321738,0.00001259977,0.00015368694,0.00045461438,0.00002277986,0.00002216092,0.0000667818],"genre_scores_gemma":[0.7483516,0.000024240739,0.25024644,0.00010818135,0.0004549262,0.00008886042,0.0006032869,0.000036483303,0.00008600853],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99848735,0.000032773703,0.0006876716,0.00022971952,0.00022611636,0.00033634985],"domain_scores_gemma":[0.99917877,0.000026388743,0.00022871772,0.00028044282,0.00017778779,0.000107886925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029748498,0.00021385409,0.0002661712,0.0001425973,0.000107563355,0.000058409107,0.00020363991,0.00019676545,0.0000021521407],"category_scores_gemma":[0.000018299088,0.00022729332,0.0001411065,0.00022818682,0.00005286586,0.000011990748,0.000084493666,0.00007043892,0.000021223927],"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":[0.0000072455573,0.000026218393,0.00028494105,0.00002972239,0.00007755297,0.000001567749,0.000048311034,0.9919142,0.00032347083,0.00008183955,0.00025380854,0.0069511146],"study_design_scores_gemma":[0.0010194612,0.00009013684,0.0036278407,0.00005055978,0.000028997016,0.00006155221,0.000037916947,0.9936812,0.00029823836,0.0002630152,0.0005667099,0.0002743811],"about_ca_topic_score_codex":0.000012840244,"about_ca_topic_score_gemma":0.0000049354767,"teacher_disagreement_score":0.58226264,"about_ca_system_score_codex":0.00010717544,"about_ca_system_score_gemma":0.00015591914,"threshold_uncertainty_score":0.9268753},"labels":[],"label_agreement":null},{"id":"W2140675764","doi":"10.1088/1367-2630/10/1/013028","title":"Complex network analysis of state spaces for random Boolean networks","year":2008,"lang":"en","type":"article","venue":"New Journal of Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"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 Calgary","funders":"","keywords":"Physics; Measure (data warehouse); Degree (music); Topology (electrical circuits); Statistical physics; State (computer science); Node (physics); Sample (material); Boolean network; Successor cardinal; Boolean function; Discrete mathematics; Combinatorics; Mathematics; Quantum mechanics; Computer science; Mathematical analysis; Algorithm; Data mining","score_opus":0.018010936588776713,"score_gpt":0.25242678027961657,"score_spread":0.23441584369083984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140675764","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":[0.5653598,0.0020768458,0.4322445,0.00004898507,0.0001139424,0.000092195995,0.000009348338,0.0000027738608,0.000051636624],"genre_scores_gemma":[0.9915875,0.00078926433,0.0053548943,0.000093763345,0.0018024873,0.0000011387422,0.00006606269,0.000023682347,0.0002811596],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987111,0.000079363854,0.0005464424,0.00016987447,0.00022551867,0.0002676958],"domain_scores_gemma":[0.9983532,0.00005155878,0.0008076733,0.00028786025,0.00035232757,0.00014738821],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002985363,0.00016965374,0.00066677504,0.000079335936,0.00009141513,0.00001243536,0.00025467118,0.00007701242,0.000014002554],"category_scores_gemma":[0.00002206684,0.0001515279,0.00093649,0.0005951815,0.00009148668,0.0000069181674,0.000045623583,0.00009350193,3.5699213e-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":[0.00048174776,0.00005531594,0.009762904,0.0000065455783,0.0045472886,0.000002951894,0.00005724447,0.9370925,0.01668269,0.000031490457,0.026473615,0.0048057497],"study_design_scores_gemma":[0.02717237,0.0046286797,0.09420568,0.00018249819,0.029973395,0.00016813219,0.00029611532,0.5652093,0.11852104,0.0054910593,0.15164123,0.002510498],"about_ca_topic_score_codex":0.000009835807,"about_ca_topic_score_gemma":0.00003547303,"teacher_disagreement_score":0.42688963,"about_ca_system_score_codex":0.000013109955,"about_ca_system_score_gemma":0.00013161356,"threshold_uncertainty_score":0.6179128},"labels":[],"label_agreement":null},{"id":"W2141021005","doi":"10.1186/1752-0509-7-s1-s3","title":"Effects of multimerization on the temporal variability of protein complex abundance","year":2013,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"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 Waterloo","funders":"Academy of Finland","keywords":"Biology; Gene; Messenger RNA; Escherichia coli; Computational biology; Cell biology; Chemistry; Genetics","score_opus":0.012154721979422503,"score_gpt":0.22982712510767883,"score_spread":0.21767240312825634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141021005","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":[0.98809683,0.0003105665,0.010346456,0.000025126079,0.000086867505,0.0009929112,0.000007701916,0.000006200527,0.0001273506],"genre_scores_gemma":[0.9990288,0.000004287233,0.00049912336,0.000016047017,0.00009736333,0.00016325511,0.00006298576,0.000010113254,0.0001180438],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984767,0.0007183586,0.00034169445,0.0002524423,0.00006745405,0.00014334524],"domain_scores_gemma":[0.99896383,0.000098757926,0.000309532,0.0004555383,0.00014374839,0.000028619113],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036202642,0.00011993951,0.00026671687,0.000028465172,0.000034703186,0.0000043531227,0.00019887541,0.00015443393,0.000017249158],"category_scores_gemma":[0.00020038831,0.0000796365,0.000098413286,0.00011200856,0.00018030281,0.0000014664818,0.000055144315,0.000036651953,0.000008524794],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021976914,0.00005612281,0.049371403,0.00016075654,0.00006815782,3.3665685e-8,0.000010234299,0.00045264012,0.94886935,0.0007230139,0.00013892303,0.00012740314],"study_design_scores_gemma":[0.0007554007,0.0008191796,0.15872042,0.000094433424,0.00005825389,0.000003122558,0.00006049159,0.011235166,0.824998,0.0002549343,0.002713643,0.0002869164],"about_ca_topic_score_codex":0.00028199985,"about_ca_topic_score_gemma":0.000013369392,"teacher_disagreement_score":0.1238713,"about_ca_system_score_codex":0.000008810133,"about_ca_system_score_gemma":0.000039019786,"threshold_uncertainty_score":0.32474822},"labels":[],"label_agreement":null},{"id":"W2141316905","doi":"10.1093/bioinformatics/bts726","title":"G<scp>e</scp>S<scp>to</scp>D<scp>ifferent</scp>: a Cytoscape plugin for the generation and the identification of gene regulatory networks describing a stochastic cell differentiation process","year":2013,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"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":"National Institute of General Medical Sciences","keywords":"Identification (biology); Computer science; Gene regulatory network; Plug-in; Computational biology; Systems biology; Biology; Theoretical computer science; Gene; Genetics; Gene expression","score_opus":0.013052161573079488,"score_gpt":0.21098444103755504,"score_spread":0.19793227946447556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141316905","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":[0.61882526,0.0014325811,0.37808126,0.00003400552,0.00017747706,0.0013610809,0.000022138847,0.000021203654,0.000045026623],"genre_scores_gemma":[0.9953734,0.00023831187,0.0019621383,0.00016949249,0.0004816985,0.00050656166,0.00052586757,0.000057448637,0.00068505976],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973614,0.00013381877,0.0011203594,0.00040174057,0.00044368883,0.00053899834],"domain_scores_gemma":[0.996879,0.00053233653,0.001006616,0.00087009865,0.00054570386,0.00016624617],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008483384,0.00041143855,0.00042234038,0.00015073596,0.00046437563,0.00028630398,0.00052133395,0.00032200842,0.0000015559635],"category_scores_gemma":[0.0009283048,0.00029076304,0.00025156818,0.0003765902,0.0002059961,0.000058785205,0.00016716798,0.00017280613,0.000010734748],"study_design_candidate":"simulation_or_modeling","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":[0.000037300724,0.0003058424,0.0014801002,0.0007490088,0.0012532589,3.1403368e-7,0.012640309,0.38341245,0.55370754,0.0004847651,0.03667578,0.009253314],"study_design_scores_gemma":[0.0011760623,0.00011148927,0.0040025287,0.000038880808,0.00048499048,0.0000073223327,0.002926005,0.84900326,0.1416364,0.000115082265,0.00041520875,0.00008274697],"about_ca_topic_score_codex":0.000010444101,"about_ca_topic_score_gemma":0.000024436607,"teacher_disagreement_score":0.46559083,"about_ca_system_score_codex":0.000042906013,"about_ca_system_score_gemma":0.000098087854,"threshold_uncertainty_score":0.99995446},"labels":[],"label_agreement":null},{"id":"W2142441087","doi":"10.1109/tcbb.2013.73","title":"Inference of Gene Regulatory Networks with Variable Time Delay from Time-Series Microarray Data","year":2013,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Computational Biology and Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Inference; Lasso (programming language); Gene regulatory network; Computer science; Pairwise comparison; Variable (mathematics); Data mining; Time series; Process (computing); Biological data; Series (stratigraphy); Microarray analysis techniques; Artificial intelligence; Machine learning; Gene; Bioinformatics; Mathematics; Biology; Genetics","score_opus":0.008457742835487246,"score_gpt":0.22077969629264235,"score_spread":0.2123219534571551,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142441087","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":[0.20449606,0.00022050894,0.7944896,0.00008622841,0.00006605233,0.00017836531,0.00036535526,0.000018537386,0.00007924582],"genre_scores_gemma":[0.649034,0.00011009868,0.34702682,0.00023726265,0.00008809364,0.000015647975,0.0032242292,0.00001701516,0.00024678226],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99897915,0.00006194518,0.00038397088,0.00027915929,0.00010231231,0.00019344201],"domain_scores_gemma":[0.9987958,0.000115357434,0.00018270536,0.000640557,0.00018419648,0.00008136892],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013688942,0.0001997428,0.00024659137,0.00007551897,0.00014942643,0.000025762203,0.00035195946,0.00023308898,0.00014980874],"category_scores_gemma":[0.000012653955,0.00016408462,0.000044889857,0.00015906883,0.00030013116,0.000036930964,0.00002681058,0.000114543865,0.000038267433],"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":[0.000303259,0.00020826067,0.0012734174,0.00003728561,0.0014221221,8.9874027e-7,0.00012779034,0.8660253,0.10273586,0.00005707411,0.002089216,0.025719479],"study_design_scores_gemma":[0.0014444217,0.0010837207,0.004382304,0.00007985007,0.00038643737,0.000075709024,0.00009732092,0.94611436,0.042036157,0.0018593158,0.0016225837,0.0008178016],"about_ca_topic_score_codex":0.000028039045,"about_ca_topic_score_gemma":0.000009382065,"teacher_disagreement_score":0.44746283,"about_ca_system_score_codex":0.000008872004,"about_ca_system_score_gemma":0.000103334016,"threshold_uncertainty_score":0.6691177},"labels":[],"label_agreement":null},{"id":"W2142664740","doi":"10.1186/1471-2105-13-s9-s3","title":"Inference of gene regulatory subnetworks from time course gene expression data","year":2012,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"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 Saskatchewan","funders":"National Natural Science Foundation of China","keywords":"Inference; Gene regulatory network; Computer science; Identification (biology); Computational biology; Block (permutation group theory); Data mining; Set (abstract data type); DNA microarray; Scale (ratio); Gene; Artificial intelligence; Gene expression; Biology; Genetics; Mathematics","score_opus":0.02317497161639883,"score_gpt":0.2607738370857789,"score_spread":0.23759886546938006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142664740","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":[0.8164983,0.005392691,0.17673402,0.000009656808,0.00025505104,0.00022459168,0.00034534856,0.000031813186,0.0005085741],"genre_scores_gemma":[0.7773105,0.00019311093,0.21725723,0.00007275189,0.00065779465,0.0000057442026,0.0042496207,0.000030390425,0.00022283506],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984407,0.00007084386,0.00057339994,0.00022636335,0.0003015787,0.0003871189],"domain_scores_gemma":[0.99721855,0.0000378316,0.000397745,0.0020502422,0.00010179231,0.00019381594],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004610383,0.00022933986,0.00029653116,0.000044935547,0.000069816975,0.00001921581,0.00071734434,0.0002895702,0.0000887198],"category_scores_gemma":[0.00006812413,0.00020957482,0.00010754665,0.00014588423,0.00012310056,0.000038117214,0.00057185616,0.000091799346,0.00007080368],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001423403,0.00039321985,0.097788654,0.00010970666,0.00046390446,7.4503424e-7,0.000421569,0.012456353,0.8404173,0.000027538446,0.03885704,0.0089216],"study_design_scores_gemma":[0.0008000667,0.000091368776,0.035134457,0.000079873316,0.000373138,0.000010347846,0.00016857385,0.23304573,0.7237038,0.000030221232,0.005884492,0.00067792996],"about_ca_topic_score_codex":0.0000076016495,"about_ca_topic_score_gemma":0.000007974243,"teacher_disagreement_score":0.22058937,"about_ca_system_score_codex":0.000013198588,"about_ca_system_score_gemma":0.00012411515,"threshold_uncertainty_score":0.8546213},"labels":[],"label_agreement":null},{"id":"W2142723924","doi":"10.1142/s0219525907000994","title":"ANALYSIS OF PREFERENTIAL NETWORK MOTIF GENERATION IN AN ARTIFICIAL REGULATORY NETWORK MODEL CREATED BY DUPLICATION AND DIVERGENCE","year":2007,"lang":"en","type":"article","venue":"Advances in Complex Systems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Gene duplication; Functional divergence; Gene regulatory network; Divergence (linguistics); Gene; Computational biology; Topology (electrical circuits); Biology; Network topology; Transcription factor; Computer science; Genetics; Genome; Gene family; Mathematics; Gene expression; Computer network; Combinatorics","score_opus":0.025170896904907952,"score_gpt":0.28557410524585813,"score_spread":0.2604032083409502,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142723924","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":[0.9159108,0.006673421,0.077038035,0.0000029477608,0.00008704042,0.0002163617,0.000014482156,0.000007665786,0.00004925016],"genre_scores_gemma":[0.9973978,0.00036259094,0.0007458387,0.000011362631,0.00033436433,0.000020734857,0.0010844832,0.000014326325,0.000028519216],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99819386,0.00015898397,0.00065829745,0.0004971863,0.00018558568,0.00030608138],"domain_scores_gemma":[0.99910456,0.000015989152,0.00028046436,0.00042757718,0.00010046002,0.0000709637],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006949135,0.00016501268,0.00037564608,0.00014243451,0.00007022758,0.000018886582,0.00016303913,0.00014966144,0.0000053593462],"category_scores_gemma":[0.000010641475,0.00017888333,0.000068270616,0.00084960763,0.00008023931,0.000022962062,0.00006134118,0.00006047005,2.6013177e-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":[0.000052179857,0.00003827677,0.14663313,0.000010480574,0.000085226035,2.5537724e-7,0.000024865474,0.75793445,0.09389117,0.00022437773,0.00012557027,0.0009800117],"study_design_scores_gemma":[0.00016880587,0.000058264803,0.056681573,0.000011491735,0.00014255718,6.000389e-7,0.000039539642,0.9396139,0.002636393,0.00009457052,0.00036499958,0.00018734943],"about_ca_topic_score_codex":0.00008094349,"about_ca_topic_score_gemma":0.005114763,"teacher_disagreement_score":0.1816794,"about_ca_system_score_codex":0.00003697882,"about_ca_system_score_gemma":0.00001910416,"threshold_uncertainty_score":0.72946507},"labels":[],"label_agreement":null},{"id":"W2143145695","doi":"10.1109/tnb.2009.2035114","title":"A Computational Tool for Monte Carlo Simulations of Biomolecular Reaction Networks Modeled on Physical Principles","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on NanoBioscience","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Monte Carlo method; Computer science; Statistical physics; Biological system; Molecular biophysics; Systems biology; Physics; Computational biology; Mathematics; Biology","score_opus":0.01350569469620966,"score_gpt":0.2606199255262964,"score_spread":0.24711423083008677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143145695","genre_codex":"methods","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":[0.49201572,0.000012360192,0.5076177,0.00005308858,0.00006482403,0.0001808382,0.0000313176,0.000011108998,0.000013070844],"genre_scores_gemma":[0.9976425,0.000010847706,0.0019517265,0.00012798033,0.00006446315,0.000021335944,0.000018598761,0.000011888068,0.00015064029],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99886626,0.00004313112,0.00023283697,0.000417624,0.0002245469,0.00021560473],"domain_scores_gemma":[0.99931246,0.00004244944,0.00010994133,0.00031566422,0.00015909721,0.00006037819],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010761312,0.00015988485,0.00016920819,0.00011782176,0.00020901009,0.000016887607,0.00016244332,0.00009717354,0.0000015748187],"category_scores_gemma":[0.000010116845,0.00015696342,0.00023404109,0.0003757371,0.000097105636,0.000010964405,0.0000014320937,0.0000665006,0.0000010896373],"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":[0.00007224314,0.00020059502,0.000004316312,0.00000201156,0.000021126772,1.6233238e-7,0.000012714307,0.66164505,0.3360869,0.00005317326,0.000011913921,0.0018897558],"study_design_scores_gemma":[0.00036730594,0.0005638353,0.00032541595,0.000012520681,0.000049928574,0.000002064475,0.000005586027,0.7825173,0.21576346,0.00008439558,0.00016215452,0.00014599405],"about_ca_topic_score_codex":0.0000043745003,"about_ca_topic_score_gemma":0.000008604101,"teacher_disagreement_score":0.50566596,"about_ca_system_score_codex":0.000034629476,"about_ca_system_score_gemma":0.00007335679,"threshold_uncertainty_score":0.64007825},"labels":[],"label_agreement":null},{"id":"W2145013375","doi":"10.1093/icb/icl027","title":"The Evolution of Animal Communication: Reliability and Deception in Signaling Systems. William A. Searcy and S. Nowicki","year":2006,"lang":"en","type":"article","venue":"Integrative and Comparative Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Deception; Reliability (semiconductor); Biology; Cognitive science; Communication; Psychology; Social psychology; Physics","score_opus":0.01573427886299679,"score_gpt":0.27800294215829036,"score_spread":0.2622686632952936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2145013375","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":[0.9758474,0.0225291,0.0010945831,0.00009701709,0.000014622831,0.000159058,0.000007527068,0.0000026399666,0.00024804389],"genre_scores_gemma":[0.99903053,0.00063606934,0.00017197935,0.000005346345,0.0000333465,0.000023344168,0.000037321082,0.0000028062877,0.000059281607],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.998884,0.00047977315,0.00024770325,0.00023525179,0.000038820977,0.0001144073],"domain_scores_gemma":[0.999421,0.00010824965,0.00011766331,0.00016853162,0.00016140126,0.000023154776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036354162,0.00011374081,0.00021446089,0.000037113692,0.00012791631,0.000016130847,0.00007509376,0.000097865915,8.72457e-7],"category_scores_gemma":[0.00002595113,0.00007562978,0.000026375326,0.00010005246,0.0006724659,0.000006164231,0.000080900696,0.00008601793,2.74426e-7],"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":[0.00036295108,0.00006118158,0.39724544,0.000017141972,0.000086744374,2.0527845e-7,0.00038367993,0.0003177321,0.57747614,0.023171242,0.0002509637,0.00062654534],"study_design_scores_gemma":[0.0015175741,0.0021283226,0.87104124,0.00012824743,0.000092115675,0.00002686542,0.012128647,0.010623442,0.08165779,0.00787934,0.012236353,0.00054006773],"about_ca_topic_score_codex":0.00043148317,"about_ca_topic_score_gemma":0.0013134028,"teacher_disagreement_score":0.49581838,"about_ca_system_score_codex":0.000028049208,"about_ca_system_score_gemma":0.00003136298,"threshold_uncertainty_score":0.30840927},"labels":[],"label_agreement":null},{"id":"W2145054862","doi":"10.1109/lssa.2007.4400907","title":"Addressing biological circuit simulation accuracy: Reachability for parameter identification and initial conditions","year":2007,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"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":"","keywords":"Reachability; Computer science; Identification (biology); Experimental data; Biological data; System identification; Data modeling; Algorithm; Mathematics; Bioinformatics","score_opus":0.10107895543488486,"score_gpt":0.3772745428354836,"score_spread":0.27619558740059874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2145054862","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":[0.765085,0.00007957925,0.23441426,0.000034158096,0.000039475995,0.00019901562,0.000013721471,0.000013245613,0.00012158382],"genre_scores_gemma":[0.9981102,0.000008345701,0.0009690272,0.000082217506,0.00019551105,0.000020459733,0.0005160561,0.0000079728825,0.00009025218],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99916583,0.000045568446,0.00025049734,0.00031552478,0.0000605942,0.00016200666],"domain_scores_gemma":[0.9993164,0.00019576793,0.0000922364,0.0002221725,0.00011415793,0.000059298043],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052956486,0.000089664805,0.00009920503,0.000038846843,0.00013278068,0.000031927015,0.000057981746,0.0001568773,0.000022105281],"category_scores_gemma":[0.0004906799,0.000081265185,0.0000794396,0.00006767755,0.0001037938,0.000005897639,0.000032845146,0.000034558812,0.0000018053875],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011612939,0.00009813981,0.01774761,0.000021275066,0.00011090355,5.738275e-7,0.00005032382,0.003253935,0.9434221,0.0005964366,0.0002979421,0.034284674],"study_design_scores_gemma":[0.0016592053,0.00045372164,0.40790674,0.000018319935,0.00024599084,0.000018324747,0.00036212255,0.04034308,0.52351624,0.01108218,0.013563491,0.00083059596],"about_ca_topic_score_codex":0.0000040389045,"about_ca_topic_score_gemma":0.00002441401,"teacher_disagreement_score":0.4199058,"about_ca_system_score_codex":0.00001196644,"about_ca_system_score_gemma":0.000015664524,"threshold_uncertainty_score":0.3313898},"labels":[],"label_agreement":null},{"id":"W2145683333","doi":"10.1186/1471-2105-8-324","title":"Mining and state-space modeling and verification of sub-networks from large-scale biomolecular networks","year":2007,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Computer science; Component (thermodynamics); Context (archaeology); Cluster analysis; Biological network; Function (biology); Network model; Distributed computing; Gene regulatory network; DNA microarray; Systems biology; Data mining; Artificial intelligence; Bioinformatics; Biology","score_opus":0.008122024849831223,"score_gpt":0.21986943049142804,"score_spread":0.21174740564159683,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2145683333","genre_codex":"methods","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":[0.48256135,0.0017863798,0.51550835,0.0000037946982,0.000028081964,0.00006785124,0.0000060095813,0.0000066889165,0.000031463074],"genre_scores_gemma":[0.919093,0.00078116026,0.07973776,0.000046547986,0.00008232753,0.0000024479689,0.00022277942,0.000019521149,0.00001442621],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99886405,0.00002920535,0.000462972,0.00020863274,0.0001324962,0.00030263865],"domain_scores_gemma":[0.99919504,0.000025775653,0.00021450361,0.00035406236,0.00008925589,0.000121370584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051087135,0.00017443472,0.00021424428,0.00006955254,0.000085184576,0.00003146941,0.000103333026,0.00020590036,0.0000015417633],"category_scores_gemma":[0.00002392248,0.00017651008,0.000064610154,0.00016748715,0.00007780726,0.000011852855,0.00012917239,0.00006395998,4.5258346e-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":[0.0002358184,0.00007558948,0.06132728,0.0001448115,0.00030800045,0.0000018668094,0.0012164395,0.8795457,0.041358568,0.000043759257,0.00033967127,0.015402537],"study_design_scores_gemma":[0.0003955923,0.000051353545,0.002161405,0.000025235142,0.000069302136,0.00000369645,0.00068013684,0.9854831,0.010709901,0.000015775458,0.0002111267,0.00019335649],"about_ca_topic_score_codex":0.000012472919,"about_ca_topic_score_gemma":0.00016027289,"teacher_disagreement_score":0.4365317,"about_ca_system_score_codex":0.000009700389,"about_ca_system_score_gemma":0.000025774913,"threshold_uncertainty_score":0.7197872},"labels":[],"label_agreement":null},{"id":"W2146388609","doi":"10.1016/j.cub.2006.06.049","title":"Elephants avoid costly mountaineering","year":2006,"lang":"en","type":"letter","venue":"Current Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":238,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Biology; Mountaineering; Evolutionary biology; Environmental ethics; Archaeology; History","score_opus":0.01393672398455152,"score_gpt":0.2635003348544584,"score_spread":0.2495636108699069,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146388609","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":[0.49528462,0.24942385,0.024138153,0.19034402,0.02925705,0.003269563,0.0022928838,0.00063652045,0.0053533334],"genre_scores_gemma":[0.35662228,0.0071279225,0.001040356,0.34506986,0.11477511,0.00063266157,0.153151,0.0009904667,0.02059033],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975737,0.0001887929,0.00043268752,0.0009246184,0.00013890472,0.0007412983],"domain_scores_gemma":[0.9987517,0.000018531908,0.00024604384,0.0008013413,0.00011568052,0.00006668431],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0001488501,0.0005229867,0.0005236916,0.0001641629,0.000085797335,0.00002571663,0.0005426507,0.0013433859,0.00007555076],"category_scores_gemma":[0.000026021266,0.0005089323,0.0003826415,0.00014756003,0.00016063472,0.0000015588195,0.00025641886,0.0008360342,0.00014594778],"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":[0.0000059956574,0.000022442357,0.0021235899,0.00007311009,0.00018153622,0.000011535768,0.0000016983013,0.00009372525,0.01975155,0.000008175333,0.9744518,0.0032748526],"study_design_scores_gemma":[0.00023973593,0.00008830516,0.00025462353,0.00002787764,0.00011999741,0.000015005404,9.500751e-7,0.00006106104,0.0036554143,0.00011549173,0.99488103,0.0005405245],"about_ca_topic_score_codex":0.000018458519,"about_ca_topic_score_gemma":0.000020303229,"teacher_disagreement_score":0.24229592,"about_ca_system_score_codex":0.00005742167,"about_ca_system_score_gemma":0.00010552656,"threshold_uncertainty_score":0.9999531},"labels":[],"label_agreement":null},{"id":"W2147615881","doi":"10.1371/journal.pone.0019358","title":"A General Model for Binary Cell Fate Decision Gene Circuits with Degeneracy: Indeterminacy and Switch Behavior in the Absence of Cooperativity","year":2011,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Alberta Innovates; Commonwealth Scientific and Industrial Research Organisation","keywords":"Multistability; Cell fate determination; Cooperativity; Bistability; Gene regulatory network; Multipotent Stem Cell; Progenitor cell; Biology; Stem cell; Biological system; Computer science; Physics; Transcription factor; Gene expression; Cell biology; Genetics; Nonlinear system; Gene","score_opus":0.045017743550908346,"score_gpt":0.23772923513505353,"score_spread":0.1927114915841452,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147615881","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":[0.9939614,0.0004921336,0.005093957,0.0000069192715,0.000005014793,0.00039484794,0.000017422373,0.000002954567,0.000025380397],"genre_scores_gemma":[0.9843939,0.00014819473,0.015096609,0.000046826128,0.000035677196,0.00013309754,0.000028101651,0.00001864247,0.00009895898],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991114,0.000048537713,0.00019338414,0.00031026886,0.00015513938,0.00018125406],"domain_scores_gemma":[0.9993598,0.0000142136705,0.00009139939,0.00037470128,0.00011450845,0.00004540306],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019512996,0.00013814286,0.00020376296,0.00004849308,0.000056796318,0.000009412817,0.00018466405,0.00009365225,0.0000028127527],"category_scores_gemma":[0.0000124899125,0.00010066373,0.00004456864,0.00011492806,0.00006694071,0.0000065006075,0.00006768872,0.00005714579,3.6703784e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000107287626,0.0007522589,0.040210966,0.000025823767,0.000043745844,0.0000044295607,0.00024145862,0.000950046,0.95671225,0.000004211225,0.000011481544,0.00093607086],"study_design_scores_gemma":[0.0007113707,0.00054133876,0.037988096,0.000024203484,0.00018006771,0.0000061519004,0.000024849262,0.05587253,0.9044256,0.000037890615,0.0000023772477,0.00018551877],"about_ca_topic_score_codex":0.000019994912,"about_ca_topic_score_gemma":0.00014567022,"teacher_disagreement_score":0.054922484,"about_ca_system_score_codex":0.0000071650384,"about_ca_system_score_gemma":0.000059974736,"threshold_uncertainty_score":0.4104948},"labels":[],"label_agreement":null},{"id":"W2147784911","doi":"10.1109/bibm.2010.5706595","title":"A dynamic qualitative probabilistic network approach for extracting gene regulatory network motifs","year":2010,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Windsor","funders":"","keywords":"Gene regulatory network; Computer science; Motif (music); Saccharomyces cerevisiae; Probabilistic logic; Computational biology; Network motif; Gene; Network analysis; Theoretical computer science; Biological network; Data mining; Genetics; Artificial intelligence; Biology; Gene expression; Engineering","score_opus":0.012982018315271375,"score_gpt":0.2817624900784552,"score_spread":0.26878047176318387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147784911","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":[0.6686682,0.0008387844,0.327296,0.00006998825,0.00038477345,0.00091975264,0.0000134391075,0.000072181654,0.0017368869],"genre_scores_gemma":[0.77582496,0.00001282137,0.21987602,0.00012164314,0.0012613102,0.00019831947,0.00043988167,0.00007057952,0.0021944332],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99746174,0.00019363977,0.00049242954,0.0008626689,0.00021125514,0.00077829114],"domain_scores_gemma":[0.99830055,0.00010888074,0.00026460097,0.0009044405,0.00022859783,0.0001929194],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0015314537,0.00035226118,0.000376854,0.000039812112,0.00032401294,0.000051352232,0.00035471303,0.00038247777,0.000036837857],"category_scores_gemma":[0.00020142768,0.0003352627,0.00029623258,0.00028630573,0.00018215911,0.0000070100928,0.0001455378,0.00024781,0.000005373204],"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":[0.0002563637,0.00025208216,0.0010009361,0.00010160439,0.00082373037,0.0000019977626,0.00040935408,0.488261,0.48348832,0.003799666,0.015243512,0.0063614263],"study_design_scores_gemma":[0.0031862638,0.0010336019,0.0095029855,0.000056052795,0.0011176438,0.00014706254,0.0018403312,0.91159034,0.026454326,0.01687688,0.024694204,0.0035002935],"about_ca_topic_score_codex":0.000006729632,"about_ca_topic_score_gemma":0.00013926529,"teacher_disagreement_score":0.457034,"about_ca_system_score_codex":0.000028328037,"about_ca_system_score_gemma":0.00011730788,"threshold_uncertainty_score":0.99990994},"labels":[],"label_agreement":null},{"id":"W2148887796","doi":"10.1109/cibcb.2011.5948475","title":"Reverse engineering of gene regulatory networks: A systems approach","year":2011,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Queen's University","funders":"","keywords":"Computer science; Gene regulatory network; Reverse engineering; Component (thermodynamics); Identification (biology); Systems biology; Expression (computer science); Function (biology); Computational biology; Gene expression; Gene; Biology; Genetics","score_opus":0.011271122196960214,"score_gpt":0.17728393890508445,"score_spread":0.16601281670812423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2148887796","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":[0.7209281,0.0050038607,0.26577765,0.0000024695946,0.0002554169,0.0002603492,0.0000035100024,0.000044632925,0.0077240346],"genre_scores_gemma":[0.98731226,0.000061068364,0.011391522,0.000016625148,0.00020572286,0.00001538539,0.00003309086,0.000026570391,0.00093775324],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991146,0.000035108944,0.00025569243,0.0002762349,0.000107989574,0.0002103774],"domain_scores_gemma":[0.99918133,0.0000027060662,0.00009479729,0.0005680776,0.00007080003,0.00008230318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021619449,0.00014261772,0.00020318276,0.000053656764,0.000021357333,0.0000048364886,0.00018336125,0.00015177406,0.000018832972],"category_scores_gemma":[0.000009799322,0.00013442723,0.0001393213,0.000147715,0.000038946648,0.0000022315464,0.000061701096,0.00004567025,0.000002440739],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008829949,0.00020520814,0.0063233324,0.0001215548,0.0009194854,0.0000054267684,0.000130401,0.33563253,0.6471894,0.0017329203,0.006982554,0.00066891976],"study_design_scores_gemma":[0.0011646897,0.00036171192,0.01796713,0.00006321123,0.00044773731,0.00011755794,0.0004985326,0.34270978,0.6270443,0.000013377649,0.008375106,0.0012368348],"about_ca_topic_score_codex":0.000032448548,"about_ca_topic_score_gemma":0.0000016484533,"teacher_disagreement_score":0.26638418,"about_ca_system_score_codex":0.000009126467,"about_ca_system_score_gemma":0.000020532385,"threshold_uncertainty_score":0.5481783},"labels":[],"label_agreement":null},{"id":"W2149272200","doi":"10.1016/j.copbio.2006.08.005","title":"Experimental approaches to identify genetic networks","year":2006,"lang":"en","type":"review","venue":"Current Opinion in Biotechnology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Ontario Genomics Institute; Genome Canada","keywords":"Budding yeast; Benchmark (surveying); Saccharomyces cerevisiae; Computational biology; Computer science; Systems biology; Set (abstract data type); Biology; Genome; Fish <Actinopterygii>; Yeast; Genetics; Gene","score_opus":0.1262240846860137,"score_gpt":0.3703639991405794,"score_spread":0.24413991445456568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149272200","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00021474477,0.99115425,0.0048357844,0.00003976197,0.0027555565,0.0008959737,0.000019643927,0.00005727064,0.000027020718],"genre_scores_gemma":[0.00077292044,0.99546456,0.0005448729,0.0000068490604,0.0013373051,0.0005055182,0.0012141389,0.00010177446,0.000052077958],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966772,0.00021858641,0.000923478,0.0013314049,0.000176115,0.00067319546],"domain_scores_gemma":[0.99833196,0.000012849204,0.0003321377,0.0011867692,0.000019829944,0.00011644651],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00019371639,0.00067497836,0.0012580564,0.0006974782,0.000070236,0.000038220645,0.0009250574,0.0017017915,0.000014342907],"category_scores_gemma":[0.000021572097,0.00067111483,0.00056178356,0.00094873144,0.00017985443,0.0000024472276,0.0007917081,0.0005614142,0.0000636628],"study_design_candidate":"not_applicable","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":[0.0000075684466,0.0002533146,0.00005949537,0.0018233635,0.00014593426,0.0000018700323,0.000004583631,0.0014679363,0.00009247854,0.00019658,0.01276395,0.9831829],"study_design_scores_gemma":[0.00017161215,0.00010930289,0.00003631964,0.0013901914,0.000090611895,0.000037066115,0.000008242282,0.00013928849,0.00023316585,0.00001274096,0.99713117,0.0006402715],"about_ca_topic_score_codex":0.000006949632,"about_ca_topic_score_gemma":0.0000067539786,"teacher_disagreement_score":0.98436725,"about_ca_system_score_codex":0.00013671532,"about_ca_system_score_gemma":0.00011956046,"threshold_uncertainty_score":0.9995942},"labels":[],"label_agreement":null},{"id":"W2149343899","doi":"10.1109/titb.2008.2007649","title":"Mining, Modeling, and Evaluation of Subnetworks From Large Biomolecular Networks and Its Comparison Study","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Information Technology in Biomedicine","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"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 Saskatchewan","funders":"","keywords":"Computer science; Subnetwork; Cluster analysis; Biological network; Probabilistic logic; Data mining; Gene regulatory network; Context (archaeology); Theoretical computer science; Artificial intelligence; Computational biology","score_opus":0.01254205238942762,"score_gpt":0.28052636317488183,"score_spread":0.2679843107854542,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149343899","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":[0.7203367,0.0012999164,0.27774286,0.0001998069,0.000064329106,0.0003182046,0.000006830735,0.000019367068,0.000012007715],"genre_scores_gemma":[0.9992676,0.00028635026,0.00022658365,0.00008150692,0.000023457686,0.000031095522,0.00007427743,0.000006313946,0.000002865631],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99873924,0.00007131611,0.0005458746,0.00021638436,0.00024191491,0.00018524252],"domain_scores_gemma":[0.9993231,0.000009407481,0.00017138205,0.00027018593,0.00017851965,0.000047358884],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005928692,0.00016082615,0.00026846922,0.0006361038,0.000075080665,0.000008866287,0.00010893955,0.00032033242,0.000009138155],"category_scores_gemma":[0.000013367596,0.00015795064,0.000031151765,0.0006091888,0.00006979027,0.000021021126,0.000004808699,0.0001514104,7.9508345e-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":[0.00037873664,0.001188484,0.009460365,0.000025185636,0.0005337944,0.000002265615,0.0013639814,0.762998,0.03348478,0.000076291464,0.00017138757,0.19031677],"study_design_scores_gemma":[0.0026418564,0.0009820325,0.001721858,0.000039994185,0.00021427582,0.0000047855597,0.0014685888,0.97933996,0.01326656,0.00010097585,0.00006483737,0.00015430752],"about_ca_topic_score_codex":0.000017507382,"about_ca_topic_score_gemma":0.0000623429,"teacher_disagreement_score":0.27893087,"about_ca_system_score_codex":0.000023701312,"about_ca_system_score_gemma":0.000025732375,"threshold_uncertainty_score":0.644104},"labels":[],"label_agreement":null},{"id":"W2150072274","doi":"10.15252/msb.20145160","title":"A system‐level model for the microbial regulatory genome","year":2014,"lang":"en","type":"article","venue":"Molecular Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":74,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Biological and Environmental Research; National Institute of General Medical Sciences; Fundação de Amparo à Pesquisa do Estado de São Paulo; U.S. Department of Energy; Office of Science; National Institutes of Health; National Science Foundation","keywords":"Regulon; Biology; Genome; ENCODE; Computational biology; Gene; Regulation of gene expression; Operon; Gene regulatory network; Genetics; Transcriptional regulation; Bacterial genome size; Regulatory sequence; Systems biology; Cis-regulatory module; Transcription factor; Promoter; Gene expression","score_opus":0.012799168538374844,"score_gpt":0.2215801313136763,"score_spread":0.20878096277530145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150072274","genre_codex":"methods","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":[0.20946915,0.004412876,0.7844201,0.000114716,0.00051398046,0.00072314753,0.00008086886,0.000039719336,0.00022543842],"genre_scores_gemma":[0.99615276,0.000018686735,0.001042645,0.00026845848,0.00072292855,0.00029144445,0.00026494483,0.00006802329,0.0011700818],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997881,0.00032917148,0.0004609217,0.00068472355,0.000115608316,0.0005285866],"domain_scores_gemma":[0.998249,0.00003486183,0.0002272814,0.0011850618,0.00019423185,0.000109574285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008908564,0.0003131928,0.00041114748,0.00007588751,0.00023803077,0.000040349518,0.0005939364,0.00040866548,0.0000017844042],"category_scores_gemma":[0.00006456747,0.00023860921,0.00037616762,0.00011949614,0.00017028632,0.0000020775444,0.00017277528,0.000090380134,0.00001631527],"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":[0.000047658836,0.000016372896,0.00016279981,0.00008116756,0.00038204095,8.734389e-7,0.000019507928,0.0737256,0.9173433,0.006877903,0.00097005704,0.00037272155],"study_design_scores_gemma":[0.0017272562,0.00040664486,0.00054497505,0.000040954248,0.00048349396,0.000164417,0.000110215005,0.8246646,0.044112753,0.00014568823,0.12663458,0.0009644117],"about_ca_topic_score_codex":0.00004060137,"about_ca_topic_score_gemma":0.000036311885,"teacher_disagreement_score":0.8732305,"about_ca_system_score_codex":0.00005028953,"about_ca_system_score_gemma":0.00009307242,"threshold_uncertainty_score":0.97302014},"labels":[],"label_agreement":null},{"id":"W2150153992","doi":"10.1093/bioinformatics/btm560","title":"Petri net-based method for the analysis of the dynamics of signal propagation in signaling pathways","year":2007,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Petri net; Computer science; SIGNAL (programming language); Representation (politics); Signal-flow graph; Dynamics (music); Network dynamics; Process (computing); Signal transduction; Systems biology; Theoretical computer science; Computational biology; Distributed computing; Biology; Cell biology; Mathematics; Programming language","score_opus":0.011995817193112481,"score_gpt":0.2528520046799133,"score_spread":0.24085618748680082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150153992","genre_codex":"methods","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":[0.25225544,0.000105707855,0.7472427,0.00003628241,0.000027316863,0.00024815067,0.000033431857,0.0000022250033,0.000048745118],"genre_scores_gemma":[0.96401197,0.0000066787843,0.03573275,0.00005582601,0.000026207434,0.000007618695,0.00013327782,0.000007486346,0.000018170324],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998913,0.000045957087,0.0005873516,0.000090198504,0.00019903369,0.00016444469],"domain_scores_gemma":[0.9988316,0.00015444604,0.00045086423,0.00037071004,0.00016904593,0.000023323446],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014355091,0.00010165409,0.00021303653,0.00016835665,0.000056092893,0.000007687243,0.00026139754,0.00010386043,0.000004210783],"category_scores_gemma":[0.00009236422,0.0000634798,0.00032789257,0.0009726385,0.000066890854,0.000003492941,0.00004762534,0.000051801624,1.284495e-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":[0.000116506955,0.00007071592,0.013077965,0.00013898328,0.00092357985,1.1900425e-7,0.00029570435,0.8856693,0.074063644,0.0005638322,0.00005191951,0.02502774],"study_design_scores_gemma":[0.00022155952,0.00004787616,0.0051734434,0.000009749427,0.00053098507,2.6886607e-7,0.00036301778,0.8399397,0.15354362,0.000022397453,0.0000791964,0.00006817774],"about_ca_topic_score_codex":0.000017480215,"about_ca_topic_score_gemma":0.00038618065,"teacher_disagreement_score":0.7117565,"about_ca_system_score_codex":0.000029456392,"about_ca_system_score_gemma":0.0000994367,"threshold_uncertainty_score":0.2588631},"labels":[],"label_agreement":null},{"id":"W2150335707","doi":"10.1098/rspa.2010.0275","title":"Approximating intrinsic noise in continuous multispecies models","year":2010,"lang":"en","type":"article","venue":"Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":23,"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 Waterloo","funders":"","keywords":"Statistical physics; Perturbation (astronomy); Physics; Noise (video); Biological system; Computer science; Biology; Quantum mechanics","score_opus":0.006193574891141499,"score_gpt":0.20041629821103024,"score_spread":0.19422272331988874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150335707","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":[0.9988481,0.000041080315,0.00051750976,0.00006860571,0.000025797322,0.000082227954,6.53675e-7,0.000009708537,0.00040631817],"genre_scores_gemma":[0.990577,0.0000033681201,0.009226767,0.000011404607,0.0001149232,0.000010232133,1.678443e-7,0.0000067000333,0.000049425405],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99928695,0.000001893469,0.00015686626,0.00020034034,0.00016798808,0.00018594386],"domain_scores_gemma":[0.99976265,0.000024318224,0.000060813512,0.000061817744,0.000046119527,0.00004429773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002664173,0.00010660493,0.00018208355,0.000012259677,0.00007269355,0.000034703462,0.00023605766,0.000057461984,0.0000013025248],"category_scores_gemma":[0.0001368631,0.00007016726,0.0001328145,0.00018788624,0.00030044798,0.000010382921,0.0001842052,0.0001363871,3.22317e-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":[0.0000051814486,0.00017556772,0.0030099747,0.00031210316,0.000050676972,5.4233496e-8,0.001185899,0.026319526,0.93657196,0.031474095,0.00014337829,0.0007516097],"study_design_scores_gemma":[0.00014195104,0.0000398108,0.0027158412,0.00005197354,0.000020983365,0.0000016702095,0.00027097634,0.94191843,0.044070844,0.01059412,0.000024012019,0.00014939877],"about_ca_topic_score_codex":0.0000032673547,"about_ca_topic_score_gemma":4.1646285e-7,"teacher_disagreement_score":0.91559887,"about_ca_system_score_codex":0.0000037572947,"about_ca_system_score_gemma":0.000008669659,"threshold_uncertainty_score":0.28613377},"labels":[],"label_agreement":null},{"id":"W2150616088","doi":"10.1109/tnn.2011.2165556","title":"Delay-Independent Stability of Genetic Regulatory Networks","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Neural Networks","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":53,"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 Saskatchewan","funders":"","keywords":"Gene regulatory network; Stability (learning theory); Computer science; Genetic network; Control theory (sociology); Gene; Mathematical optimization; Mathematics; Genetics; Biology; Artificial intelligence; Gene expression; Machine learning","score_opus":0.016732998477795955,"score_gpt":0.21638660459837544,"score_spread":0.19965360612057947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150616088","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":[0.5631802,0.00058961037,0.43538323,0.0000072229473,0.00046846832,0.00020188579,0.000006450073,0.000028535473,0.00013436716],"genre_scores_gemma":[0.9984946,0.00026334287,0.00064840936,0.0001232039,0.00023298108,0.000042328964,0.000013434483,0.000059815386,0.000121876525],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977394,0.00022454001,0.0005961101,0.0006621008,0.00027265798,0.0005052112],"domain_scores_gemma":[0.9983304,0.000026094933,0.00021184993,0.0010711726,0.00014360563,0.00021683608],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00024486016,0.00034901258,0.00036151308,0.00009458708,0.00015829143,0.000012696748,0.00037660272,0.00039436377,0.00023979881],"category_scores_gemma":[0.0000028388467,0.00034979096,0.00046397353,0.00032527093,0.0002268097,0.000008711602,0.000008966594,0.0003384151,0.0000042018696],"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":[0.00041449393,0.0003089692,0.0036297888,0.00001386194,0.00032367517,0.000010139427,0.000047540736,0.96726847,0.007215576,0.0000060480397,0.00024030975,0.020521136],"study_design_scores_gemma":[0.0016593644,0.001623978,0.04063827,0.000045245066,0.0007223919,0.000115385905,0.000113198024,0.7053221,0.24808492,0.000060925875,0.00033208312,0.0012821505],"about_ca_topic_score_codex":0.000038767896,"about_ca_topic_score_gemma":0.00020502663,"teacher_disagreement_score":0.4353144,"about_ca_system_score_codex":0.000034570337,"about_ca_system_score_gemma":0.00004069108,"threshold_uncertainty_score":0.9998954},"labels":[],"label_agreement":null},{"id":"W2150917095","doi":"10.1038/msb4100037","title":"Physics takes another stab at biological design principles","year":2005,"lang":"en","type":"article","venue":"Molecular Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Biology; Stab; Computational biology; Engineering ethics; Engineering; Anatomy","score_opus":0.035909174874849195,"score_gpt":0.24690297285148385,"score_spread":0.21099379797663464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150917095","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":[0.7012051,0.011884962,0.28467974,0.00015065359,0.00024755785,0.0005029694,0.000025894424,0.00006850691,0.0012346683],"genre_scores_gemma":[0.9938465,0.00014365908,0.003064802,0.00038507397,0.0007457164,0.00009129994,0.00020950624,0.00005334473,0.0014601445],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9975056,0.0006245443,0.00042546244,0.0007598038,0.00012626415,0.0005583048],"domain_scores_gemma":[0.9987852,0.000021722688,0.00020784531,0.0007667952,0.00010559891,0.00011283911],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00040060197,0.00034936538,0.0004184995,0.000054219538,0.00012836051,0.000026213003,0.00038220358,0.00047223203,0.000042804295],"category_scores_gemma":[0.000050538132,0.00029092596,0.00024495943,0.00016056033,0.00020399937,0.0000031806403,0.00018923501,0.00009497664,0.00013942442],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006255952,0.00006347728,0.0050229556,0.000010166886,0.00028021095,0.000008310911,0.000020144547,0.018889267,0.9717567,0.00095116225,0.0013660552,0.001568969],"study_design_scores_gemma":[0.0007253369,0.0005012025,0.000773273,0.000015322652,0.000075343734,0.000085247935,0.00003291157,0.004631167,0.52571684,0.000052772975,0.46668324,0.00070732785],"about_ca_topic_score_codex":0.000016406197,"about_ca_topic_score_gemma":0.000018739735,"teacher_disagreement_score":0.4653172,"about_ca_system_score_codex":0.000069609436,"about_ca_system_score_gemma":0.000059939146,"threshold_uncertainty_score":0.9999543},"labels":[],"label_agreement":null},{"id":"W2151232515","doi":"10.1093/bioinformatics/btn611","title":"Sparse combinatorial inference with an application in cancer biology","year":2008,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kinexus Bioinformatics Corporation (Canada)","funders":"Basic Energy Sciences; National Institutes of Health; National Cancer Institute; Office of Science; AstraZeneca; U.S. Department of Energy","keywords":"Inference; Computer science; Curse of dimensionality; Boolean function; Focus (optics); Statistical inference; Function (biology); Theoretical computer science; Boolean expression; Boolean network; Machine learning; Artificial intelligence; Algorithm; Mathematics; Biology; Statistics","score_opus":0.015231213001381477,"score_gpt":0.2626038295757963,"score_spread":0.24737261657441484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151232515","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":[0.9905413,0.00012207212,0.008687826,0.000021614893,0.000066588,0.00014341975,0.0000073311744,0.000012194835,0.00039769828],"genre_scores_gemma":[0.99615204,0.00022498448,0.0031492645,0.00008555621,0.00012701265,0.000042326166,0.0001803737,0.00000930701,0.000029105247],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99935746,0.000024420944,0.00021749339,0.00013904725,0.000079370875,0.00018218836],"domain_scores_gemma":[0.9994283,0.0000049761193,0.00010512647,0.00033004407,0.00006681478,0.00006475598],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000083757586,0.000113325914,0.00013254568,0.00005653359,0.000054628243,0.0000067783867,0.0001557104,0.00012593034,0.000006145114],"category_scores_gemma":[0.0000115232015,0.00009633358,0.00002628113,0.00017921349,0.00009780528,0.0000087697545,0.00004237574,0.000056855548,0.000009080699],"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":[0.00037613267,0.00043442388,0.9230179,0.00007485839,0.00018933928,0.000005041783,0.0009861112,0.01679294,0.029940752,0.003085073,0.000984759,0.024112636],"study_design_scores_gemma":[0.013793172,0.00618864,0.29512665,0.00012399144,0.00030017394,0.00019448312,0.0011386051,0.3839336,0.13576628,0.0023835702,0.15699707,0.004053748],"about_ca_topic_score_codex":0.000095869065,"about_ca_topic_score_gemma":0.00036602243,"teacher_disagreement_score":0.62789124,"about_ca_system_score_codex":0.000020964877,"about_ca_system_score_gemma":0.00012551996,"threshold_uncertainty_score":0.39283693},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.008619950761029931,"score_gpt":0.22898715813783438,"score_spread":0.22036720737680446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151484461","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":[0.7421773,0.0030944936,0.2542111,0.000012995209,0.00024618092,0.00018672741,0.0000029942498,0.000009430915,0.0000587816],"genre_scores_gemma":[0.99888206,0.000031349122,0.00008651295,0.000052826414,0.00044631102,0.000031310276,0.00019041146,0.00001552094,0.00026368914],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985531,0.00050095643,0.00030113402,0.00038680056,0.00004030414,0.00021770709],"domain_scores_gemma":[0.9994657,0.000045033623,0.00013998464,0.0002283602,0.00006462791,0.000056278786],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050727086,0.00014672207,0.00024998322,0.000080486985,0.000042143714,0.00001616646,0.000075020784,0.00024191014,0.0000019777706],"category_scores_gemma":[0.00010014894,0.00013754085,0.00007633127,0.00007802756,0.00008073258,0.0000025695426,0.000068784924,0.000062679486,0.000004201146],"study_design_candidate":"simulation_or_modeling","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":[0.0009931448,0.00031598835,0.2508439,0.00028126978,0.00083338155,0.0000063258253,0.0004923768,0.2781619,0.3973589,0.009333369,0.0010610546,0.060318362],"study_design_scores_gemma":[0.004244153,0.0014810472,0.08317891,0.00020659668,0.00017672309,0.00019473826,0.0010997654,0.89594924,0.0073529766,0.00040401256,0.004640097,0.0010717533],"about_ca_topic_score_codex":0.00010651885,"about_ca_topic_score_gemma":0.0006801193,"teacher_disagreement_score":0.6177873,"about_ca_system_score_codex":0.000022345957,"about_ca_system_score_gemma":0.000013163885,"threshold_uncertainty_score":0.5608753},"labels":[],"label_agreement":null},{"id":"W2151991601","doi":"10.1093/database/bau095","title":"WholeCellSimDB: a hybrid relational/HDF database for whole-cell model predictions","year":2014,"lang":"en","type":"article","venue":"Database","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":43,"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 Prince Edward Island","funders":"National Center for Chronic Disease Prevention and Health Promotion; U.S. National Library of Medicine; National Institute of General Medical Sciences; National Institutes of Health","keywords":"Computer science; Python (programming language); JSON; Metadata; JavaScript; Database; Interface (matter); Relational database; Graphical user interface; Interoperability; SQL; Relational database management system; Information retrieval; World Wide Web; Programming language","score_opus":0.015070836204794637,"score_gpt":0.23656580453771275,"score_spread":0.22149496833291812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151991601","genre_codex":"methods","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":[0.10325623,0.00049301516,0.88795906,0.00026256207,0.00013695256,0.00034696716,0.0065745143,0.00004290074,0.0009277683],"genre_scores_gemma":[0.8836184,0.000108493994,0.0420424,0.00068268797,0.0008318839,0.0001798821,0.06613497,0.00008151512,0.006319764],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99848336,0.000066392466,0.0002877405,0.00062948815,0.00020109124,0.00033194968],"domain_scores_gemma":[0.9983574,0.000036728303,0.00011823349,0.0011604637,0.00013830562,0.0001888826],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003972223,0.00021636185,0.00017659276,0.0000833096,0.00021199317,0.000025613364,0.00026460868,0.00008331684,0.000029494122],"category_scores_gemma":[0.00012811631,0.00022918853,0.00017048541,0.00011960402,0.000072094736,0.00001643071,0.00020365682,0.0001022293,0.00006531934],"study_design_candidate":"not_applicable","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":[0.00010723676,0.00025780723,0.00067934394,0.000075150216,0.00012522972,0.0000017890388,0.000012308311,0.11266642,0.522112,0.00076976727,0.36268535,0.00050754467],"study_design_scores_gemma":[0.0010244801,0.000084859785,0.000050357612,0.000015177467,0.00018543041,0.000007597374,0.000010526377,0.5462779,0.062188406,0.00014987649,0.3896956,0.00030982896],"about_ca_topic_score_codex":0.0000087581775,"about_ca_topic_score_gemma":0.000032472642,"teacher_disagreement_score":0.8459167,"about_ca_system_score_codex":0.000018057026,"about_ca_system_score_gemma":0.00010536503,"threshold_uncertainty_score":0.9346037},"labels":[],"label_agreement":null},{"id":"W2152223517","doi":"10.1038/msb.2008.31","title":"Colored extrinsic fluctuations and stochastic gene expression","year":2008,"lang":"en","type":"article","venue":"Molecular Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":273,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"William Osler Health System; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Biology; Biological system; Statistical physics; Noise (video); Colors of noise; Feed forward; Gene regulatory network; Stochastic process; Negative feedback; Physics; Function (biology); Gene expression; Gene; Genetics; Computer science; Statistics; Mathematics; Quantum mechanics","score_opus":0.00980371723301397,"score_gpt":0.22403158051118613,"score_spread":0.21422786327817217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152223517","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":[0.8894147,0.008160629,0.10179444,0.000037167534,0.00019641966,0.0002596898,0.00001565657,0.000023764333,0.00009753449],"genre_scores_gemma":[0.99822205,0.00012759508,0.000729372,0.00007444808,0.00019103993,0.000080034966,0.00026691158,0.000029171857,0.00027939884],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99855924,0.00023157727,0.00028623536,0.00052561006,0.00009802793,0.000299328],"domain_scores_gemma":[0.9991478,0.000012993937,0.000119038625,0.0004887721,0.00010258765,0.00012882627],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013661965,0.0002084292,0.0002777084,0.00009989572,0.00018419644,0.000012310934,0.00015910015,0.00027159494,0.000007083229],"category_scores_gemma":[0.000060369166,0.00019540553,0.00009745357,0.00014478705,0.00019877541,0.00000250365,0.0001483074,0.00007139187,0.000013953721],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021151685,0.000020805757,0.0013480484,0.0000073747533,0.000090865666,0.000015012725,0.000026030213,0.0031190033,0.99463886,0.00015535206,0.0003902782,0.00016722157],"study_design_scores_gemma":[0.002750475,0.0010340388,0.011356062,0.000054305987,0.00025461076,0.001893209,0.00016226966,0.008187921,0.95298105,0.00021519502,0.019656492,0.001454379],"about_ca_topic_score_codex":0.000024508867,"about_ca_topic_score_gemma":0.0000058880896,"teacher_disagreement_score":0.108807325,"about_ca_system_score_codex":0.000016346768,"about_ca_system_score_gemma":0.00006439763,"threshold_uncertainty_score":0.79684067},"labels":[],"label_agreement":null},{"id":"W2152897367","doi":"10.1371/journal.pone.0102873","title":"Gene Networks of Fully Connected Triads with Complete Auto-Activation Enable Multistability and Stepwise Stochastic Transitions","year":2014,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":45,"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":"Canadian Institutes of Health Research; American Heart Association; National Science Foundation","keywords":"Multistability; Network topology; Gene regulatory network; SOX2; Computational biology; Computer science; Topology (electrical circuits); Biology; Boolean network; Regulation of gene expression; Transcription factor; Genetics; Gene; Gene expression; Physics; Computer network; Mathematics; Algorithm","score_opus":0.01864178714687467,"score_gpt":0.1958539760066758,"score_spread":0.17721218885980114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152897367","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":[0.8613293,0.0001787853,0.1381274,0.000058086767,0.000006227914,0.00024192399,0.000020044747,0.0000140224765,0.000024202543],"genre_scores_gemma":[0.9960494,0.000018119672,0.0034646834,0.000033198437,0.00009556018,0.000028460787,0.00026011054,0.000018906776,0.00003153128],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99903494,0.00012539675,0.00022018122,0.0003011831,0.00014294987,0.00017537283],"domain_scores_gemma":[0.999207,0.00003785386,0.00012051398,0.0003431976,0.00021054034,0.00008090393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017987979,0.00013470816,0.00028306094,0.0000377741,0.000079793026,0.000011982519,0.00007003831,0.00009890814,0.000018423876],"category_scores_gemma":[0.00006238886,0.0001265263,0.000046169218,0.00014479774,0.00012441911,0.0000047368753,0.000024962648,0.00006430655,5.5876836e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033239354,0.0003773347,0.0010353344,0.00004977157,0.00041404323,1.85316e-7,0.000038325736,0.025525853,0.9719063,0.000031214367,0.000009088465,0.0002801312],"study_design_scores_gemma":[0.004289236,0.001942018,0.025349692,0.00014130097,0.001136959,0.000005987606,0.00008048668,0.4381763,0.52807176,0.00013910362,0.00007993415,0.00058722036],"about_ca_topic_score_codex":0.000019871984,"about_ca_topic_score_gemma":0.00006642983,"teacher_disagreement_score":0.44383457,"about_ca_system_score_codex":0.000012169648,"about_ca_system_score_gemma":0.000030186084,"threshold_uncertainty_score":0.5159593},"labels":[],"label_agreement":null},{"id":"W2153184834","doi":"10.1109/cca.2005.1507116","title":"Genetic network inference via gene set stochastic sampling and sensitivity analysis","year":2005,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Generalizability theory; Robustness (evolution); Inference; Computer science; Artificial neural network; Gene regulatory network; Set (abstract data type); Artificial intelligence; Machine learning; Computational biology; Data mining; Gene; Gene expression; Biology; Genetics; Mathematics; Statistics","score_opus":0.012343918777446575,"score_gpt":0.25449726587046834,"score_spread":0.24215334709302178,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2153184834","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":[0.5557596,0.00082616095,0.44324964,0.000040054238,0.000017593615,0.000057374567,0.0000041041876,0.00001382598,0.000031631684],"genre_scores_gemma":[0.9762422,0.00011963656,0.02244685,0.00025312311,0.00064028247,0.0000072533035,0.000091061585,0.000019529947,0.0001800806],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985227,0.00011488846,0.0002623361,0.0005605918,0.0001492641,0.00039023053],"domain_scores_gemma":[0.99909717,0.000041545758,0.00009289321,0.0005095541,0.00008868061,0.00017014341],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029991215,0.0002258075,0.00030635082,0.00009178225,0.00013999906,0.000039959352,0.00007823374,0.00015009868,0.000054412554],"category_scores_gemma":[0.000030819516,0.0002216788,0.00017950992,0.00048041678,0.00008245532,0.0000038124667,0.00017960231,0.00007725055,0.000012795949],"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":[0.000012596668,0.00001703463,0.033060428,0.000003167209,0.0008426432,0.000002413515,0.00001377009,0.89971536,0.060751833,0.0000097608445,0.00012469871,0.0054462883],"study_design_scores_gemma":[0.0005202446,0.00012917061,0.28670818,0.000007928509,0.0025330216,0.00008702,0.000027727092,0.6926503,0.014081927,0.00014715544,0.002149677,0.0009576756],"about_ca_topic_score_codex":0.000055592154,"about_ca_topic_score_gemma":0.0013710632,"teacher_disagreement_score":0.42080277,"about_ca_system_score_codex":0.000016770588,"about_ca_system_score_gemma":0.000034329205,"threshold_uncertainty_score":0.9039799},"labels":[],"label_agreement":null},{"id":"W2153917440","doi":"10.1016/j.biosystems.2005.09.010","title":"Dynamical properties of model gene networks and implications for the inverse problem","year":2005,"lang":"en","type":"article","venue":"Biosystems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Boolean network; Inverse; Logarithm; Matching (statistics); Boolean model; Mathematics; Boolean function; Function (biology); Upper and lower bounds; Gene regulatory network; Inverse problem; Computer science; Mathematical optimization; Applied mathematics; Discrete mathematics; Gene; Biology; Statistics; Gene expression; Genetics","score_opus":0.01882024732517422,"score_gpt":0.2295458387987989,"score_spread":0.21072559147362468,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2153917440","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":[0.9434961,0.007740931,0.047315538,0.00078587834,0.000030040255,0.00056024047,0.000020583391,0.000009579752,0.0000410989],"genre_scores_gemma":[0.9974449,0.00021672904,0.00164036,0.0000530046,0.00022728363,0.00010153027,0.000022487797,0.000012950861,0.00028075278],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999448,0.000020007441,0.0001846216,0.00017856671,0.0000405736,0.0001282525],"domain_scores_gemma":[0.9995091,0.000005664226,0.000078068304,0.0002917203,0.00007801314,0.000037464422],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014827751,0.00008339555,0.00010961253,0.000015574396,0.000079772086,0.000011100508,0.00012107257,0.00008876788,3.4213778e-7],"category_scores_gemma":[0.0000074474965,0.000055606903,0.000073682044,0.000053911317,0.00006882056,0.0000019797765,0.000054369728,0.000023319963,3.5444552e-7],"study_design_candidate":"simulation_or_modeling","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":[0.000028799814,0.000028680142,0.0018598752,0.000043447715,0.00016633568,1.2981342e-8,0.000032551223,0.20811987,0.7852309,0.00021974566,0.0023213138,0.0019484981],"study_design_scores_gemma":[0.00024578426,0.00004421559,0.00053827686,0.000013972169,0.00009392792,0.000007329811,0.000033516735,0.9533369,0.038885333,0.000022221726,0.0066586644,0.000119836135],"about_ca_topic_score_codex":0.000008225134,"about_ca_topic_score_gemma":0.00018488265,"teacher_disagreement_score":0.7463455,"about_ca_system_score_codex":0.0000092598275,"about_ca_system_score_gemma":0.00003025344,"threshold_uncertainty_score":0.22675838},"labels":[],"label_agreement":null},{"id":"W2153935608","doi":"10.1139/cjc-2012-0409","title":"Kinetics of gene expression in bacteria — From models to measurements, and back again","year":2012,"lang":"en","type":"article","venue":"Canadian Journal of Chemistry","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Tekes; Academy of Finland","keywords":"Stochastic modelling; Gene expression; Computational biology; Stochastic dynamics; Stochastic process; Transcription (linguistics); Gene; Expression (computer science); Biological system; Statistical physics; Chemistry; Computer science; Biology; Genetics; Physics; Mathematics; Statistics","score_opus":0.021958080354155935,"score_gpt":0.21235510998258875,"score_spread":0.1903970296284328,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2153935608","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":[0.99535865,0.0035891288,0.00062742963,0.000040204217,0.000053461357,0.000029619676,0.000020085225,3.2584867e-7,0.00028110674],"genre_scores_gemma":[0.9952185,0.000038726892,0.0043216906,0.000051751056,0.0002608267,7.2795586e-7,0.00002001199,0.000012824091,0.0000749371],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99925166,0.000027923788,0.00029070504,0.00010833462,0.0001038374,0.00021754672],"domain_scores_gemma":[0.9990034,0.0000041985354,0.00014466522,0.00019215085,0.00010152855,0.00055401714],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014778768,0.000102158694,0.00018216895,0.000045236342,0.000012297971,0.00000948524,0.00015046555,0.00012039832,0.00009830842],"category_scores_gemma":[0.00003077716,0.00010389282,0.000057597914,0.000069409696,0.000033717504,0.000006655279,0.000020656864,0.00006472558,8.8430676e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016898593,0.000011290478,0.01793137,0.000010575785,0.000036950212,0.0000020359632,0.00009767018,0.0016531171,0.97920865,6.222818e-8,0.0008000437,0.00023132868],"study_design_scores_gemma":[0.00025892304,0.000020312587,0.0053001177,0.00005392956,0.000019721632,0.000012901292,0.00005902257,0.000016691996,0.99227893,0.000014546775,0.0018647029,0.00010018364],"about_ca_topic_score_codex":0.00016088395,"about_ca_topic_score_gemma":0.0005029889,"teacher_disagreement_score":0.01307029,"about_ca_system_score_codex":0.00004274256,"about_ca_system_score_gemma":0.00012186125,"threshold_uncertainty_score":0.4236626},"labels":[],"label_agreement":null},{"id":"W2154411047","doi":"10.1039/c1mb05094j","title":"Implementing an OR–NOT (ORN) logic gate with components of the SOS regulatory network of <i>Escherichia coli</i>","year":2011,"lang":"en","type":"article","venue":"Molecular BioSystems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"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":"Ministerio de Ciencia e Innovación; Petroleum Technology Research Centre","keywords":"Repressor lexA; Synthetic biology; Escherichia coli; Plasmid; Biology; Computational biology; SOS response; Computer science; Genetics; DNA; Gene","score_opus":0.020155575243022736,"score_gpt":0.2231818589156459,"score_spread":0.20302628367262315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154411047","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":[0.9972921,0.00055679696,0.0011361637,0.000014073747,0.000118440956,0.00042905795,0.000017177741,0.000013688203,0.00042249358],"genre_scores_gemma":[0.9981413,0.000013163492,0.0013472608,0.00016052443,0.00010372877,0.00002061742,0.000053210442,0.00005269651,0.00010751433],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9976805,0.00039413318,0.00059109007,0.00046368467,0.00036974187,0.00050086237],"domain_scores_gemma":[0.99783677,0.0000063839684,0.00062712235,0.0012063615,0.00021334861,0.000110024994],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062560703,0.00028165488,0.00042716626,0.000034070024,0.00012666208,0.000011619569,0.0005761741,0.00017101079,0.000024196199],"category_scores_gemma":[0.000012339055,0.00018926938,0.00023542996,0.00038836282,0.00019405485,0.000005434761,0.00027763768,0.00008909717,0.0000015400842],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028027373,0.00009452498,0.014152588,0.00009183228,0.000544096,0.0000069179755,0.00007368349,0.0012700091,0.983015,0.00027538373,0.000119742224,0.00007593799],"study_design_scores_gemma":[0.000711893,0.0005049876,0.017374255,0.00011665684,0.0002570756,0.000020293159,0.00015403156,0.0005226676,0.97819835,0.00003583976,0.0017687287,0.00033519827],"about_ca_topic_score_codex":0.00013288777,"about_ca_topic_score_gemma":0.00022654256,"teacher_disagreement_score":0.0048166374,"about_ca_system_score_codex":0.000016872202,"about_ca_system_score_gemma":0.00010356432,"threshold_uncertainty_score":0.7718181},"labels":[],"label_agreement":null},{"id":"W2154567872","doi":"10.1109/icbbe.2009.5163379","title":"Separable Parameter Estimation Method for Nonlinear Biological Systems","year":2009,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nonlinear system; Estimation theory; Applied mathematics; Mathematics; Separable space; Non-linear least squares; Linear model; Function (biology); Least-squares function approximation; Mathematical optimization; Control theory (sociology); Computer science; Algorithm; Statistics; Mathematical analysis; Artificial intelligence","score_opus":0.01981554309670836,"score_gpt":0.3090726177351744,"score_spread":0.28925707463846606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154567872","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":[0.13853973,0.00054696837,0.85999477,0.00013459443,0.00006792069,0.0002604982,0.000007980757,0.000024959549,0.00042260028],"genre_scores_gemma":[0.58602905,0.000031004365,0.4114967,0.00034285928,0.00024055546,0.000032585835,0.0002906686,0.000009117264,0.0015274318],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99919677,0.00006297532,0.00018479355,0.00029567824,0.00006228063,0.00019750159],"domain_scores_gemma":[0.99952805,0.00002735865,0.000057114856,0.00025982785,0.00006955594,0.00005808136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028790976,0.00011492081,0.00016468087,0.000027592552,0.00005548325,0.000026547348,0.000103840815,0.00016246285,0.000012059331],"category_scores_gemma":[0.00007195135,0.00008868147,0.00013856356,0.00007821906,0.00001480149,0.000001817277,0.000016552585,0.000028179396,0.000009327469],"study_design_candidate":"simulation_or_modeling","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":[0.00024738995,0.00025523512,0.0010154766,0.000032168384,0.00037621742,0.0000019423787,0.00001732329,0.23250166,0.67127985,0.0022411353,0.031387623,0.060643993],"study_design_scores_gemma":[0.0004225499,0.00059742335,0.00043603237,0.0000052210207,0.000066452456,0.000015661413,0.0000190991,0.8491231,0.09560571,0.00082013645,0.05261671,0.00027188347],"about_ca_topic_score_codex":0.0000046296486,"about_ca_topic_score_gemma":0.0000017548957,"teacher_disagreement_score":0.61662143,"about_ca_system_score_codex":0.000008377157,"about_ca_system_score_gemma":0.000018193135,"threshold_uncertainty_score":0.36163253},"labels":[],"label_agreement":null},{"id":"W2155131464","doi":"10.1186/1752-0509-3-72","title":"Cascading signaling pathways improve the fidelity of a stochastically and deterministically simulated molecular RS latch","year":2009,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"University of Toronto","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Heart and Stroke Foundation of Canada","keywords":"Crosstalk; Computer science; Fidelity; High fidelity; Systems biology; Biological system; Topology (electrical circuits); Electronic engineering; Biology; Bioinformatics; Engineering; Electrical engineering; Telecommunications","score_opus":0.012919113163575071,"score_gpt":0.25092129764782317,"score_spread":0.2380021844842481,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2155131464","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":[0.91461056,0.0019392107,0.08289153,0.000029975383,0.00010543814,0.0003028151,0.000020521002,0.000014666441,0.00008524913],"genre_scores_gemma":[0.998766,0.000015498634,0.00087452045,0.00010454557,0.00016267023,0.000008880766,0.000029122853,0.000015793867,0.00002293885],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9982264,0.00032042075,0.0005352706,0.0004731657,0.00010362824,0.00034111986],"domain_scores_gemma":[0.99889857,0.00010257752,0.00021864778,0.0005014772,0.00017310953,0.00010564363],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005851887,0.00021802344,0.0003913869,0.000046156096,0.00009126024,0.000022352542,0.00023711177,0.00030738526,0.0000026540697],"category_scores_gemma":[0.00028332838,0.0001594206,0.0001446638,0.00012251548,0.00019238335,0.0000021046328,0.00009923376,0.00009933869,0.0000016658579],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006865964,0.00002335673,0.0020726537,0.00003061147,0.000099805,0.0000039821666,0.000028287135,0.0066954573,0.98868006,0.0015719782,0.000011282464,0.000713835],"study_design_scores_gemma":[0.004903504,0.0072144526,0.023386898,0.00031576923,0.0013967328,0.00048493486,0.001087133,0.44914937,0.5018278,0.00468763,0.0028904984,0.002655313],"about_ca_topic_score_codex":0.000036010544,"about_ca_topic_score_gemma":0.000011271675,"teacher_disagreement_score":0.48685232,"about_ca_system_score_codex":0.000013569669,"about_ca_system_score_gemma":0.0000875468,"threshold_uncertainty_score":0.6500983},"labels":[],"label_agreement":null},{"id":"W2156302998","doi":"","title":"Scaling limits of spatial chemical reaction networks","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Scaling; Biological system; Reaction dynamics; Dynamics (music); Chemical reaction; Statistical physics; Spatial ecology; Scale (ratio); Molecular dynamics; Spatial configuration; Chemical species; Chemical physics; Molecule; Physics; Computer science; Chemistry; Distribution (mathematics); Mathematics; Computational chemistry; Ecology; Biology; Quantum mechanics; Geometry","score_opus":0.031386659938419034,"score_gpt":0.178312350023372,"score_spread":0.146925690084953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156302998","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":[0.9442846,0.00024826912,0.05457607,0.000010036209,0.0002657253,0.0001548145,0.0000063219536,0.000019962432,0.00043420304],"genre_scores_gemma":[0.9979874,0.00050685625,0.00014718666,0.000020729498,0.0005379133,0.0000010499284,0.0002642469,0.000030213681,0.0005044351],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986199,0.00008938532,0.00023038621,0.0007441684,0.000060300838,0.00025583044],"domain_scores_gemma":[0.9985663,0.000016113348,0.00032487826,0.0007778501,0.0001923604,0.00012244543],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012485121,0.00025903824,0.0003261363,0.000085714266,0.000044581964,0.000014053919,0.00039894032,0.0006793228,0.00002795993],"category_scores_gemma":[0.00003090211,0.00031150808,0.0003544074,0.00015331463,0.00012092416,0.000004138099,0.0005369713,0.00029752558,0.000011002621],"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":[0.00014040334,0.00011001985,0.006418339,0.00006923027,0.00060567923,0.000013451556,0.000014042323,0.8235058,0.16622081,0.0003345297,0.00068213884,0.0018855272],"study_design_scores_gemma":[0.0011709959,0.00014910474,0.0052484944,0.0001914956,0.0012158398,0.000010621734,0.000089503024,0.79671186,0.19018291,0.0018429805,0.0018026636,0.0013835055],"about_ca_topic_score_codex":0.00022941452,"about_ca_topic_score_gemma":0.00003848476,"teacher_disagreement_score":0.054428883,"about_ca_system_score_codex":0.00005323496,"about_ca_system_score_gemma":0.000080495214,"threshold_uncertainty_score":0.9999337},"labels":[],"label_agreement":null},{"id":"W2156553312","doi":"10.1093/bioinformatics/btp028","title":"Gene network reconstruction from transcriptional dynamics under kinetic model uncertainty: a case for the second derivative","year":2009,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"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 Ottawa","funders":"","keywords":"Computer science; ENCODE; Bayesian probability; Expression (computer science); Bayesian network; Gene; Gene regulatory network; Representation (politics); Transcription (linguistics); Computational biology; Gene expression; Theoretical computer science; Data mining; Algorithm; Biology; Artificial intelligence; Genetics","score_opus":0.013357795792574708,"score_gpt":0.2265834792411285,"score_spread":0.2132256834485538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156553312","genre_codex":"methods","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":[0.36767134,0.0006267772,0.6304889,0.0002926193,0.00015207575,0.00031995366,0.0002555591,0.000015475649,0.00017732392],"genre_scores_gemma":[0.93332154,0.000069625276,0.06393857,0.0010323172,0.00041752303,0.000027693153,0.0008572733,0.00001592328,0.00031951393],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99903846,0.000022926348,0.00037331504,0.00017840676,0.000115383606,0.00027151898],"domain_scores_gemma":[0.9992561,0.000036767804,0.00016111886,0.00035377458,0.000121528465,0.00007072684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015298385,0.00018991032,0.00016742038,0.000029010325,0.00024552908,0.00004670739,0.00015854377,0.00016725564,0.000026274138],"category_scores_gemma":[0.000013205883,0.00015121003,0.00018652774,0.00012365801,0.00008323311,0.000011201434,0.000023010445,0.00008125738,0.000002496291],"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":[0.00010049478,0.000025018951,0.00006224523,0.000014642957,0.000337953,0.0000019586614,0.0001684332,0.96515346,0.004599501,0.001039603,0.0025181333,0.025978547],"study_design_scores_gemma":[0.0004846176,0.000098789584,0.00025706756,0.000007885941,0.00014270662,0.00017848487,0.00035679663,0.9906154,0.001377099,0.0047967816,0.0014755228,0.00020879095],"about_ca_topic_score_codex":0.000008325633,"about_ca_topic_score_gemma":0.0004350932,"teacher_disagreement_score":0.5665503,"about_ca_system_score_codex":0.00005423914,"about_ca_system_score_gemma":0.000091009715,"threshold_uncertainty_score":0.6166166},"labels":[],"label_agreement":null},{"id":"W2156716434","doi":"10.3389/fcell.2014.00038","title":"Gene regulatory networks and their applications: understanding biological and medical problems in terms of networks","year":2014,"lang":"en","type":"review","venue":"Frontiers in Cell and Developmental Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":299,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto","funders":"Standortagentur Tirol","keywords":"Gene regulatory network; Inference; Computer science; Consistency (knowledge bases); Context (archaeology); Popularity; Data science; Perspective (graphical); Biological network; Artificial intelligence; Computational biology; Gene; Biology; Gene expression; Genetics; Psychology","score_opus":0.01937954923349737,"score_gpt":0.23981745086038608,"score_spread":0.2204379016268887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156716434","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018192994,0.9472901,0.050113194,0.0000055723503,0.00011079,0.0005009427,0.000007491661,0.0000046431005,0.00014796594],"genre_scores_gemma":[0.06086718,0.93684626,0.0015528975,0.000036560632,0.00010639242,0.0001102459,0.00043526845,0.00002345115,0.000021731383],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99781233,0.00028348202,0.00072925794,0.0007503213,0.00006013948,0.0003644682],"domain_scores_gemma":[0.9993272,0.00006871591,0.0002620018,0.00019287424,0.000009522399,0.00013967496],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006750947,0.00039785643,0.0012641042,0.0002122858,0.00006120745,0.000011186767,0.00020629556,0.0011782988,0.0000053107233],"category_scores_gemma":[0.00001674867,0.00029697453,0.00009782299,0.00022718981,0.00061973254,0.0000030651938,0.0003898506,0.00027508228,2.324583e-7],"study_design_candidate":"not_applicable","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":[0.00002939104,0.00007659371,0.048895936,0.0012440295,0.000281163,0.000003380147,0.000043002434,0.000082079474,0.00013465677,0.000073395444,0.00047393682,0.94866246],"study_design_scores_gemma":[0.004086874,0.0008459482,0.003095377,0.005693742,0.00043517686,0.00052181626,0.0007432615,0.0071398467,0.00030243918,0.005826008,0.9675287,0.0037807876],"about_ca_topic_score_codex":0.0000033600545,"about_ca_topic_score_gemma":0.000028591694,"teacher_disagreement_score":0.9670548,"about_ca_system_score_codex":0.00006879367,"about_ca_system_score_gemma":0.000072286064,"threshold_uncertainty_score":0.99994826},"labels":[],"label_agreement":null},{"id":"W2157281548","doi":"10.1109/memb.2009.932477","title":"Error detection and unit conversion","year":2009,"lang":"en","type":"article","venue":"IEEE Engineering in Medicine and Biology Magazine","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"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":"National Institute of Biomedical Imaging and Bioengineering; National Heart, Lung, and Blood Institute; U.S. Food and Drug Administration; University of Toronto; University of Oxford; National Institutes of Health; National Science Foundation","keywords":"Computer science; Biomedicine; Ode; Programming language; Bioinformatics; Applied mathematics; Mathematics","score_opus":0.01491471949119318,"score_gpt":0.25449458968750827,"score_spread":0.23957987019631508,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157281548","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":[0.9957919,0.0018114673,0.0018414197,0.00030511883,0.00010380433,0.000053500546,5.7057656e-7,0.000012505372,0.00007970113],"genre_scores_gemma":[0.9985927,0.00069874496,0.00013556403,0.00019405014,0.0002508943,0.0000020367825,0.000021035967,0.0000057683087,0.00009923348],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99947894,0.000021711308,0.0001260117,0.00020456196,0.00002619263,0.00014258153],"domain_scores_gemma":[0.9997866,0.000011743955,0.00002454348,0.00010502299,0.000017499146,0.000054604385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016108234,0.00010917562,0.00015577029,0.000107407,0.000020465755,0.0000020940754,0.00003983698,0.00014077712,0.000005487955],"category_scores_gemma":[0.000037186426,0.000090689435,0.000014019529,0.00011017395,0.0000600638,0.000002087192,0.000013986497,0.000087508706,0.0000013431833],"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":[0.000026981092,0.0000078105895,0.007136353,0.000011651634,0.000018675491,0.000002932134,0.000018112398,0.0006188366,0.9869587,0.000014078317,0.0002994381,0.004886466],"study_design_scores_gemma":[0.0073706065,0.0060356185,0.63005763,0.00018510137,0.00023419122,0.0003244614,0.00012929605,0.05851157,0.13891529,0.00021453248,0.15691754,0.0011041623],"about_ca_topic_score_codex":0.000005869074,"about_ca_topic_score_gemma":0.0000142624185,"teacher_disagreement_score":0.8480434,"about_ca_system_score_codex":0.0000044636226,"about_ca_system_score_gemma":0.0000046037803,"threshold_uncertainty_score":0.36982077},"labels":[],"label_agreement":null},{"id":"W2158195391","doi":"10.1142/s0218127411028398","title":"STRUCTURAL PRINCIPLES FOR COMPLEX DYNAMICS IN GLASS NETWORKS","year":2011,"lang":"en","type":"article","venue":"International Journal of Bifurcation and Chaos","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"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 Victoria","funders":"","keywords":"Sequence (biology); Complex network; Diagram; Computer science; Complex dynamics; State (computer science); State diagram; Convergence (economics); Statistical physics; Dynamics (music); Simple (philosophy); Piecewise linear function; Topology (electrical circuits); Mathematics; Physics; Algorithm; Combinatorics","score_opus":0.030604121832869886,"score_gpt":0.26985334354635854,"score_spread":0.23924922171348864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158195391","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":[0.9765687,0.00027596747,0.02235691,0.00024821635,0.00026393504,0.00006416464,0.000006469771,0.0000016167543,0.0002140183],"genre_scores_gemma":[0.99722475,0.0001421998,0.0020527851,0.00011029007,0.0003143445,0.0000028912766,0.00006128236,0.000006789402,0.000084667845],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994424,0.000020166266,0.0002716046,0.00008973206,0.000101048085,0.00007505041],"domain_scores_gemma":[0.99940926,0.000007442854,0.00022102377,0.000063311476,0.00026000087,0.000038951865],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015448283,0.00006423347,0.000089540685,0.00008835711,0.000019572286,0.000014867781,0.00016297186,0.00005510908,0.000014413739],"category_scores_gemma":[0.000025427255,0.00005825339,0.000067953675,0.00003718357,0.00003210845,0.000006864954,0.000034002922,0.000043745076,2.0873273e-7],"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":[0.0020316285,0.00031228652,0.8105744,0.000038436232,0.0015521758,0.000022156628,0.0009703166,0.030643692,0.031907566,0.022908432,0.0015546418,0.09748427],"study_design_scores_gemma":[0.0024156636,0.00035992937,0.4821196,0.0000440873,0.00006491725,0.00021107071,0.000567389,0.4984828,0.0048247464,0.0013727597,0.0092414245,0.0002956454],"about_ca_topic_score_codex":0.00000748033,"about_ca_topic_score_gemma":0.00018159761,"teacher_disagreement_score":0.4678391,"about_ca_system_score_codex":0.00003855173,"about_ca_system_score_gemma":0.000027433149,"threshold_uncertainty_score":0.23755042},"labels":[],"label_agreement":null},{"id":"W2158536518","doi":"10.1109/bibm.2010.5706586","title":"Structure identification and parameter estimation of biological s-systems","year":2010,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Pruning; Nonlinear system; Computer science; Algorithm; System identification; Estimation theory; Nonlinear system identification; Identification (biology); Regularization (linguistics); Mathematics; Artificial intelligence; Mathematical optimization; Data mining; Measure (data warehouse)","score_opus":0.008523512464004186,"score_gpt":0.23944910478250078,"score_spread":0.2309255923184966,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158536518","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":[0.99178034,0.00012118436,0.00788929,0.000019933259,0.00008068426,0.000061514686,0.000004744441,0.000004193761,0.00003811493],"genre_scores_gemma":[0.9973879,0.000013577553,0.0023147834,0.000009746476,0.0000533402,0.0000029010343,0.000079936035,0.0000035715698,0.00013423974],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995929,0.000021961316,0.00013305467,0.00014939536,0.00004537252,0.00005729677],"domain_scores_gemma":[0.9996691,0.0000066718144,0.00006554124,0.00019195216,0.000040904728,0.00002587577],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000084732885,0.000053097297,0.00007277158,0.00002026286,0.000019705414,0.000012220976,0.00005170052,0.00012322198,0.000018880753],"category_scores_gemma":[0.00004701984,0.00004016328,0.000026320327,0.000041432777,0.00005806247,0.0000014249711,0.000025236812,0.000032930413,9.509858e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000043408827,0.0000055810797,0.008327219,0.000004507433,0.000020188543,4.2407702e-8,0.0000040702894,0.0008424055,0.98766446,0.00031987153,0.00012856426,0.0026787627],"study_design_scores_gemma":[0.00016022309,0.00006775478,0.08666196,0.0000019129234,0.000031833923,0.0000157961,0.000025713409,0.025584651,0.8856074,0.00063139724,0.0010802399,0.00013111182],"about_ca_topic_score_codex":0.000006321753,"about_ca_topic_score_gemma":0.0000140147495,"teacher_disagreement_score":0.10205704,"about_ca_system_score_codex":9.263334e-7,"about_ca_system_score_gemma":0.000006449574,"threshold_uncertainty_score":0.1637811},"labels":[],"label_agreement":null},{"id":"W2159389525","doi":"10.1109/bibm.2009.80","title":"Qualitative Motif Detection in Gene Regulatory Networks","year":2009,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"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 Windsor","funders":"","keywords":"Dynamic Bayesian network; ENCODE; Bayesian network; Computer science; Gene regulatory network; Probabilistic logic; Bayesian probability; Artificial intelligence; Machine learning; Data mining; Computational biology; Gene; Gene expression; Biology; Genetics","score_opus":0.009974400700667648,"score_gpt":0.27547320928579594,"score_spread":0.2654988085851283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159389525","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":[0.9579382,0.00082772877,0.039945364,0.00007974114,0.00006143193,0.00009595752,5.568601e-7,0.000018646027,0.0010323689],"genre_scores_gemma":[0.997606,0.00007333429,0.0008635823,0.00027930082,0.00022853653,0.000006405557,0.000034694363,0.000011920165,0.0008962406],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989291,0.00015651669,0.00022577909,0.00033920736,0.00010571607,0.00024368678],"domain_scores_gemma":[0.9994694,0.0000074223053,0.000060825667,0.00034597353,0.00004912932,0.00006726903],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035378465,0.00013764716,0.00014677805,0.000075820004,0.0000441481,0.000011926081,0.0001099884,0.0001722486,0.00002176009],"category_scores_gemma":[0.00002073079,0.00013660423,0.00010446663,0.00024392587,0.000035037585,0.00000303534,0.000027347669,0.00007697331,0.000006956393],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009370922,0.00009952191,0.00064972107,0.000002250511,0.00007307449,0.0000047940566,0.00027679114,0.046700314,0.8979457,0.00017451898,0.0009136411,0.05306595],"study_design_scores_gemma":[0.0007976549,0.00040236616,0.06638936,0.000009594208,0.000039564053,0.000014394069,0.00058536,0.020005966,0.90922713,0.00084408035,0.001179202,0.0005053063],"about_ca_topic_score_codex":0.000012645451,"about_ca_topic_score_gemma":0.00015025,"teacher_disagreement_score":0.06573964,"about_ca_system_score_codex":0.000028527196,"about_ca_system_score_gemma":0.000018007804,"threshold_uncertainty_score":0.5570559},"labels":[],"label_agreement":null},{"id":"W2159739447","doi":"10.1093/bioinformatics/btv341","title":"JSBML 1.0: providing a smorgasbord of options to encode systems biology models","year":2015,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":42,"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":"National Institute of Allergy and Infectious Diseases; Biotechnology and Biological Sciences Research Council; Seventh Framework Programme; Danmarks Tekniske Universitet; National Institute of General Medical Sciences; Novo Nordisk; Bundesministerium für Bildung und Forschung; European Commission; Deutsche Forschungsgemeinschaft; Novo Nordisk Fonden; National Science Foundation; Google; National Institutes of Health","keywords":"ENCODE; Computer science; Computational biology; Systems biology; Biology; Data science; Genetics; Gene","score_opus":0.034921473298470486,"score_gpt":0.2662321145306797,"score_spread":0.2313106412322092,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159739447","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":[0.66432583,0.0014898892,0.32857257,0.00010846702,0.00037488865,0.0005908896,0.00007417381,0.000040913164,0.004422385],"genre_scores_gemma":[0.97562087,0.000055375916,0.023738965,0.000074073796,0.00010561054,0.000027790556,0.00011115159,0.000015577767,0.00025061038],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998987,0.000042257485,0.00045128667,0.000141012,0.00013749489,0.00024090939],"domain_scores_gemma":[0.99893147,0.0000072593593,0.00017549662,0.0004575203,0.00023571283,0.0001925666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033244738,0.0001403809,0.00023010606,0.00011469974,0.000039936327,0.00001945255,0.00024253072,0.00014604702,0.0000017805905],"category_scores_gemma":[0.00007212662,0.00012748303,0.00008728563,0.00023109461,0.00004887586,0.000009468577,0.00016364305,0.000033208733,0.000020465413],"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":[0.000111044734,0.000141973,0.0038733613,0.0002607653,0.000514836,0.0000012578773,0.0017466666,0.8491206,0.1121288,0.008363136,0.02010082,0.0036367115],"study_design_scores_gemma":[0.0014813764,0.0012570249,0.00018148783,0.00010343661,0.00025151874,0.000053556396,0.003408398,0.8794369,0.045816567,0.0009738862,0.06607674,0.00095911755],"about_ca_topic_score_codex":0.00003414459,"about_ca_topic_score_gemma":0.000013622758,"teacher_disagreement_score":0.31129503,"about_ca_system_score_codex":0.000030168057,"about_ca_system_score_gemma":0.00016186733,"threshold_uncertainty_score":0.5198607},"labels":[],"label_agreement":null},{"id":"W2160420612","doi":"10.1016/j.jtbi.2009.12.005","title":"Cycling expression and cooperative operator interaction in the trp operon of Escherichia coli","year":2009,"lang":"en","type":"article","venue":"Journal of Theoretical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Consejo Nacional de Ciencia y Tecnología","keywords":"trp operon; Operon; Escherichia coli; Cooperativity; Repressor; L-arabinose operon; Biology; Tryptophan; Genetics; Operator (biology); lac operon; Mutant; Gene; Gene expression; Amino acid","score_opus":0.007429065909562696,"score_gpt":0.27845662310568925,"score_spread":0.27102755719612653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160420612","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":[0.9970454,0.0008722485,0.0011488465,0.0006253468,0.0000639901,0.000059164417,0.000001220534,6.8717276e-7,0.00018309892],"genre_scores_gemma":[0.9985527,0.00029951095,0.0006380672,0.00034544093,0.00015094137,9.808688e-7,0.000003990708,0.0000038506355,0.0000045452457],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989339,0.00042365145,0.00034973474,0.00011805439,0.000061577746,0.00011309396],"domain_scores_gemma":[0.9995168,0.000059186434,0.00016198211,0.00012192432,0.00009922555,0.00004091192],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060699484,0.00008905018,0.0002243068,0.00004817258,0.000030470448,0.000010479816,0.00016716176,0.00012916989,0.000021777723],"category_scores_gemma":[0.00020129696,0.000051233463,0.00007657651,0.00008504552,0.00022570952,0.000005001987,0.00003523064,0.00013092547,3.8078053e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002958559,0.00006959752,0.0009897334,0.0000020480807,0.000028005827,0.0000022499717,0.00011250473,0.00029799438,0.9912354,0.0057743937,0.000088098226,0.0011041283],"study_design_scores_gemma":[0.0010764555,0.0029932214,0.005226584,0.00006901946,0.000074744006,0.00009020375,0.00081099576,0.0007552921,0.98356956,0.0040492592,0.0011237323,0.0001609377],"about_ca_topic_score_codex":8.007018e-7,"about_ca_topic_score_gemma":0.000001420236,"teacher_disagreement_score":0.0076658353,"about_ca_system_score_codex":0.000008347127,"about_ca_system_score_gemma":0.000028703951,"threshold_uncertainty_score":0.208924},"labels":[],"label_agreement":null},{"id":"W2160845585","doi":"10.1038/msb.2009.83","title":"Strategies for cellular decision‐making","year":2009,"lang":"en","type":"review","venue":"Molecular Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":338,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ottawa Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Ottawa Hospital Research Institute","keywords":"Biology; Probabilistic logic; Context (archaeology); Computational biology; Computer science; Risk analysis (engineering); Artificial intelligence; Business","score_opus":0.022662960022535025,"score_gpt":0.32107412236699423,"score_spread":0.2984111623444592,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160845585","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000048957612,0.7723004,0.22549622,0.0000033580627,0.00058515277,0.0011406731,0.00007006234,0.00003151999,0.0003236197],"genre_scores_gemma":[0.00503692,0.98935497,0.0019914196,0.00006873048,0.0010413696,0.0004999123,0.001616278,0.00016229489,0.00022808238],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9961087,0.00055217923,0.0011105476,0.0013255024,0.00016225257,0.0007407943],"domain_scores_gemma":[0.99752086,0.00007490151,0.000690832,0.0013941865,0.00018856111,0.00013067137],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00057800824,0.0008343736,0.002231355,0.00028797265,0.000140427,0.00012535938,0.0008598428,0.0015815768,0.000007461234],"category_scores_gemma":[0.000081790546,0.0007172969,0.0015831308,0.0003134339,0.00010991274,0.000003207155,0.00019656049,0.00021501932,0.000032668828],"study_design_candidate":"not_applicable","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":[0.00002814491,0.00005679499,0.0000025876827,0.0042168656,0.0015813744,0.000037615846,0.0000065712356,0.00071878004,0.0038679852,0.0045030643,0.004359259,0.980621],"study_design_scores_gemma":[0.00019283428,0.00029653485,1.6168775e-7,0.0019092364,0.0009547898,0.00008229839,0.00001876418,0.000117814336,0.00007467556,0.0004405742,0.99518174,0.00073059194],"about_ca_topic_score_codex":0.000006134652,"about_ca_topic_score_gemma":0.000007664175,"teacher_disagreement_score":0.9908225,"about_ca_system_score_codex":0.00006827058,"about_ca_system_score_gemma":0.00051816803,"threshold_uncertainty_score":0.99971455},"labels":[],"label_agreement":null},{"id":"W2161406501","doi":"10.1016/j.jmb.2004.09.073","title":"Efficient Attenuation of Stochasticity in Gene Expression Through Post-transcriptional Control","year":2004,"lang":"en","type":"article","venue":"Journal of Molecular Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":228,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; McGill University Health Centre","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Gene expression; Biology; Operon; In silico; Gene; Ribosome; Gene regulatory network; Messenger RNA; Translational efficiency; Regulation of gene expression; Ribosomal binding site; Computational biology; Translation (biology); Genetics; RNA","score_opus":0.0064762599792396935,"score_gpt":0.24982944906334495,"score_spread":0.24335318908410525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161406501","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":[0.6136171,0.0016072795,0.3844495,0.00016646786,0.00007614072,0.00006415463,0.000008965967,9.423474e-7,0.0000094210045],"genre_scores_gemma":[0.99307185,0.0000410061,0.0065241284,0.00020060915,0.0001144986,0.0000028595925,0.000031066033,0.000011595115,0.0000023550326],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99875546,0.00016306997,0.00054111093,0.00018722344,0.00016871886,0.00018443627],"domain_scores_gemma":[0.99898076,0.000011970708,0.00040156228,0.00017698105,0.00037554392,0.000053180665],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035192136,0.00013085389,0.00029952594,0.000120366625,0.000023869552,0.000003750707,0.00017970933,0.00019090314,0.00000910393],"category_scores_gemma":[0.00011334155,0.00011301131,0.00024100818,0.00012536261,0.00010359171,0.0000028023892,0.000030449124,0.00011949953,0.0000010535003],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019172493,0.00010651998,0.0010350916,0.0000042822035,0.000066998415,0.000008201628,0.00003211558,0.32431093,0.67399216,0.0001793715,0.0000036526208,0.00006893121],"study_design_scores_gemma":[0.002869574,0.0008240293,0.0070095668,0.000038745708,0.00007648394,0.00009326989,0.00003862449,0.00030715056,0.98798746,0.0005180349,0.00010147218,0.0001356005],"about_ca_topic_score_codex":0.000013726689,"about_ca_topic_score_gemma":0.000008452559,"teacher_disagreement_score":0.37945476,"about_ca_system_score_codex":0.000038291168,"about_ca_system_score_gemma":0.00015239793,"threshold_uncertainty_score":0.46084675},"labels":[],"label_agreement":null},{"id":"W2161977175","doi":"10.1016/j.copbio.2008.06.011","title":"The stochastic nature of biochemical networks","year":2008,"lang":"en","type":"review","venue":"Current Opinion in Biotechnology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":220,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Center for Research Resources; National Institute of General Medical Sciences; National Institutes of Health","keywords":"Biology; Stochastic modelling; Computational biology; Gene; Phenotype; Gene regulatory network; Gene expression; Genetics; Mathematics","score_opus":0.024099974516973547,"score_gpt":0.3293104388493081,"score_spread":0.30521046433233456,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161977175","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000037694706,0.99561507,0.0012380265,0.000055883098,0.0025842162,0.00042437267,0.000017657487,0.000021349711,0.000005756188],"genre_scores_gemma":[0.00048267565,0.99812496,0.00004254376,0.000002968139,0.0006664743,0.000096615324,0.000521589,0.0000473138,0.000014846041],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977232,0.00016332489,0.0008104215,0.00068289804,0.0001614756,0.00045864776],"domain_scores_gemma":[0.9981488,0.00007282333,0.00053158693,0.001127915,0.000063301326,0.000055553337],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00017295951,0.00044687392,0.0010338377,0.0002657247,0.000089820845,0.0000083368095,0.001000819,0.0028974728,0.0000027264841],"category_scores_gemma":[0.00016882157,0.00032391297,0.0005868003,0.0007902117,0.00063221704,0.000001159731,0.0005360842,0.0013572918,0.000005785792],"study_design_candidate":"not_applicable","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":[0.000014363818,0.00008989592,0.000007879795,0.0013904447,0.0002389711,5.286412e-7,0.0000020071084,0.00025755694,0.000032015454,0.00055349135,0.018635228,0.9787776],"study_design_scores_gemma":[0.0001337038,0.000057872396,0.0000026279822,0.0018899135,0.000068584064,0.000066760695,0.0000036061933,0.00016003597,0.00006262055,0.000029130542,0.9972324,0.00029274492],"about_ca_topic_score_codex":0.0000010390746,"about_ca_topic_score_gemma":0.0000019423715,"teacher_disagreement_score":0.97859716,"about_ca_system_score_codex":0.000050490118,"about_ca_system_score_gemma":0.00020865248,"threshold_uncertainty_score":0.9999213},"labels":[],"label_agreement":null},{"id":"W2161993753","doi":"10.1016/j.laa.2004.04.005","title":"On matrices with common invariant cones with applications in neural and gene networks","year":2004,"lang":"en","type":"article","venue":"Linear Algebra and its Applications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Invariant (physics); Mathematics; Linear subspace; Eigenvalues and eigenvectors; Multilinear map; Pure mathematics; Topology (electrical circuits); Discrete mathematics; Combinatorics; Physics","score_opus":0.0051005745601671,"score_gpt":0.21654431957752301,"score_spread":0.2114437450173559,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161993753","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":[0.972266,0.0030571844,0.023705972,0.0003013741,0.0000031453205,0.0005428636,0.000011272687,0.000015238119,0.00009694833],"genre_scores_gemma":[0.9973134,0.0005697747,0.0012880071,0.00018100603,0.00009937115,0.00031250415,0.00017639449,0.00001913528,0.000040422266],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99928385,0.000017396,0.00013950303,0.00033726514,0.00006895517,0.00015304612],"domain_scores_gemma":[0.99952614,0.000017948178,0.00006705245,0.0002632155,0.000040043422,0.00008558559],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000049964718,0.00014140535,0.00014115851,0.000052050458,0.00013724282,0.000025314876,0.000091055714,0.00008045477,0.0000021627407],"category_scores_gemma":[0.0000017504963,0.00010793751,0.000017853567,0.00027055695,0.00007648075,0.0000053530903,0.000041505264,0.000081740625,0.0000019012721],"study_design_candidate":"simulation_or_modeling","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":[0.00085789687,0.0017217787,0.10242254,0.00023007726,0.0009873243,0.000020454574,0.0004813012,0.6171622,0.07400202,0.18130395,0.00025078357,0.020559656],"study_design_scores_gemma":[0.027958715,0.00836808,0.43600398,0.00045442654,0.0027688534,0.0010914706,0.0019538002,0.22258523,0.19881319,0.016110642,0.075705215,0.008186405],"about_ca_topic_score_codex":0.000021246955,"about_ca_topic_score_gemma":0.00023389565,"teacher_disagreement_score":0.394577,"about_ca_system_score_codex":0.0000069124776,"about_ca_system_score_gemma":0.000025178528,"threshold_uncertainty_score":0.44015637},"labels":[],"label_agreement":null},{"id":"W2163904845","doi":"10.1109/cec.2011.5949893","title":"Hierarchical self-organized learning in agent-based modeling of the MAPK signaling pathway","year":2011,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"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 Calgary","funders":"","keywords":"Computer science; Multi-agent system; Distributed computing; Self-organization; Order (exchange); Artificial intelligence","score_opus":0.014316442023658045,"score_gpt":0.20349441764443657,"score_spread":0.18917797562077854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163904845","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":[0.98708373,0.00013516699,0.01166973,0.000025277537,0.000030615778,0.0000842052,5.09153e-7,0.000016298261,0.0009544356],"genre_scores_gemma":[0.9952741,0.0000069165517,0.0043851133,0.00007972785,0.000040242612,0.000004749127,0.000009140983,0.000019709943,0.00018029795],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99900347,0.00016761948,0.00025860444,0.00024245998,0.00013052931,0.00019731816],"domain_scores_gemma":[0.9995213,0.000008432374,0.00007329877,0.0002966359,0.00005545437,0.000044840053],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029265898,0.000114199436,0.00015153091,0.00004901755,0.00005398375,0.0000051743527,0.00022263186,0.00011571336,0.00007536366],"category_scores_gemma":[0.000037920123,0.00008523864,0.00014988918,0.00020755742,0.000032569114,0.0000013896774,0.000103733364,0.00013016617,0.0000027544775],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005203883,0.0001035644,0.02866668,0.000016432394,0.00008137228,0.000001883356,0.00020069578,0.1699814,0.8004205,0.000082881175,0.000013710018,0.00037880192],"study_design_scores_gemma":[0.00050786417,0.000058941787,0.0008376132,0.000014926401,0.000033254077,0.0000013296019,0.000110539244,0.2009569,0.7970764,0.00008124215,0.00017238063,0.00014862308],"about_ca_topic_score_codex":0.000036783742,"about_ca_topic_score_gemma":0.00004669749,"teacher_disagreement_score":0.030975487,"about_ca_system_score_codex":0.000012173506,"about_ca_system_score_gemma":0.00010351203,"threshold_uncertainty_score":0.34759307},"labels":[],"label_agreement":null},{"id":"W2164915726","doi":"10.1093/nar/gkq844","title":"Gene expression variations are predictive for stochastic noise","year":2010,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Biology; Gene expression; Genetics; Evolvability; Phenotype; Gene; Regulation of gene expression; Computational biology; Chromatin; Noise (video); Computer science","score_opus":0.022818280965678447,"score_gpt":0.31607059244339636,"score_spread":0.2932523114777179,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2164915726","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":[0.92088175,0.00015943754,0.07744542,0.00026638253,0.00018724121,0.0005654793,0.00008239137,0.00002376983,0.00038812726],"genre_scores_gemma":[0.9914934,0.000015611071,0.005947862,0.000029129596,0.00091630867,0.00022779808,0.00014644298,0.000042008884,0.0011814504],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983701,0.000115572104,0.00017597631,0.000490546,0.00039043635,0.0004573707],"domain_scores_gemma":[0.99841297,0.00006596334,0.000063098785,0.0006943098,0.0005786966,0.0001849596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007315553,0.00013170214,0.00014458044,0.00013546695,0.000388364,0.00004580871,0.00037688643,0.00026803455,0.000098241784],"category_scores_gemma":[0.0005436968,0.00012380454,0.00012581848,0.00025489568,0.00017267754,0.0000056383888,0.00024453874,0.00031013158,0.000032913515],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011805158,0.000077921155,0.0014205754,0.000009645696,0.0000604211,8.139141e-7,0.00004884193,0.001109929,0.98880106,0.00006598658,0.007397254,0.0008894695],"study_design_scores_gemma":[0.0016793273,0.00072667765,0.026598472,0.000034113706,0.00009172,0.000015690626,0.00030773538,0.02857793,0.9148577,0.0017682109,0.024826154,0.0005162817],"about_ca_topic_score_codex":0.000005814955,"about_ca_topic_score_gemma":0.000032828084,"teacher_disagreement_score":0.07394341,"about_ca_system_score_codex":0.000023715713,"about_ca_system_score_gemma":0.0001359389,"threshold_uncertainty_score":0.5048603},"labels":[],"label_agreement":null},{"id":"W2165187344","doi":"10.1073/pnas.1201103109","title":"Stochastic branching-diffusion models for gene expression","year":2012,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Covariance; Statistical physics; Diffusion; Biology; Poisson distribution; Gene expression; Physics; Biological system; Biophysics; Gene; Mathematics; Genetics; Statistics","score_opus":0.03141029762408582,"score_gpt":0.28924168637192016,"score_spread":0.25783138874783434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165187344","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":[0.9977226,0.00062696065,0.0009630399,0.00021047663,0.000019381981,0.00013933894,0.000007756868,0.0000027714034,0.00030766815],"genre_scores_gemma":[0.9948529,0.000015298232,0.004698807,0.00008217008,0.00023217012,0.000012758041,6.5028837e-7,0.000004418026,0.000100857294],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990736,0.000004176954,0.00017738003,0.00016318249,0.00043402603,0.00014761263],"domain_scores_gemma":[0.9995433,0.00001883407,0.00023953078,0.000009178095,0.00015328184,0.000035888566],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00076528685,0.00007011706,0.00009297598,0.000057247416,0.00015073818,0.0000065821246,0.00038182613,0.000081580074,0.0000021717124],"category_scores_gemma":[0.00013818388,0.000047122143,0.00009994062,0.00018999136,0.00020641586,0.000025848109,0.00013393968,0.000039574352,1.7500612e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014342738,0.000026573562,0.0009437415,0.000014935254,0.000010065739,5.99453e-11,0.000040194755,0.008178447,0.9885362,0.0016537313,0.0004627874,0.000118995886],"study_design_scores_gemma":[0.00013234495,0.000028858423,0.0030215883,0.000024643332,0.000017597691,0.0000021446258,0.00003385681,0.010395564,0.9759535,0.01021114,0.00011251621,0.000066210465],"about_ca_topic_score_codex":5.113474e-7,"about_ca_topic_score_gemma":1.2819499e-8,"teacher_disagreement_score":0.01258265,"about_ca_system_score_codex":0.000008021065,"about_ca_system_score_gemma":0.000014024916,"threshold_uncertainty_score":0.19215852},"labels":[],"label_agreement":null},{"id":"W2165247488","doi":"10.1101/gr.097378.109","title":"Gene regulatory networks and the role of robustness and stochasticity in the control of gene expression","year":2011,"lang":"en","type":"article","venue":"Genome Research","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":382,"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":"National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of General Medical Sciences; Canadian Institutes of Health Research","keywords":"Biology; Gene regulatory network; Gene; Robustness (evolution); Gene expression; Regulation of gene expression; Computational biology; Genetics; Phenotype; Systems biology; Gene expression profiling; Regulator gene","score_opus":0.021159220429424717,"score_gpt":0.2580567786374276,"score_spread":0.23689755820800287,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165247488","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":[0.96530366,0.021882368,0.012279503,0.000028320972,0.000008733406,0.00034648046,0.000005479893,0.0000013069765,0.00014412076],"genre_scores_gemma":[0.9988988,0.0006096226,0.00031858968,0.000011457469,0.00008495516,0.000037243044,0.0000074147824,0.000011425605,0.000020486861],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9982568,0.00068355154,0.000245136,0.00025813925,0.00028043485,0.00027591726],"domain_scores_gemma":[0.99908084,0.00009323004,0.00008898589,0.0005249973,0.00015901445,0.000052955198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026313665,0.00010001881,0.0002256915,0.000080361264,0.00009985494,0.00000906478,0.00032195958,0.00012161607,0.000008590136],"category_scores_gemma":[0.000057544803,0.00006058287,0.000057233145,0.0002082224,0.00075609563,0.0000029499554,0.00018906589,0.00016180649,1.6162048e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007542638,0.000072359835,0.0076435492,0.000021684275,0.00009910245,0.000001963761,0.000650346,0.018352639,0.9697375,0.00017207595,0.000014773868,0.002479721],"study_design_scores_gemma":[0.0047935415,0.000547433,0.22151817,0.000050021714,0.00013799487,0.000040859748,0.002477593,0.049576882,0.7194144,0.0008715109,0.00022518128,0.00034638584],"about_ca_topic_score_codex":0.0000645125,"about_ca_topic_score_gemma":0.000026750891,"teacher_disagreement_score":0.2503231,"about_ca_system_score_codex":0.000006624651,"about_ca_system_score_gemma":0.00004066661,"threshold_uncertainty_score":0.2785866},"labels":[],"label_agreement":null},{"id":"W2166860637","doi":"10.1073/pnas.022642299","title":"Synchronizing genetic relaxation oscillators by intercell signaling","year":2002,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":284,"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; Advanced Research Projects Agency; Office of Naval Research; Fetzer Institute; National Science Foundation","keywords":"Synthetic biology; Quorum sensing; Synchronizing; Synchronization (alternating current); Context (archaeology); Population; Mechanism (biology); Biology; Gene regulatory network; SIGNAL (programming language); Computational biology; Computer science; Gene; Biological system; Genetics; Physics; Gene expression; Computer network; Telecommunications; Channel (broadcasting)","score_opus":0.021191823959818556,"score_gpt":0.24884011301772627,"score_spread":0.2276482890579077,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2166860637","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":[0.99682206,0.0012596333,0.000013090936,0.0003695436,0.000011908959,0.00006661295,0.0000031810982,0.000003655498,0.0014503165],"genre_scores_gemma":[0.9983331,0.0001084661,0.0010714175,0.00010812322,0.00008990822,0.0000030588283,2.69971e-7,0.000004841126,0.00028084143],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988565,0.0000075468756,0.000251972,0.00023330863,0.00052803144,0.0001226269],"domain_scores_gemma":[0.9994561,0.000013869688,0.00034286518,0.000009934482,0.00014989523,0.00002731774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045648956,0.00007986122,0.00009507114,0.0000700559,0.00014372663,0.0000147923865,0.00044670503,0.000087974775,0.000021416521],"category_scores_gemma":[0.00014761821,0.000060404338,0.000088188586,0.0004037607,0.00034475458,0.000013555048,0.00010374875,0.00006362781,0.0000014627299],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020204654,0.00001417949,0.006792151,0.0000141058135,0.000020028996,9.506088e-10,0.000036135356,0.001417705,0.98822093,0.00017987778,0.0028971904,0.00040567628],"study_design_scores_gemma":[0.00009457544,0.000048469963,0.0046674237,0.000034300443,0.000021527203,0.0000044847748,0.00006624148,0.00817912,0.98471725,0.001100939,0.00097174617,0.000093944356],"about_ca_topic_score_codex":0.0000015142922,"about_ca_topic_score_gemma":3.532808e-8,"teacher_disagreement_score":0.006761415,"about_ca_system_score_codex":0.000019389852,"about_ca_system_score_gemma":0.000008375703,"threshold_uncertainty_score":0.24632174},"labels":[],"label_agreement":null},{"id":"W2166927587","doi":"10.1002/9780470686263.ch1","title":"Quantitative Modeling in Toxicology: An Introduction","year":2010,"lang":"en","type":"other","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Université de Montréal","funders":"","keywords":"Computer science; Data science","score_opus":0.016394144841131945,"score_gpt":0.2737328648620033,"score_spread":0.2573387200208714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2166927587","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4435409,0.0094289,0.06841176,0.0015257631,0.0031470766,0.0014056333,0.000050100356,0.00031315675,0.4721767],"genre_scores_gemma":[0.13624747,0.0009286802,0.025814494,0.0001925866,0.005286547,0.00005790143,0.0016689359,0.0007152857,0.8290881],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99902654,0.000072727824,0.00014969926,0.00050556666,0.00006967006,0.00017577493],"domain_scores_gemma":[0.99937236,0.000001427012,0.00007270758,0.00047215042,0.000032377855,0.00004899479],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014978713,0.00017989881,0.00020651556,0.00020876003,0.000015789343,0.000010506345,0.00014906903,0.0006499409,0.0006282429],"category_scores_gemma":[0.000023988907,0.00017437863,0.00006889354,0.00012762898,0.000042538217,0.000001238136,0.000051353196,0.0001737337,0.000018829383],"study_design_candidate":"not_applicable","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":[0.000119468,0.00030693653,0.00047688204,0.00005567247,0.00046829245,0.000008916567,0.00006327506,0.028447645,0.5579743,0.0021850872,0.40396988,0.0059236754],"study_design_scores_gemma":[0.0007406178,0.0006541581,0.000044621585,0.0000347735,0.00013833876,0.000019491483,0.000248903,0.10485712,0.013647019,0.0003667192,0.8780727,0.0011755901],"about_ca_topic_score_codex":0.000090211564,"about_ca_topic_score_gemma":0.012993174,"teacher_disagreement_score":0.54432726,"about_ca_system_score_codex":0.000009932266,"about_ca_system_score_gemma":0.00004260233,"threshold_uncertainty_score":0.7250496},"labels":[],"label_agreement":null},{"id":"W2167218823","doi":"10.1103/physreve.80.061920","title":"Pitchfork and Hopf bifurcation thresholds in stochastic equations with delayed feedback","year":2009,"lang":"en","type":"article","venue":"Physical Review E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Bifurcation diagram; Mathematics; Pitchfork bifurcation; Infinite-period bifurcation; Hopf bifurcation; Saddle-node bifurcation; Transcritical bifurcation; Multiplicative function; Mathematical analysis; Bifurcation theory; Parameter space; Bifurcation; Multiplicative noise; Limit (mathematics); Statistical physics; Physics; Nonlinear system; Quantum mechanics; Statistics","score_opus":0.00991711186909543,"score_gpt":0.2738481289984077,"score_spread":0.2639310171293123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167218823","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":[0.9594045,0.025932482,0.013088236,0.0009789389,0.000009209719,0.00032836103,0.0000024720266,0.000009164332,0.0002466077],"genre_scores_gemma":[0.996686,0.002426569,0.00016373613,0.0005038995,0.00010083697,0.000022044424,0.00005795222,0.0000079533675,0.00003101492],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99935883,0.00003634655,0.00013172477,0.0002341015,0.000100296726,0.00013867587],"domain_scores_gemma":[0.99958956,0.000012955084,0.000056670775,0.00024109967,0.000041084113,0.000058603975],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000090988375,0.00011023106,0.0001910612,0.000021500218,0.000031715215,0.000009501401,0.000072001865,0.000027230946,0.0000037925797],"category_scores_gemma":[0.00003767101,0.000087272485,0.000054229225,0.00023484469,0.000032618053,0.000003989532,0.000019926392,0.000053815093,0.000007779324],"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":[0.00060246006,0.0025931709,0.006982683,0.0010523746,0.0008613548,0.000015291002,0.00049884565,0.06876349,0.38678625,0.021224257,0.007043929,0.50357586],"study_design_scores_gemma":[0.01525715,0.015953394,0.5177183,0.014563875,0.0076481276,0.00021347836,0.00032452596,0.25362027,0.04352568,0.07359462,0.04736497,0.010215617],"about_ca_topic_score_codex":0.0000037225186,"about_ca_topic_score_gemma":0.000030415504,"teacher_disagreement_score":0.51073563,"about_ca_system_score_codex":0.000009886354,"about_ca_system_score_gemma":0.000027316362,"threshold_uncertainty_score":0.35588685},"labels":[],"label_agreement":null},{"id":"W2167746224","doi":"10.1016/s0006-3495(03)70013-7","title":"Feedback Regulation in the Lactose Operon: A Mathematical Modeling Study and Comparison with Experimental Data","year":2003,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":220,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Lactose; Operon; lac operon; gal operon; Chemistry; Biological system; Econometrics; Food science; Biology; Mathematics; Biochemistry; Gene","score_opus":0.040857157046535995,"score_gpt":0.30371490898662523,"score_spread":0.26285775194008926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167746224","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":[0.99625313,0.00018194538,0.003246124,0.000052191008,0.00001099466,0.00013901349,9.4948433e-7,0.0000020904467,0.00011355219],"genre_scores_gemma":[0.99898624,0.0000058854066,0.0007858425,0.00002642146,0.00014655651,0.0000046067003,0.000010105576,0.0000111498575,0.000023207012],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989466,0.00022153714,0.0002096711,0.00024475218,0.00022294646,0.0001544789],"domain_scores_gemma":[0.99943304,0.00000998224,0.000060867842,0.00040770057,0.000026076958,0.00006232255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003697069,0.000119031945,0.00016304995,0.00002352695,0.00010493389,0.000083846535,0.00024246944,0.000042915613,0.000018492237],"category_scores_gemma":[0.000015997866,0.000072925555,0.00003062845,0.00010190276,0.00005111779,0.000011068926,0.000080563725,0.00013443928,0.0000043470936],"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":[0.0007773386,0.0060208803,0.017300917,0.000021485761,0.0005590594,0.00005528337,0.0024533647,0.028964844,0.94021696,0.0005197424,0.0008786136,0.0022314861],"study_design_scores_gemma":[0.0070975036,0.004365381,0.0131445695,0.00009238158,0.00048835797,0.00096750667,0.023191482,0.88989407,0.058023933,0.00033231516,0.0013120334,0.0010904405],"about_ca_topic_score_codex":0.0000020338111,"about_ca_topic_score_gemma":0.00000838455,"teacher_disagreement_score":0.882193,"about_ca_system_score_codex":0.000010940802,"about_ca_system_score_gemma":0.000026437801,"threshold_uncertainty_score":0.2973818},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.028870462950591584,"score_gpt":0.2911497765064473,"score_spread":0.2622793135558557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168281812","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":[0.49477127,0.02786318,0.46939585,0.000046608544,0.004663177,0.0018503728,0.00027216604,0.00010914499,0.0010282167],"genre_scores_gemma":[0.99064994,0.000108012144,0.0010646468,0.00012951507,0.004529768,0.00021325916,0.001738648,0.00005924566,0.0015069933],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966332,0.00044545258,0.0009358622,0.00084708363,0.0000912343,0.001047185],"domain_scores_gemma":[0.99799365,0.00020805563,0.00042493152,0.0008797296,0.00028183387,0.00021179105],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0018271724,0.00041987863,0.0008109765,0.00012733159,0.00023241618,0.000034953904,0.000484425,0.00084722467,0.000011042901],"category_scores_gemma":[0.00009347911,0.00036658163,0.00033208422,0.0002588484,0.0002309301,0.0000031103689,0.00018486619,0.00013028004,0.000037236823],"study_design_candidate":"not_applicable","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":[0.0013875163,0.00027897072,0.43152288,0.0006638908,0.0020237889,0.000008053489,0.000061025698,0.07112841,0.396569,0.02415984,0.07012047,0.0020761208],"study_design_scores_gemma":[0.0023293342,0.0013067548,0.0024955103,0.00006415438,0.00020202076,0.00014902114,0.00023269243,0.009400994,0.0036215445,0.00019399018,0.9790534,0.0009506007],"about_ca_topic_score_codex":0.00014342909,"about_ca_topic_score_gemma":0.00037677973,"teacher_disagreement_score":0.9089329,"about_ca_system_score_codex":0.000051592873,"about_ca_system_score_gemma":0.00010148744,"threshold_uncertainty_score":0.9998786},"labels":[],"label_agreement":null},{"id":"W2168780544","doi":"10.1007/s00285-012-0608-8","title":"Dynamics and stability of a three-dimensional model of cell signal transduction","year":2012,"lang":"en","type":"article","venue":"Journal of Mathematical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Ordinary differential equation; Stability (learning theory); Differential equation; Signal transduction; Exponential stability; Signalling; Control theory (sociology); Mathematics; Cytosol; SIGNAL (programming language); Hysteresis; Biological system; Signalling pathways; Dynamics (music); Applied mathematics; Mathematical analysis; Physics; Computer science; Biology; Cell biology; Nonlinear system","score_opus":0.015968019775851158,"score_gpt":0.23863028646188583,"score_spread":0.22266226668603467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168780544","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":[0.90869045,0.0006222892,0.090506345,0.00005400184,0.000024743347,0.000040931372,0.000008563413,7.286606e-7,0.000051929957],"genre_scores_gemma":[0.98551583,0.000026610936,0.014362301,0.0000086740765,0.000068175425,6.194564e-7,0.0000054587204,0.000006242083,0.0000060869115],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991071,0.000074939315,0.00049809925,0.000084996405,0.000098916316,0.00013593241],"domain_scores_gemma":[0.9992536,0.00004491964,0.00033523864,0.00012635914,0.00015624422,0.000083647785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006308694,0.0000883148,0.00032595336,0.00004513762,0.000014062073,0.0000011397093,0.000082686216,0.00014873774,0.00005774243],"category_scores_gemma":[0.000041623447,0.00006556938,0.0001605096,0.00004651351,0.0001966698,0.000004638427,0.00003722035,0.00007878884,3.689698e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000111921654,0.00027877596,0.0072327154,0.00007563234,0.000104551335,1.0875038e-7,0.00003888241,0.00067490776,0.9897974,0.0012961332,0.000011815111,0.00037713395],"study_design_scores_gemma":[0.00058067485,0.00065592444,0.0009260279,0.00002320723,0.00025719215,0.0000797161,0.00006498776,0.066387445,0.91611797,0.014768022,0.000008511418,0.00013034517],"about_ca_topic_score_codex":7.1376667e-7,"about_ca_topic_score_gemma":0.000003530437,"teacher_disagreement_score":0.076825365,"about_ca_system_score_codex":0.000010226025,"about_ca_system_score_gemma":0.00004905794,"threshold_uncertainty_score":0.26738417},"labels":[],"label_agreement":null},{"id":"W2169316089","doi":"10.1529/biophysj.106.101717","title":"Origin of Bistability in the lac Operon","year":2007,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":101,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Bistability; Multistability; lac operon; Operon; Lactose; Inducer; L-arabinose operon; Chemistry; Physics; Biophysics; Biological system; Escherichia coli; Biology; Biochemistry; Gene; Quantum mechanics; Nonlinear system","score_opus":0.012945299753237511,"score_gpt":0.27313799941015565,"score_spread":0.26019269965691816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2169316089","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":[0.9984172,0.00009412202,0.00096645363,0.00016263837,0.000053571122,0.00004234088,0.0000012978184,0.0000011911823,0.0002611726],"genre_scores_gemma":[0.9991967,0.000026222177,0.00019950652,0.00007286086,0.00046277294,7.266327e-7,0.0000038468247,0.000005473839,0.00003190069],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99919367,0.000095261064,0.00023437204,0.00012243942,0.00017554415,0.00017869126],"domain_scores_gemma":[0.99956346,0.000017936676,0.00008202865,0.00022812696,0.00005612996,0.000052342537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007745578,0.00007647133,0.00011740133,0.00003178032,0.000039909726,0.000011942105,0.00023557928,0.000060845512,0.000011440444],"category_scores_gemma":[0.000029651414,0.000049309714,0.0001434256,0.00018574734,0.00009141986,0.0000021365147,0.00003396383,0.00012904606,0.0000030722606],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006709208,0.00014827613,0.013645536,0.000003911093,0.000027239657,0.0000067715273,0.000046092693,0.00012144457,0.9833798,0.00013217867,0.00033543006,0.0020862306],"study_design_scores_gemma":[0.00080446975,0.00047945158,0.2966508,0.000015933727,0.000062673214,0.00008188788,0.00039511055,0.00020542483,0.67432404,0.00027196086,0.026453065,0.00025515535],"about_ca_topic_score_codex":0.000011731471,"about_ca_topic_score_gemma":0.000036132078,"teacher_disagreement_score":0.30905575,"about_ca_system_score_codex":0.000014190471,"about_ca_system_score_gemma":0.000034721874,"threshold_uncertainty_score":0.20107919},"labels":[],"label_agreement":null},{"id":"W2169937880","doi":"10.1109/tsmcb.2009.2014736","title":"Automated Large-Scale Control of Gene Regulatory Networks","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"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 Calgary","funders":"","keywords":"Computer science; Curse of dimensionality; State space; Control (management); Gene regulatory network; Markov decision process; Reduction (mathematics); Dimensionality reduction; Space (punctuation); State (computer science); Scale (ratio); Mathematical optimization; Machine learning; Markov process; Artificial intelligence; Algorithm; Mathematics; Gene","score_opus":0.006217990682234753,"score_gpt":0.21510425167019398,"score_spread":0.20888626098795923,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2169937880","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":[0.6580432,0.0049611363,0.33375466,0.00010137696,0.00087254035,0.00080175244,0.00014108863,0.00020031673,0.0011239059],"genre_scores_gemma":[0.9950318,0.0007693397,0.00028134338,0.00021654711,0.00032915847,0.00003772218,0.000049919494,0.00006608737,0.0032181244],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99710405,0.00025728688,0.00083946483,0.0007493086,0.0004210346,0.0006288347],"domain_scores_gemma":[0.9981042,0.00003386409,0.00033135503,0.0009846125,0.00022127674,0.00032469194],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004293664,0.00047994434,0.0006610252,0.00016634772,0.00019211006,0.000065423956,0.0002954214,0.0004961228,0.00002964917],"category_scores_gemma":[0.0000043501873,0.00049492554,0.0003125388,0.0002864287,0.00019559455,0.000008617954,0.0000052186065,0.00024003471,0.000016129916],"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":[0.0005368496,0.0012889246,0.0011273752,0.0001117557,0.0012953157,0.000022217991,0.00037825524,0.8261317,0.15282556,0.00044628768,0.00809685,0.007738901],"study_design_scores_gemma":[0.008149475,0.003212993,0.015621696,0.00042811708,0.0017801579,0.00024264572,0.0005140824,0.7211891,0.21167417,0.000080429454,0.034625437,0.0024817435],"about_ca_topic_score_codex":0.000022864084,"about_ca_topic_score_gemma":0.00006489662,"teacher_disagreement_score":0.33698854,"about_ca_system_score_codex":0.000035752193,"about_ca_system_score_gemma":0.000053898602,"threshold_uncertainty_score":0.99975026},"labels":[],"label_agreement":null},{"id":"W2170345699","doi":"10.1088/1367-2630/11/4/043024","title":"Random sampling versus exact enumeration of attractors in random Boolean networks","year":2009,"lang":"en","type":"article","venue":"New Journal of Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"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 Calgary","funders":"","keywords":"Attractor; Distribution (mathematics); Exponent; Enumeration; Integer (computer science); Measure (data warehouse); Sampling (signal processing); Weighting","score_opus":0.018271726927553626,"score_gpt":0.2688594907382594,"score_spread":0.25058776381070574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170345699","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":[0.8832427,0.0017312072,0.114576325,0.000055141947,0.00021787506,0.00006548813,6.8855525e-7,0.0000017965954,0.00010876579],"genre_scores_gemma":[0.99717504,0.00037312644,0.0009892549,0.000036205223,0.0013774188,2.4028932e-7,0.000014211531,0.000010734666,0.000023753239],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99900615,0.000080451486,0.00045786827,0.00011899616,0.0001788404,0.00015769793],"domain_scores_gemma":[0.9991508,0.000041483898,0.00044489332,0.00016819453,0.000113448725,0.00008118679],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030856807,0.00012439788,0.00033010554,0.000049549,0.00002680415,0.000014565028,0.00014276888,0.00009840256,0.0000071373297],"category_scores_gemma":[0.000049891725,0.00011504975,0.00027306803,0.00016558242,0.000020581148,0.000011573394,0.000013417812,0.0001525933,4.4296172e-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":[0.0037200064,0.00012926817,0.0023246875,0.0000053721933,0.0002458571,0.000004042731,0.0000932583,0.63942504,0.2851865,0.000040616207,0.0008267814,0.06799856],"study_design_scores_gemma":[0.110795505,0.005061849,0.04785913,0.0004540677,0.001488924,0.00006493919,0.00034490493,0.02806848,0.7904226,0.0025680885,0.011365472,0.0015060011],"about_ca_topic_score_codex":0.0000074565974,"about_ca_topic_score_gemma":0.000015065271,"teacher_disagreement_score":0.61135656,"about_ca_system_score_codex":0.000023501198,"about_ca_system_score_gemma":0.00011862482,"threshold_uncertainty_score":0.46915925},"labels":[],"label_agreement":null},{"id":"W2170467788","doi":"10.1016/j.jtbi.2007.01.021","title":"Studying genetic regulatory networks at the molecular level: Delayed reaction stochastic models","year":2007,"lang":"en","type":"article","venue":"Journal of Theoretical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":124,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Stochastic modelling; Computer science; Gene regulatory network; Stochastic process; Binary number; Stochastic simulation; Function (biology); Genetic model; Systems biology; Biological system; Gene; Computational biology; Gene expression; Biology; Mathematics; Genetics","score_opus":0.01312764917970648,"score_gpt":0.25594102212197717,"score_spread":0.24281337294227068,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170467788","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":[0.6138491,0.003402416,0.3820927,0.00016595659,0.00024900047,0.000092723974,0.000002170637,0.000004467726,0.00014145984],"genre_scores_gemma":[0.99762166,0.00013834109,0.0010719582,0.00037079462,0.0006767739,0.0000027503424,0.000015810381,0.000035753284,0.00006617524],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9978428,0.00036718897,0.00074025284,0.00031606937,0.00024032754,0.00049335504],"domain_scores_gemma":[0.99837714,0.00014363331,0.00046689305,0.0005282387,0.00028484347,0.00019924955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018879877,0.00024064815,0.00035541545,0.000107365944,0.00016017846,0.000015525136,0.00044704636,0.00036562452,0.00003761346],"category_scores_gemma":[0.00016416915,0.00016264059,0.0003841889,0.00018942554,0.0007306861,0.0000051648444,0.00024097321,0.0003210428,0.00000485348],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014602476,0.00012279821,0.00068798463,0.0000055049913,0.0011066794,0.000051583764,0.000053671654,0.23455827,0.7130765,0.038171526,0.00076974,0.009935515],"study_design_scores_gemma":[0.012055803,0.013921002,0.03742626,0.00025986065,0.006793986,0.010941889,0.0015511287,0.17257039,0.3948796,0.3326746,0.012071046,0.004854428],"about_ca_topic_score_codex":0.0000026616005,"about_ca_topic_score_gemma":0.000014798273,"teacher_disagreement_score":0.38377255,"about_ca_system_score_codex":0.00008763198,"about_ca_system_score_gemma":0.0000659053,"threshold_uncertainty_score":0.66322905},"labels":[],"label_agreement":null},{"id":"W2170599381","doi":"10.1186/1742-4682-8-30","title":"Cancer as a dynamical phase transition","year":2011,"lang":"en","type":"article","venue":"Theoretical Biology and Medical Modelling","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":104,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Cancer Foundation; Allard Foundation; National Cancer Institute; National Institutes of Health; Ministry of Advanced Education, Government of Alberta","keywords":"Analogy; Attractor; Statistical physics; Phase transition; Cancer; Perspective (graphical); Transition (genetics); Dynamical systems theory; Physics; Computer science; Mathematics; Biology; Thermodynamics; Artificial intelligence; Quantum mechanics; Epistemology","score_opus":0.011969819853532753,"score_gpt":0.2823732760610032,"score_spread":0.27040345620747047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170599381","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":[0.69977546,0.0009912163,0.2978562,0.00031350888,0.00005335517,0.00007212451,0.000005119517,0.000012872357,0.0009201227],"genre_scores_gemma":[0.9966578,0.0013632815,0.0008787378,0.0007577075,0.00022258224,0.000027244194,0.00005913454,0.000012262102,0.000021268404],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989658,0.00012763223,0.00019141268,0.00034857585,0.00009549286,0.00027109915],"domain_scores_gemma":[0.9994719,0.000022121338,0.000026566393,0.00015442015,0.000033185628,0.00029182524],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00031940185,0.00013295736,0.00018319384,0.00002849281,0.000068913854,0.000003291548,0.000120621786,0.0004117635,0.0009394992],"category_scores_gemma":[0.00004469442,0.00010514001,0.000080750375,0.00005262342,0.0010105759,0.0000017394407,0.00005100191,0.00015922831,0.000009178648],"study_design_candidate":"theoretical_or_conceptual","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":[0.0016763185,0.0005178911,0.00040524482,0.000029281166,0.00042747194,0.000032139316,0.00050009205,0.00065219053,0.042374615,0.90063393,0.000066894565,0.052683946],"study_design_scores_gemma":[0.0030911532,0.0015580715,0.00003488972,0.00007508622,0.0003055529,0.00013090616,0.000112763846,0.64632165,0.040561438,0.30440393,0.002733431,0.00067115267],"about_ca_topic_score_codex":0.000018437584,"about_ca_topic_score_gemma":0.00000465638,"teacher_disagreement_score":0.64566946,"about_ca_system_score_codex":0.0000049885043,"about_ca_system_score_gemma":0.000055194032,"threshold_uncertainty_score":0.9999738},"labels":[],"label_agreement":null},{"id":"W2170904936","doi":"10.1109/iscas.1989.100673","title":"The immune system: a neglected challenge for network theorists","year":2003,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Field (mathematics); Computer science; Artificial neural network; Artificial intelligence; Feed forward; Cognitive science; Engineering; Psychology; Control engineering; Mathematics","score_opus":0.006182630006246077,"score_gpt":0.21733700905152384,"score_spread":0.21115437904527776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170904936","genre_codex":"review","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":[0.29275602,0.29964814,0.2299106,0.0019584014,0.0040928926,0.0048261397,0.00002320034,0.00043344835,0.16635115],"genre_scores_gemma":[0.99421,0.00035036524,0.0008618024,0.00003676328,0.00041019128,0.0001124849,0.000028102137,0.000027513797,0.0039627957],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988921,0.00015017214,0.00022604513,0.00026975156,0.00008570062,0.00037623046],"domain_scores_gemma":[0.99913394,0.000042842326,0.00008321452,0.0005699013,0.00011201515,0.000058085636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035275795,0.00014439852,0.00015005826,0.000011395668,0.00034656803,0.000032261265,0.00020257906,0.00012052334,0.000010653774],"category_scores_gemma":[0.000063652995,0.00009659727,0.00020410796,0.00013421042,0.000051673353,9.295527e-7,0.000037146485,0.00004254947,0.00000884283],"study_design_candidate":"not_applicable","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":[0.0005455966,0.00019304613,0.0009998133,0.00017564246,0.0029220812,0.0000052953224,0.00008751771,0.010817428,0.15986297,0.75574434,0.055271957,0.013374336],"study_design_scores_gemma":[0.0011601313,0.00039215357,0.000599096,0.000024026336,0.00020342221,0.000029883819,0.00038861518,0.002383361,0.077629104,0.0020563828,0.91460806,0.0005257487],"about_ca_topic_score_codex":0.0000035884987,"about_ca_topic_score_gemma":0.00006476885,"teacher_disagreement_score":0.85933614,"about_ca_system_score_codex":0.000016380356,"about_ca_system_score_gemma":0.00004942358,"threshold_uncertainty_score":0.39391226},"labels":[],"label_agreement":null},{"id":"W2171832486","doi":"10.1093/bioinformatics/btl017","title":"Polynomial model approach for resynchronization analysis of cell-cycle gene expression data","year":2006,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"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":"","keywords":"Computational biology; Microarray analysis techniques; Gene; Identification (biology); Cell cycle; Computer science; Expression (computer science); Gene expression; Biology; Functional genomics; Microarray; Gene expression profiling; Genomics; Algorithm; Genetics; Genome","score_opus":0.015229784318238205,"score_gpt":0.23799432060265668,"score_spread":0.22276453628441847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171832486","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":[0.19302158,0.00022096124,0.8055489,0.000004539834,0.000019141335,0.00017006087,0.00031259577,0.000008846683,0.00069339556],"genre_scores_gemma":[0.70538723,0.000030084557,0.28261212,0.000017054708,0.00010571449,0.00000835654,0.01163105,0.000012785594,0.00019562671],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989835,0.000016400605,0.00044662014,0.00021345499,0.0001587086,0.00018133163],"domain_scores_gemma":[0.998627,0.0000069854555,0.0002752732,0.0009496278,0.00010030358,0.00004082703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021204202,0.00012887522,0.00022795815,0.00014582401,0.0000716502,0.000018791803,0.00036941402,0.00014516975,0.0000030993858],"category_scores_gemma":[0.000016805481,0.00012144705,0.00015078894,0.00033557252,0.00004061045,0.0000133416415,0.00020755139,0.000025958518,5.948656e-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":[0.00003087872,0.00006940173,0.00055121083,0.000051218944,0.00019276893,2.5077295e-8,0.000023339362,0.75206226,0.23444468,0.000004233259,0.012308094,0.0002618799],"study_design_scores_gemma":[0.00026523694,0.00002272992,0.00013999638,0.0000016179218,0.0005468875,2.6659302e-7,0.00002822673,0.80306524,0.19534497,0.0000036652552,0.0004676703,0.00011350693],"about_ca_topic_score_codex":0.000010197896,"about_ca_topic_score_gemma":0.000010747231,"teacher_disagreement_score":0.52293676,"about_ca_system_score_codex":0.000014551136,"about_ca_system_score_gemma":0.00007067981,"threshold_uncertainty_score":0.49524668},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.019119387477840116,"score_gpt":0.2540747617919151,"score_spread":0.234955374314075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2172187648","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":[0.6542764,0.001176175,0.34314898,0.00005921704,0.00014407627,0.00021372693,0.000046677553,0.000019435267,0.00091536966],"genre_scores_gemma":[0.99641424,0.00009860829,0.0025944693,0.00016553255,0.0001708173,0.000029194362,0.00009250302,0.000022037042,0.00041256731],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99862057,0.00018082635,0.00036719439,0.00046488273,0.00006599969,0.00030053023],"domain_scores_gemma":[0.9993077,0.00007200316,0.00014253327,0.0003339099,0.00006543485,0.00007845549],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004489889,0.00018250966,0.0003235272,0.00008510383,0.000069279246,0.000023172928,0.00011990802,0.0002691606,0.0000025670201],"category_scores_gemma":[0.00006995138,0.00017832957,0.000048522037,0.00010419227,0.00007157402,0.0000039423435,0.000081783684,0.00008521842,0.0000033600977],"study_design_candidate":"simulation_or_modeling","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":[0.000096111624,0.00010493629,0.51813775,0.00024709947,0.000178273,0.000002600837,0.00032200327,0.25089464,0.21868181,0.0029129202,0.007180871,0.0012409854],"study_design_scores_gemma":[0.00067112537,0.00020777693,0.0020861528,0.000036206635,0.00003275696,0.000033844182,0.00011454021,0.9926712,0.001043099,0.00068488356,0.0021523365,0.00026607412],"about_ca_topic_score_codex":0.00011625378,"about_ca_topic_score_gemma":0.0003915661,"teacher_disagreement_score":0.7417766,"about_ca_system_score_codex":0.000022484177,"about_ca_system_score_gemma":0.00007326835,"threshold_uncertainty_score":0.7272069},"labels":[],"label_agreement":null},{"id":"W2172648302","doi":"10.1007/978-94-017-8896-0_17","title":"Toward Intracellular Delivery and Drug Discovery: Stochastic Logic Networks as Efficient Computational Models for Gene Regulatory Networks","year":2014,"lang":"en","type":"book-chapter","venue":"Fundamental biomedical technologies","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Gene regulatory network; Probabilistic logic; Boolean network; Computer science; Biological network; Theoretical computer science; And-inverter graph; Boolean function; Computational biology; Boolean circuit; Gene; Algorithm; Biology; Artificial intelligence; Gene expression; Genetics","score_opus":0.011246966327475126,"score_gpt":0.2152243253908006,"score_spread":0.20397735906332548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2172648302","genre_codex":"methods","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":[0.021495335,0.027686063,0.9479121,0.0005369828,0.00050013,0.0010324616,0.00017926541,0.00028991533,0.00036773714],"genre_scores_gemma":[0.9826046,0.0011926452,0.0038899756,0.0002256902,0.000547254,0.000107378444,0.0030591167,0.00012062897,0.008252683],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99689263,0.000037171896,0.00065633527,0.0012637276,0.0005088674,0.0006412455],"domain_scores_gemma":[0.9985138,0.00010720288,0.00040345237,0.0006790543,0.00011551521,0.0001809466],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0003779079,0.0007241456,0.00076871313,0.0002604503,0.00026698268,0.00010684809,0.00059308874,0.001478028,0.00001848528],"category_scores_gemma":[0.000047681795,0.0006711548,0.00041821878,0.00009492024,0.0017423875,0.00000777295,0.001002288,0.00045925903,0.000007368204],"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":[0.00031917554,0.00012572684,0.000008510904,0.00011930922,0.001247806,0.000029390234,0.000022727203,0.91228086,0.0023180314,0.037172772,0.009235731,0.037119966],"study_design_scores_gemma":[0.001707674,0.0011479177,0.000011805405,0.000347489,0.0007570056,0.00014860116,0.00024497395,0.9130499,0.0011335568,0.05960023,0.019975757,0.0018750833],"about_ca_topic_score_codex":0.000004527034,"about_ca_topic_score_gemma":0.0000026247733,"teacher_disagreement_score":0.9611093,"about_ca_system_score_codex":0.00013790566,"about_ca_system_score_gemma":0.000105469386,"threshold_uncertainty_score":0.99981827},"labels":[],"label_agreement":null},{"id":"W2172997278","doi":"10.1016/j.tcs.2012.03.044","title":"Approximation algorithms for orienting mixed graphs","year":2012,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Logarithm; Approximation algorithm; Undirected graph; Vertex (graph theory); Mathematics; Combinatorics; Graph; Directed graph; Mixed graph; Discrete mathematics; Algorithm; Computer science; Line graph; Voltage graph","score_opus":0.011063770892872771,"score_gpt":0.25410822685249945,"score_spread":0.24304445595962668,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2172997278","genre_codex":"methods","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":[0.39504942,0.000065599495,0.60431886,0.00003227614,0.0002658322,0.00008881883,0.000001018136,0.000011161463,0.00016703963],"genre_scores_gemma":[0.89970034,0.0000022580857,0.09975369,0.00008197456,0.00041669887,0.000012688659,0.0000141901355,0.000007736814,0.000010424219],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99889237,0.00003985782,0.0001393912,0.00030147107,0.00019977165,0.00042714764],"domain_scores_gemma":[0.9993461,0.000021340156,0.000046650326,0.0003090256,0.0001226647,0.00015422518],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011188085,0.0000969174,0.00009487971,0.000056197565,0.0002284589,0.00004775824,0.00032088524,0.000050330258,0.000007642892],"category_scores_gemma":[0.000055823883,0.00008332858,0.00008476039,0.00031759558,0.00076297316,0.00001155347,0.00019788368,0.000034800476,0.000006035856],"study_design_candidate":"theoretical_or_conceptual","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":[0.000024192506,0.00010564133,0.002120159,0.000016135253,0.000032417287,1.6949228e-7,0.00013949905,0.00050336984,0.10082592,0.8431776,0.00030636386,0.052748542],"study_design_scores_gemma":[0.00059119525,0.00033598018,0.00495533,0.000015217475,0.00007474368,0.000024655441,0.000039700135,0.41085374,0.5405546,0.03923226,0.002755553,0.0005670475],"about_ca_topic_score_codex":2.4385105e-7,"about_ca_topic_score_gemma":1.321701e-7,"teacher_disagreement_score":0.8039453,"about_ca_system_score_codex":0.000010433243,"about_ca_system_score_gemma":0.00002582261,"threshold_uncertainty_score":0.3398041},"labels":[],"label_agreement":null},{"id":"W2181129920","doi":"10.1186/s13637-015-0030-9","title":"Carcinogenesis: alterations in reciprocal interactions of normal functional structure of biologic systems","year":2015,"lang":"en","type":"article","venue":"EURASIP Journal on Bioinformatics and Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Ottawa Hospital","funders":"","keywords":"Reciprocal; Matrix (chemical analysis); Computational biology; Biology; Pathological; Functional analysis; Basis (linear algebra); Computer science; Mathematics; Genetics; Chemistry; Gene; Mathematical analysis","score_opus":0.030816123196659863,"score_gpt":0.2607278045510084,"score_spread":0.22991168135434856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2181129920","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":[0.99380326,0.0019385131,0.0029247792,0.00002953061,0.00084504916,0.00014656362,0.000065670705,0.000002991618,0.0002436316],"genre_scores_gemma":[0.99913126,0.00015543212,0.00024435628,0.00002483729,0.00026960816,0.0000044156045,0.00010845363,0.000007906753,0.0000537558],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983864,0.00022428902,0.0009299536,0.00013467768,0.00013144843,0.00019326112],"domain_scores_gemma":[0.99872786,0.000034730536,0.00059275696,0.00019659291,0.00032223045,0.0001258348],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004751078,0.00016179429,0.0003818442,0.00027307367,0.000061376275,0.0000249867,0.00013022948,0.00018244002,0.0000043495284],"category_scores_gemma":[0.00009144278,0.00011920403,0.00009143378,0.0001742916,0.00010357768,0.000013958164,0.000052722262,0.00015805196,0.0000014909257],"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":[0.0010488352,0.0002499803,0.41636077,0.00035665467,0.00095016765,0.00000815935,0.00087378273,0.18314438,0.38707873,0.005411728,0.0026044298,0.0019123828],"study_design_scores_gemma":[0.019134985,0.023187188,0.31433558,0.002011975,0.0009792174,0.014295259,0.0312539,0.39855987,0.122902066,0.0012504649,0.067817464,0.0042720116],"about_ca_topic_score_codex":0.000040734125,"about_ca_topic_score_gemma":0.000050834653,"teacher_disagreement_score":0.26417667,"about_ca_system_score_codex":0.000031167976,"about_ca_system_score_gemma":0.00012724407,"threshold_uncertainty_score":0.48609993},"labels":[],"label_agreement":null},{"id":"W2184213955","doi":"10.1007/s00285-015-0949-1","title":"The limiting dynamics of a bistable molecular switch with and without noise","year":2015,"lang":"en","type":"article","venue":"Journal of Mathematical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Narodowe Centrum Nauki","keywords":"Bistability; Bursting; Stationary distribution; Statistical physics; Gaussian noise; Noise (video); Population; Stationary state; Gaussian; Mathematics; Physics; Biology; Quantum mechanics; Computer science; Statistics; Markov chain","score_opus":0.010691320462533804,"score_gpt":0.24985984853769128,"score_spread":0.23916852807515748,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2184213955","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":[0.9689962,0.0014307378,0.028626155,0.0004081625,0.000024138186,0.000054507294,0.0000015036674,0.0000015890888,0.00045695825],"genre_scores_gemma":[0.992297,0.00010724961,0.0074195,0.000034976547,0.00005931278,0.0000015645198,0.0000026850032,0.000011687588,0.00006603309],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991336,0.000099545,0.00037308692,0.00010642737,0.000120913865,0.00016643849],"domain_scores_gemma":[0.99898434,0.00004919155,0.00036162292,0.00020135845,0.00028724776,0.000116249845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073406956,0.000103573046,0.0002806571,0.00003509098,0.000036295434,0.000012761273,0.00016879172,0.00009786087,0.0000021947017],"category_scores_gemma":[0.0002933975,0.00005653314,0.00007716448,0.00008046552,0.00023043525,0.000002738243,0.00007778751,0.000094601295,7.4384235e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002241126,0.0005795348,0.14876823,0.00031517877,0.0030698162,0.000045392022,0.00042730058,0.002514534,0.7723111,0.057192255,0.0010118,0.01152375],"study_design_scores_gemma":[0.018340966,0.024322828,0.0065043336,0.000979629,0.004117814,0.010568365,0.008763163,0.071753286,0.54330397,0.28461954,0.023960914,0.002765154],"about_ca_topic_score_codex":0.0000011908537,"about_ca_topic_score_gemma":0.000008718242,"teacher_disagreement_score":0.2290071,"about_ca_system_score_codex":0.000012981924,"about_ca_system_score_gemma":0.00009460627,"threshold_uncertainty_score":0.23053546},"labels":[],"label_agreement":null},{"id":"W2187695640","doi":"","title":"Using label propagation for learning temporally abstract actions in reinforcement learning","year":2013,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Abstraction; Reinforcement learning; Construct (python library); Computer science; Artificial intelligence; Machine learning; Key (lock); Programming language","score_opus":0.0380446733139703,"score_gpt":0.29454255963902803,"score_spread":0.2564978863250577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2187695640","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":[0.9548364,0.00005685469,0.043115795,0.0000754053,0.000030120564,0.00035464263,1.4479791e-7,0.000017096821,0.0015135069],"genre_scores_gemma":[0.9905631,0.00001780901,0.004667279,0.000035572004,0.00009815778,0.000062562445,0.00009903069,0.00001777368,0.004438725],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924934,0.000027755792,0.00022147257,0.00021630219,0.00008271007,0.00020244245],"domain_scores_gemma":[0.99961996,0.000008089482,0.000107521286,0.00011871222,0.00010261562,0.000043082346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018603746,0.00010143749,0.00009905869,0.000067870686,0.00012313448,0.000035708217,0.000062277664,0.00009367903,0.00009475757],"category_scores_gemma":[0.00005412233,0.000098560944,0.000051835657,0.00010715224,0.000016569005,0.000009845274,0.000035301844,0.000092195936,0.00001268228],"study_design_candidate":"simulation_or_modeling","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":[0.00000843642,0.000016397866,0.008081192,0.000010701873,0.00003142027,1.3725591e-7,0.000015540747,0.37173897,0.6175194,0.00002479672,0.00015576862,0.002397266],"study_design_scores_gemma":[0.0015852967,0.000533814,0.017148564,0.000044484335,0.00007350096,0.0000073742385,0.00073796196,0.748761,0.21087354,0.00011313584,0.019482942,0.00063838984],"about_ca_topic_score_codex":0.00013494992,"about_ca_topic_score_gemma":0.000071135015,"teacher_disagreement_score":0.40664583,"about_ca_system_score_codex":0.000034213313,"about_ca_system_score_gemma":0.00005071259,"threshold_uncertainty_score":0.40191987},"labels":[],"label_agreement":null},{"id":"W2190785257","doi":"10.1039/c5ib00252d","title":"Build to understand: synthetic approaches to biology","year":2015,"lang":"en","type":"review","venue":"Integrative Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Army Research Office; American Heart Association; National Institute of General Medical Sciences; Division of Mathematical Sciences; National Institutes of Health; National Science Foundation","keywords":"Synthetic biology; Biology; Computational biology; Systems biology; Task (project management); Experimental biology; Evolutionary biology; Data science; Computer science; Engineering","score_opus":0.16339548309425514,"score_gpt":0.354589425332191,"score_spread":0.19119394223793587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2190785257","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00015849413,0.9811334,0.015021373,0.00017731443,0.00048078105,0.0011369622,0.000287651,0.00003437494,0.00156965],"genre_scores_gemma":[0.0018624343,0.98971045,0.002889001,0.0004151416,0.001061998,0.00042603628,0.0018291433,0.00015041974,0.0016553936],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99581516,0.0010295664,0.0007374596,0.0015824153,0.00010497984,0.0007303945],"domain_scores_gemma":[0.99777603,0.000083034254,0.0003007096,0.0011683225,0.00019512228,0.00047676553],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00061674026,0.0009187367,0.0022949767,0.00045685572,0.00008653447,0.00002852577,0.0010016585,0.0012618894,0.000049691527],"category_scores_gemma":[0.00026995823,0.00064264564,0.0007572326,0.0006400752,0.00029927958,0.0000019514355,0.0006118129,0.00035540512,0.0003876396],"study_design_candidate":"not_applicable","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":[0.00007194863,0.0001027391,0.00002539309,0.00040377286,0.00182762,0.000004750346,0.00021401764,0.000038462273,0.000648145,0.0061629983,0.015698586,0.97480154],"study_design_scores_gemma":[0.0001030697,0.0009645115,5.4249176e-7,0.00042568072,0.00044597764,0.000031768992,0.00020510927,0.000003735432,0.0001858707,0.00068192935,0.9962418,0.0007099854],"about_ca_topic_score_codex":0.000033913628,"about_ca_topic_score_gemma":0.00023704494,"teacher_disagreement_score":0.98054326,"about_ca_system_score_codex":0.0002502737,"about_ca_system_score_gemma":0.00058395194,"threshold_uncertainty_score":0.9996025},"labels":[],"label_agreement":null},{"id":"W2191530647","doi":"10.1016/j.jmb.2015.10.004","title":"Tools and Principles for Microbial Gene Circuit Engineering","year":2015,"lang":"en","type":"review","venue":"Journal of Molecular Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":101,"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":"Biotechnology and Biological Sciences Research Council; Directorate for Biological Sciences; Royal Society; Royal Society of Canada; Wellcome Trust","keywords":"Synthetic biology; Computer science; Modular design; Scalability; Electronic circuit; Context (archaeology); Circuit design; Rational design; Biochemical engineering; Computational biology; Engineering; Nanotechnology; Biology; Embedded system; Electrical engineering","score_opus":0.046067304077958456,"score_gpt":0.3044333852416415,"score_spread":0.25836608116368304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2191530647","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018159476,0.97873735,0.018723106,0.000012720022,0.00030194523,0.00030488643,0.00008561751,0.0000036301612,0.000014779295],"genre_scores_gemma":[0.0002596339,0.9919667,0.006269845,0.000038436647,0.0009819866,0.000019671232,0.00032256483,0.00007583927,0.00006531991],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99821544,0.00015881105,0.00085280795,0.00036076788,0.00009431311,0.0003178502],"domain_scores_gemma":[0.99831474,0.000036334426,0.00083266,0.0003426204,0.0002939928,0.0001796777],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00075418706,0.00037923577,0.001410623,0.00021169744,0.00003063026,0.000033007054,0.00038853573,0.0006589295,0.0000016499949],"category_scores_gemma":[0.00027345712,0.00031690073,0.0008312791,0.00011151849,0.000068046174,0.0000030218873,0.00017371602,0.00021069356,0.000001724852],"study_design_candidate":"not_applicable","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":[0.000059672442,0.00007362225,0.000020401432,0.0030348615,0.004261813,0.000068616144,0.000013584497,0.0005348612,0.23413806,0.00035191717,0.0012120858,0.75623053],"study_design_scores_gemma":[0.00036548305,0.0003910422,0.0000014696273,0.00034994286,0.0011299546,0.0009160682,0.0000017698202,0.000008072356,0.0030181268,0.00004623085,0.99346346,0.0003083869],"about_ca_topic_score_codex":3.830314e-7,"about_ca_topic_score_gemma":7.3290715e-7,"teacher_disagreement_score":0.9922514,"about_ca_system_score_codex":0.000049408645,"about_ca_system_score_gemma":0.00043754998,"threshold_uncertainty_score":0.9999283},"labels":[],"label_agreement":null},{"id":"W2204725725","doi":"10.1016/j.jmaa.2015.11.070","title":"Inverse problems for delay differential equations using the Collage Theorem","year":2015,"lang":"en","type":"article","venue":"Journal of Mathematical Analysis and Applications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Delay differential equation; Ode; Mathematics; Ordinary differential equation; Applied mathematics; Inverse problem; Series (stratigraphy); Population; Regular polygon; Differential equation; Mathematical optimization; Mathematical analysis; Medicine","score_opus":0.031156675308309786,"score_gpt":0.2834688466250077,"score_spread":0.2523121713166979,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2204725725","genre_codex":"methods","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":[0.18168749,0.00024438908,0.8176536,0.00018540134,0.000006875772,0.00016760826,0.00000782856,0.0000015289781,0.000045277404],"genre_scores_gemma":[0.9904728,0.000032130458,0.008992848,0.000040819912,0.00024403975,0.00003890252,0.000019545547,0.000008499369,0.00015039551],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99919593,0.000053353673,0.00037381783,0.000114559174,0.00015880814,0.00010351305],"domain_scores_gemma":[0.9989925,0.00006940278,0.000287634,0.0002248744,0.00030663697,0.00011895564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000494468,0.00008632048,0.00022821946,0.00008240371,0.00013285902,0.000043961736,0.00015594253,0.000055194945,0.000014108669],"category_scores_gemma":[0.00008171175,0.000052344207,0.0002931918,0.00036039657,0.00009383401,0.0000045164393,0.00004529393,0.000047067017,9.0865603e-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":[0.0003357543,0.0028524676,0.007046434,0.00033725676,0.030924885,0.0000036008528,0.002153811,0.3866624,0.353545,0.19524637,0.010418699,0.010473295],"study_design_scores_gemma":[0.0019619607,0.00040271954,0.0004024468,0.00003784504,0.021092197,0.000105449864,0.0020828496,0.8264518,0.009077368,0.11370103,0.024099898,0.0005844599],"about_ca_topic_score_codex":0.0000015231567,"about_ca_topic_score_gemma":0.000019513142,"teacher_disagreement_score":0.8087853,"about_ca_system_score_codex":0.000012384027,"about_ca_system_score_gemma":0.000054996202,"threshold_uncertainty_score":0.21345349},"labels":[],"label_agreement":null},{"id":"W2222444545","doi":"10.1017/mdh.2015.30","title":"A Knockout Experiment: Disciplinary Divides and Experimental Skill in Animal Behaviour Genetics","year":2015,"lang":"en","type":"article","venue":"Medical History","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"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":"Social Sciences and Humanities Research Council of Canada; National Science Foundation","keywords":"Context (archaeology); Discipline; Negotiation; Set (abstract data type); Sociology; Cognitive science; Engineering ethics; Epistemology; Computer science; Biology; Psychology; Social science","score_opus":0.02065468956583848,"score_gpt":0.27953174232347777,"score_spread":0.2588770527576393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2222444545","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":[0.93636316,0.06267998,0.000038472837,0.000087627894,0.000187681,0.00008130735,0.0000015634516,0.0000110399105,0.0005491591],"genre_scores_gemma":[0.99834204,0.00011668444,0.00032351477,0.00015090637,0.00026942667,0.000035275254,0.00003526291,0.000024530289,0.00070238404],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986396,0.00009578045,0.00024334066,0.0003949015,0.0003745938,0.000251776],"domain_scores_gemma":[0.99923176,0.00000681087,0.00005090172,0.00026891622,0.000025992147,0.000415608],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028117857,0.00016563373,0.00019479629,0.00006438675,0.000035267592,0.000005311203,0.00018561236,0.0002026543,0.000107908956],"category_scores_gemma":[0.00004802014,0.00016327543,0.00006599073,0.000051474468,0.00031572903,0.000003751551,0.00032847203,0.0001108056,0.000007868455],"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":[0.0008694537,0.002849235,0.38116708,0.000061854174,0.0002571694,0.0006100689,0.013241249,0.00021147126,0.4703033,0.00013688827,0.124036215,0.006256004],"study_design_scores_gemma":[0.012801242,0.0057986462,0.19356667,0.00024114117,0.00028936035,0.000463463,0.008993375,0.005124751,0.35482213,0.00015596,0.41443086,0.003312408],"about_ca_topic_score_codex":0.00003043309,"about_ca_topic_score_gemma":0.000077821984,"teacher_disagreement_score":0.29039463,"about_ca_system_score_codex":0.00019840158,"about_ca_system_score_gemma":0.00020698595,"threshold_uncertainty_score":0.66581786},"labels":[],"label_agreement":null},{"id":"W2231145543","doi":"10.1103/physreve.92.062712","title":"Role of DNA binding sites and slow unbinding kinetics in titration-based oscillators","year":2015,"lang":"en","type":"article","venue":"Physical Review E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"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":"National Institutes of Health; Canadian Aeronautics and Space Institute","keywords":"Repressor; DNA; Cooperativity; Biophysics; Cooperative binding; Physics; Noise (video); Binding site; Biology; Chemistry; Genetics; Gene; Computer science; Transcription factor","score_opus":0.015467945996246844,"score_gpt":0.27423766063060045,"score_spread":0.2587697146343536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2231145543","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":[0.9859197,0.013634768,0.00002952062,0.0000560138,0.00001017315,0.00010122593,0.00000286983,0.0000031579932,0.000242535],"genre_scores_gemma":[0.99856544,0.0010173724,0.00019685156,0.000070724236,0.00007883807,0.0000068781424,0.00004057083,0.000009699163,0.0000136520375],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99935484,0.000057237572,0.00016959892,0.00018197128,0.00012049809,0.0001158735],"domain_scores_gemma":[0.9995946,0.000016312059,0.00008293946,0.00017862258,0.000050905168,0.00007658977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015619819,0.00009516628,0.0002288677,0.000033074215,0.000011736318,0.0000059608465,0.00007201873,0.000030892435,0.0000024004385],"category_scores_gemma":[0.00011434956,0.00008547157,0.000074297124,0.00021599761,0.000041918694,0.0000024511864,0.000036697278,0.00003723441,0.0000039898737],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006121497,0.00006777871,0.02066244,0.00017453692,0.000024214434,3.6816863e-7,0.000020686148,0.00041009465,0.97569454,0.00012151198,0.00021676188,0.0026009518],"study_design_scores_gemma":[0.0009961084,0.00052080455,0.012669756,0.0010663895,0.00033175218,0.0000030207182,0.000082542734,0.016092708,0.94969684,0.0010617771,0.01682866,0.0006496405],"about_ca_topic_score_codex":0.0000034561538,"about_ca_topic_score_gemma":0.000014343192,"teacher_disagreement_score":0.025997695,"about_ca_system_score_codex":0.000012625394,"about_ca_system_score_gemma":0.000036033096,"threshold_uncertainty_score":0.34854293},"labels":[],"label_agreement":null},{"id":"W2265998000","doi":"10.1063/1.4937491","title":"Hybrid stochastic simulation of reaction-diffusion systems with slow and fast dynamics","year":2015,"lang":"en","type":"article","venue":"The Journal of Chemical Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Partition (number theory); Stochastic simulation; Diffusion; Benchmarking; Reaction–diffusion system; Mathematical optimization; Algorithm; Applied mathematics; Statistical physics; Mathematics; Physics","score_opus":0.008249156107901442,"score_gpt":0.22054300980624336,"score_spread":0.21229385369834192,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2265998000","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":[0.93750364,0.00030630446,0.062052745,0.00002472844,0.00003807217,0.000043155982,0.0000024980209,0.0000013559691,0.000027521746],"genre_scores_gemma":[0.9995498,0.000014815059,0.00008138891,0.000008020935,0.0003009897,3.403577e-7,0.000011796791,0.000010857433,0.000022004248],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994032,0.000041821808,0.00020406261,0.000065892906,0.00020774794,0.00007727392],"domain_scores_gemma":[0.999129,0.000029555438,0.0003310106,0.0001538136,0.00028627325,0.00007035002],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019475687,0.00008260322,0.00016506934,0.0000136686485,0.000017748018,0.000006621106,0.000096030875,0.00003758669,1.7595525e-7],"category_scores_gemma":[0.000029752715,0.000052514475,0.00004688244,0.000060472565,0.00008166393,0.0000058100336,0.000037100708,0.00008619703,2.3174249e-7],"study_design_candidate":"simulation_or_modeling","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":[0.00030191234,0.000046552137,0.00015168308,0.000014003715,0.00011643268,5.285115e-7,0.000049083315,0.48231667,0.5159983,0.000016662965,0.00011664291,0.0008715284],"study_design_scores_gemma":[0.0016454651,0.00064198487,0.00016598159,0.0001177582,0.00065192376,0.00022169988,0.00040241468,0.78965443,0.20497034,0.0011501817,0.00012367207,0.0002541379],"about_ca_topic_score_codex":0.0000042050383,"about_ca_topic_score_gemma":4.5564377e-7,"teacher_disagreement_score":0.31102797,"about_ca_system_score_codex":0.000025103609,"about_ca_system_score_gemma":0.000046462523,"threshold_uncertainty_score":0.2141478},"labels":[],"label_agreement":null},{"id":"W2266613162","doi":"10.1038/ncomms10160","title":"A role of stochastic phenotype switching in generating mosaic endothelial cell heterogeneity","year":2016,"lang":"en","type":"article","venue":"Nature Communications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":113,"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; St. Michael's Hospital; University of Alberta","funders":"National Heart, Lung, and Blood Institute; National Institutes of Health; American Heart Association","keywords":"Phenotype; Biology; Phenotypic switching; Von Willebrand factor; Genetics; Cell biology; Gene; Endothelial stem cell; Immunology; In vitro","score_opus":0.008514241025443674,"score_gpt":0.25491245378986793,"score_spread":0.24639821276442425,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2266613162","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":[0.9844338,0.011117888,0.003907066,0.00014986531,0.000033743287,0.00011486777,0.000029110894,0.000008675972,0.00020495051],"genre_scores_gemma":[0.99420154,0.00017105942,0.0053739795,0.00005577257,0.00007525563,0.000019172969,0.000050631956,0.000016674314,0.000035910154],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99918383,0.00014511083,0.00023258668,0.00019358566,0.00009283753,0.00015202949],"domain_scores_gemma":[0.9984324,0.000048982285,0.00012655069,0.0012695168,0.00008265189,0.000039925017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018640383,0.00010536845,0.00013607464,0.00006281263,0.00008041347,0.000006627615,0.00059309957,0.00020400796,0.0000050318695],"category_scores_gemma":[0.000089270165,0.00008613951,0.00008913966,0.00015051827,0.00005174098,0.0000038033054,0.00030409533,0.00018092516,0.0000034607167],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010126706,0.000059912432,0.0036821205,0.000002573442,0.00002678393,6.242976e-8,0.00003570147,0.00097234285,0.99157983,0.00013816191,0.000047086156,0.0034453173],"study_design_scores_gemma":[0.0016419619,0.00014039695,0.009120757,0.00008558486,0.000128263,0.000007200577,0.00015286528,0.016831607,0.9614363,0.00044744796,0.009424542,0.0005831207],"about_ca_topic_score_codex":0.000018307306,"about_ca_topic_score_gemma":0.0012920458,"teacher_disagreement_score":0.030143557,"about_ca_system_score_codex":0.000022362583,"about_ca_system_score_gemma":0.000060281396,"threshold_uncertainty_score":0.3512667},"labels":[],"label_agreement":null},{"id":"W2290618319","doi":"10.1137/140991820","title":"On Controllability of Delayed Boolean Control Networks","year":2016,"lang":"en","type":"article","venue":"SIAM Journal on Control and Optimization","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":190,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"City University of Hong Kong","keywords":"Controllability; Trajectory; State (computer science); Mathematics; Control theory (sociology); Sequence (biology); Control (management); Computer science; Applied mathematics; Algorithm; Physics","score_opus":0.0029087760431143936,"score_gpt":0.19830803768423555,"score_spread":0.19539926164112115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2290618319","genre_codex":"methods","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":[0.18893902,0.0010367885,0.8087044,0.00075954915,0.00016189487,0.00022079315,0.000019916686,0.000008163019,0.00014947997],"genre_scores_gemma":[0.99801624,0.0005546784,0.00033564595,0.0005971702,0.00035100093,0.0000059612753,0.000008268242,0.000018808183,0.000112219706],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99875045,0.00019045165,0.00040113064,0.00025471995,0.0001792781,0.00022396461],"domain_scores_gemma":[0.9989227,0.00010844199,0.00032673264,0.0002410292,0.0002549209,0.00014619192],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051852973,0.0001759842,0.0003177858,0.00007115266,0.00011171531,0.00002339652,0.00010730986,0.00015629578,0.000042326505],"category_scores_gemma":[0.00017797328,0.000113685346,0.00017099876,0.00007262702,0.000086833774,0.0000074160694,0.000012201249,0.000091445654,0.0000014495001],"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":[0.0026875618,0.00007697709,0.0021060242,0.0000026699856,0.00034500426,0.0000022561446,0.0000035946675,0.9733971,0.015127626,0.00028291062,0.00045787598,0.00551042],"study_design_scores_gemma":[0.043735024,0.006976761,0.008957909,0.00017912454,0.00075950875,0.00008796718,0.000027289008,0.9304906,0.004743714,0.0011213697,0.0020710658,0.00084964256],"about_ca_topic_score_codex":9.5333627e-7,"about_ca_topic_score_gemma":0.0000049744153,"teacher_disagreement_score":0.8090772,"about_ca_system_score_codex":0.000023359748,"about_ca_system_score_gemma":0.000042575863,"threshold_uncertainty_score":0.46359536},"labels":[],"label_agreement":null},{"id":"W2294194070","doi":"10.1142/s0219720016410055","title":"Sequential construction of a model for modular gene expression control, applied to spatial patterning of the<i>Drosophila</i>gene<i>hunchback</i>","year":2016,"lang":"en","type":"article","venue":"Journal of Bioinformatics and Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"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 Victoria; British Columbia Institute of Technology","funders":"National Institute of General Medical Sciences; National Institutes of Health; Russian Foundation for Basic Research","keywords":"Gene regulatory network; Gene; Biology; Computational biology; Cis-regulatory module; Regulation of gene expression; Genetics; Gene expression; Regulator gene; Regulatory sequence; Transcription factor; Translation (biology); Regulator; Gap gene; Transcription (linguistics); Messenger RNA; Promoter","score_opus":0.008403906487245838,"score_gpt":0.22243375229412654,"score_spread":0.2140298458068807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2294194070","genre_codex":"methods","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":[0.47778517,0.000051424362,0.52184516,0.000099819095,0.000062436484,0.0000842386,0.000066289824,6.299036e-7,0.0000048219154],"genre_scores_gemma":[0.9357207,0.000029281833,0.0639583,0.00013043705,0.00012595093,0.000003698333,0.000021751664,0.0000062191993,0.0000036517838],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989938,0.00003228252,0.0006385566,0.00009317231,0.00012895375,0.0001132128],"domain_scores_gemma":[0.9986972,0.00003671789,0.0007608222,0.00011335139,0.00033502257,0.00005688156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023944514,0.00010444938,0.0002652641,0.00007345748,0.000050560044,0.000005345193,0.00013920528,0.000102566875,0.000001671516],"category_scores_gemma":[0.000029608083,0.000063953004,0.00015785765,0.000049403894,0.00012467855,0.0000070434803,0.00007205642,0.000035084027,1.7737611e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002426344,0.000017961076,0.001430543,0.000021599444,0.0001298374,5.8281284e-8,0.000046098874,0.16617657,0.826559,0.0002970751,0.000053328167,0.0050253137],"study_design_scores_gemma":[0.0041972194,0.0007770481,0.0022768225,0.00008810108,0.0001920116,0.00009490984,0.00005150434,0.2735936,0.70895535,0.009274835,0.00024854712,0.0002500421],"about_ca_topic_score_codex":9.662184e-7,"about_ca_topic_score_gemma":0.0000010514414,"teacher_disagreement_score":0.45793554,"about_ca_system_score_codex":0.000010460954,"about_ca_system_score_gemma":0.00010487177,"threshold_uncertainty_score":0.26079276},"labels":[],"label_agreement":null},{"id":"W23013199","doi":"10.1007/b11466","title":"Multimedia Mass Balance Modelling of Two Phthalate Esters by the Regional Population-Based Model (RPM)","year":2002,"lang":"en","type":"book-chapter","venue":"The handbook of environmental chemistry","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trent University","funders":"","keywords":"Phthalate; Balance (ability); Environmental science; Computer science; Medicine; Chemistry; Physical therapy; Organic chemistry","score_opus":0.01306111063011846,"score_gpt":0.19247012021979246,"score_spread":0.17940900958967398,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W23013199","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":[0.621547,0.15152936,0.14835447,0.00058911595,0.00046576996,0.004169223,0.005011566,0.0001594946,0.06817404],"genre_scores_gemma":[0.93340504,0.0009176778,0.0010817695,0.00008447736,0.00016245873,0.000019283612,0.000985494,0.000113271024,0.06323052],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982625,0.000020869453,0.00051400875,0.0005113775,0.0004495513,0.00024169186],"domain_scores_gemma":[0.9983742,0.0000321521,0.000600918,0.00089251756,0.000016541553,0.00008365276],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000114714174,0.0004288714,0.00038851146,0.000017687687,0.00009406855,0.000008037256,0.0004954838,0.0003598633,0.0001859251],"category_scores_gemma":[0.000001357261,0.00034214783,0.00043750578,0.000016495307,0.0004178961,0.000003380192,0.00008477532,0.00023991473,0.000006184479],"study_design_candidate":"simulation_or_modeling","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":[0.00005381979,0.000049560447,0.00073454896,0.000060700408,0.00031381455,0.0000012454757,0.00001620373,0.4620563,0.53576183,0.0000030732747,0.00074336474,0.00020550404],"study_design_scores_gemma":[0.0012114968,0.000046032197,0.000022525284,0.00025096184,0.00053961657,0.0000150149035,0.000014383487,0.75457597,0.2398455,0.00048952154,0.0022475803,0.0007414139],"about_ca_topic_score_codex":0.000011080816,"about_ca_topic_score_gemma":0.0000025688967,"teacher_disagreement_score":0.3118581,"about_ca_system_score_codex":0.000071400165,"about_ca_system_score_gemma":0.000031098465,"threshold_uncertainty_score":0.9999031},"labels":[],"label_agreement":null},{"id":"W2302806166","doi":"10.1063/1.4944952","title":"An adaptive tau-leaping method for stochastic simulations of reaction-diffusion systems","year":2016,"lang":"en","type":"article","venue":"AIP Advances","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mesoscopic physics; Master equation; Reaction–diffusion system; Computer science; Path (computing); Stochastic simulation; Diffusion; Statistical physics; Population; Stochastic process; Mathematical optimization; Applied mathematics; Biological system; Mathematics; Physics; Mathematical analysis","score_opus":0.014004621860751727,"score_gpt":0.30293658425491166,"score_spread":0.2889319623941599,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2302806166","genre_codex":"methods","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":[0.19186746,0.0017060415,0.80604386,0.000026118743,0.00011780881,0.00017712565,0.000033134926,0.000008942614,0.000019524537],"genre_scores_gemma":[0.9892229,0.0000702495,0.010249643,0.000012479653,0.00023012904,0.000029597135,0.00003804136,0.000015560638,0.00013141563],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992419,0.00007141113,0.00019453137,0.00026599038,0.00008818674,0.00013800421],"domain_scores_gemma":[0.9992479,0.000095431016,0.00016729154,0.00027693552,0.00016389311,0.000048568403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001459266,0.00009856385,0.00015651139,0.000047352383,0.000075758806,0.0000051368133,0.0001000136,0.000069414025,0.0000031678585],"category_scores_gemma":[0.000069597336,0.000073291405,0.00007931367,0.00008134369,0.00003938641,0.0000125109345,0.000020668323,0.00001717998,9.2324586e-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":[0.00007620365,0.000029769883,0.00023896078,0.000011839788,0.000060416285,6.8910744e-8,0.000014562857,0.08962384,0.8987218,0.00022332366,0.00004174104,0.0109574795],"study_design_scores_gemma":[0.003683752,0.0036336982,0.0032835377,0.0004348871,0.00071676774,0.000020328405,0.0016699536,0.47788143,0.44321406,0.0044300226,0.059674643,0.0013569165],"about_ca_topic_score_codex":0.000012444619,"about_ca_topic_score_gemma":0.000040902127,"teacher_disagreement_score":0.7973554,"about_ca_system_score_codex":0.000015912281,"about_ca_system_score_gemma":0.000029790737,"threshold_uncertainty_score":0.29887366},"labels":[],"label_agreement":null},{"id":"W2304747814","doi":"","title":"Analysis of a simple gene expression model","year":2012,"lang":"en","type":"dissertation","venue":"Open ULeth Scholarship (OPUS) (University of Lethbridge)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"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":"University of Lethbridge","keywords":"Mathematics; Hypergeometric distribution; Statistical physics; Probability distribution; Noise (video); Stochastic process; Hypergeometric function; Invariant (physics); Invariant measure; Applied mathematics; Mathematical analysis; Statistics; Physics; Computer science; Mathematical physics","score_opus":0.02362911571132187,"score_gpt":0.27357302624677354,"score_spread":0.24994391053545167,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2304747814","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":[0.9934339,0.0013921505,0.0022699477,0.000026201184,0.00008719081,0.00036225608,0.00026682927,0.000009753626,0.002151785],"genre_scores_gemma":[0.97531056,0.00034824756,0.00477859,0.00003419406,0.000066111395,0.0000020524851,0.009299069,0.0000542877,0.010106858],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9974964,0.00030488276,0.0004324156,0.0008200725,0.0005257156,0.00042047934],"domain_scores_gemma":[0.99683017,0.0000250198,0.0010458027,0.0013441035,0.0005137612,0.0002411642],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000920288,0.0004097248,0.0010946606,0.000568846,0.00025314378,0.000042072003,0.0017842875,0.00082543364,0.00026767672],"category_scores_gemma":[0.000057414356,0.0005144532,0.0009205347,0.00091862923,0.000113392874,0.000059846963,0.0005901004,0.00038601804,0.000012058578],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065632677,0.00022259478,0.020265492,0.00015062881,0.0038195592,0.0000058844003,0.0005206,0.010356701,0.9597475,0.00003532978,0.0018845965,0.002334819],"study_design_scores_gemma":[0.002075608,0.00024916066,0.21856678,0.00024898592,0.016575456,0.0000038777684,0.0022725496,0.005354993,0.7457888,0.000144459,0.006887136,0.0018321913],"about_ca_topic_score_codex":0.00044399762,"about_ca_topic_score_gemma":0.0011282506,"teacher_disagreement_score":0.21395867,"about_ca_system_score_codex":0.0000534784,"about_ca_system_score_gemma":0.00029324216,"threshold_uncertainty_score":0.9997307},"labels":[],"label_agreement":null},{"id":"W2318071399","doi":"10.1049/iet-syb.2015.0077","title":"Minimum steering node set of complex networks and its applications to biomolecular networks","year":2016,"lang":"en","type":"article","venue":"IET Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Controllability; Biological network; Node (physics); Network controllability; Complex network; Computer science; Set (abstract data type); Graph; Complex system; Topology (electrical circuits); State (computer science); Biomolecule; Network structure; Distributed computing; Theoretical computer science; Bioinformatics; Artificial intelligence; Mathematics; Algorithm; Nanotechnology; Biology; Engineering; Centrality","score_opus":0.017800677285560774,"score_gpt":0.26515448042997597,"score_spread":0.24735380314441519,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2318071399","genre_codex":"methods","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":[0.42631555,0.0081472,0.56418437,0.00021126999,0.00023548171,0.000661556,0.000074791526,0.000027924007,0.00014184591],"genre_scores_gemma":[0.9983874,0.00031742788,0.00018808774,0.000095738,0.0005414288,0.00013361183,0.00010780992,0.000029634977,0.00019885972],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99845445,0.00016662627,0.0004174606,0.0005201296,0.000065976084,0.00037536686],"domain_scores_gemma":[0.9989719,0.000042030028,0.00016625578,0.00052346237,0.00013514239,0.00016124961],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026363766,0.00021136436,0.00037227015,0.00008245303,0.00006714756,0.000010898921,0.00025840782,0.00030243563,0.000008083859],"category_scores_gemma":[0.000023641682,0.00016452969,0.000098511046,0.00021015726,0.00009667818,0.0000024515032,0.00021155333,0.00004351841,0.000008541187],"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":[0.000035987967,0.000015565949,0.007838009,0.000031696538,0.00024838955,0.0000010607508,0.000009268604,0.014908515,0.9731078,0.00044681132,0.0011308691,0.0022260011],"study_design_scores_gemma":[0.0039618863,0.0018201795,0.013343574,0.00038906885,0.0005443825,0.0002766245,0.00026279734,0.122952566,0.10957067,0.00010535768,0.74400944,0.0027634895],"about_ca_topic_score_codex":0.000017126982,"about_ca_topic_score_gemma":0.000018917734,"teacher_disagreement_score":0.86353713,"about_ca_system_score_codex":0.000016184049,"about_ca_system_score_gemma":0.000021709906,"threshold_uncertainty_score":0.6709326},"labels":[],"label_agreement":null},{"id":"W2323352121","doi":"10.1103/physreve.89.052708","title":"Coherent feedforward transcriptional regulatory motifs enhance drug resistance","year":2014,"lang":"en","type":"article","venue":"Physical Review E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"National Institutes of Health; Government of Ontario","keywords":"Gene regulatory network; Phenotype; Gene; Biology; Feed forward; Computational biology; Inheritance (genetic algorithm); Genetics; Computer science; Gene expression","score_opus":0.006256615604538342,"score_gpt":0.2568582165559898,"score_spread":0.25060160095145145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2323352121","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":[0.8615292,0.12367868,0.006703507,0.0020951245,0.0002047928,0.00055873155,0.000014526804,0.000053286025,0.0051621795],"genre_scores_gemma":[0.9890604,0.0051965043,0.00034644158,0.0009873337,0.00068111415,0.00006188168,0.00008683829,0.00002844522,0.003551021],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985086,0.00017645449,0.00026568578,0.00048699675,0.0002989443,0.00026333646],"domain_scores_gemma":[0.99898815,0.000017207505,0.000116053794,0.00064526545,0.0000965864,0.00013674087],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030020394,0.00021182715,0.00037672996,0.000015562777,0.000073671625,0.000012097803,0.00026522353,0.000039746068,0.000049217717],"category_scores_gemma":[0.000059323647,0.00018949254,0.00039168622,0.0001519099,0.00009098424,0.0000043204986,0.000047858015,0.00009752605,0.000090089285],"study_design_candidate":"not_applicable","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":[0.00007666809,0.00044897248,0.00053116045,0.0021460615,0.00038576478,0.0000016034802,0.00005927027,0.00040956837,0.8309948,0.0091027515,0.13105522,0.024788147],"study_design_scores_gemma":[0.00026864314,0.00005506635,0.004423826,0.00068064133,0.00026779337,0.0000019873103,0.0000035438682,0.00035121702,0.07301463,0.0022599024,0.9181725,0.0005002826],"about_ca_topic_score_codex":0.0000013286177,"about_ca_topic_score_gemma":0.00002656839,"teacher_disagreement_score":0.78711724,"about_ca_system_score_codex":0.000021555245,"about_ca_system_score_gemma":0.00003644247,"threshold_uncertainty_score":0.77272815},"labels":[],"label_agreement":null},{"id":"W2328206864","doi":"10.1021/sb500165g","title":"A Low Cost, Customizable Turbidostat for Use in Synthetic Circuit Characterization","year":2014,"lang":"en","type":"article","venue":"ACS Synthetic Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":133,"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":"Institut National de la Santé et de la Recherche Médicale; Rice University; National Institute of General Medical Sciences; Rita Allen Foundation; Canadian Institute for Advanced Research; California Institute of Technology; National Human Genome Research Institute; Allen Foundation; Paul G. Allen Family Foundation; National Institutes of Health; National Science Foundation","keywords":"Synthetic biology; Flexibility (engineering); Computer science; Characterization (materials science); Electronic circuit; Biochemical engineering; Circuit design; Multiplexing; Software; Embedded system; Nanotechnology; Engineering; Electrical engineering; Telecommunications; Materials science; Biology; Mathematics","score_opus":0.013817171516287398,"score_gpt":0.23194821459381154,"score_spread":0.21813104307752415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2328206864","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":[0.92794335,0.00010341336,0.07078747,0.00017570355,0.0002369136,0.00053647213,0.000052761225,0.00002301731,0.00014092369],"genre_scores_gemma":[0.99742997,0.000114576076,0.00043626135,0.00037211875,0.00020607926,0.00019726623,0.0006725279,0.000046519595,0.00052471226],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998182,0.00025591976,0.0003562888,0.000642659,0.00006433324,0.0004988062],"domain_scores_gemma":[0.9989168,0.00010956492,0.0001531007,0.0006345282,0.000094883515,0.00009111145],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004545982,0.00023917982,0.00035383846,0.00013368814,0.00007591864,0.000029373208,0.00026266495,0.00036680378,0.000030420464],"category_scores_gemma":[0.00033197954,0.00023036967,0.00013764342,0.00016501392,0.00015007069,0.000007070137,0.00008959512,0.0000863982,0.000028013734],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011205469,0.00011612548,0.008908762,0.00003264534,0.00007896656,8.254718e-7,0.000030060717,0.00046503643,0.9528842,0.0008636055,0.00018985671,0.036317844],"study_design_scores_gemma":[0.00290087,0.0007277591,0.009516253,0.00011565306,0.00023935911,0.00006561897,0.000043040145,0.016687628,0.6722062,0.0018717631,0.29431137,0.0013144168],"about_ca_topic_score_codex":0.00001985805,"about_ca_topic_score_gemma":0.00007921416,"teacher_disagreement_score":0.29412153,"about_ca_system_score_codex":0.000033066597,"about_ca_system_score_gemma":0.000050605897,"threshold_uncertainty_score":0.9394202},"labels":[],"label_agreement":null},{"id":"W2328667583","doi":"10.4208/cicp.130612.121012a","title":"An Accelerated Method for Simulating Population Dynamics","year":2013,"lang":"en","type":"article","venue":"Communications in Computational Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"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 Ottawa","funders":"","keywords":"Benchmark (surveying); Monte Carlo method; Population; Computer science; Dynamics (music); Statistical physics; Algorithm; Mathematical optimization; Mathematics; Statistics; Physics","score_opus":0.04093858986237402,"score_gpt":0.3706384571857729,"score_spread":0.32969986732339884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2328667583","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":[0.26805252,0.00007256747,0.73114175,0.00025135273,0.000022394837,0.00032618677,0.000014779801,0.000017422719,0.00010100912],"genre_scores_gemma":[0.71074945,0.0000051942566,0.28453907,0.00009460343,0.00006667746,0.00008764279,0.004423216,0.000016540751,0.000017600316],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991497,0.00015770401,0.00026186858,0.00021450824,0.000086462096,0.00012976224],"domain_scores_gemma":[0.99866825,0.0001278043,0.000117303745,0.00074222276,0.0003056607,0.000038735394],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018012366,0.00010474053,0.00011879127,0.000045003642,0.00017387621,0.000049768463,0.00042499002,0.00007260879,0.0000044468693],"category_scores_gemma":[0.000035788205,0.00012316363,0.0000662612,0.00025226627,0.00003463189,0.000019550056,0.000114979164,0.00007237831,0.0000041472376],"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":[0.0000040602818,0.00010212102,0.008330901,0.000004625626,0.000029090617,1.1959116e-8,0.000025423155,0.9500781,0.002194459,0.006112829,0.00007683445,0.03304152],"study_design_scores_gemma":[0.00023547438,0.000030435762,0.02359664,0.0000048661304,0.000012442446,4.5492666e-7,0.000042761916,0.93787944,0.00015850192,0.03780725,0.00010513762,0.00012659664],"about_ca_topic_score_codex":0.0000856025,"about_ca_topic_score_gemma":0.00012362697,"teacher_disagreement_score":0.4466027,"about_ca_system_score_codex":0.000051345363,"about_ca_system_score_gemma":0.0000402035,"threshold_uncertainty_score":0.5022467},"labels":[],"label_agreement":null},{"id":"W2329568427","doi":"10.1242/jeb.059725","title":"Metabolism in the age of ‘omes’","year":2012,"lang":"en","type":"review","venue":"Journal of Experimental Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":68,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Flux (metallurgy); Hierarchy; Biology; Metabolism; Enzyme; Protein expression; Computational biology; Messenger RNA; Energy metabolism; Gene; Biochemistry; Chemistry","score_opus":0.034735911291467414,"score_gpt":0.34180772786285774,"score_spread":0.3070718165713903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2329568427","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0043973327,0.9948681,0.000010684861,0.000008982807,0.0003412048,0.0001379106,0.000008877044,6.2846897e-7,0.00022626722],"genre_scores_gemma":[0.036194738,0.9625234,0.00022695551,0.00006227606,0.0008353522,0.000011009631,0.00009263481,0.000021341239,0.000032277865],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99795264,0.0006172462,0.0009030881,0.0001680582,0.00011853083,0.00024041922],"domain_scores_gemma":[0.9985968,0.00003549106,0.00092231965,0.0003543671,0.000042749918,0.00004825506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068925164,0.00026025597,0.0012815756,0.00018665292,0.000020225832,0.0000062208937,0.00063692464,0.00038075796,0.000039966002],"category_scores_gemma":[0.000021483454,0.0001505822,0.00090196385,0.00018954776,0.00015175436,0.0000029340624,0.0001273797,0.00023844864,0.0000038209005],"study_design_candidate":"not_applicable","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":[0.00019096072,0.0018651462,0.0004661029,0.0015589762,0.0051720296,0.00011929089,0.00097212626,0.00000843127,0.5728475,0.0007458434,0.0042470363,0.41180658],"study_design_scores_gemma":[0.00020647864,0.0002150891,0.000017067287,0.00016264491,0.00049971405,0.000266592,0.00011432947,1.1067653e-7,0.004790582,0.000009308906,0.99357617,0.00014188532],"about_ca_topic_score_codex":0.0000035762355,"about_ca_topic_score_gemma":0.0000026832095,"teacher_disagreement_score":0.98932916,"about_ca_system_score_codex":0.000025927904,"about_ca_system_score_gemma":0.00009877672,"threshold_uncertainty_score":0.61405635},"labels":[],"label_agreement":null},{"id":"W2330875406","doi":"10.1126/science.aac9786","title":"Stochastic activation of a DNA damage response causes cell-to-cell mutation rate variation","year":2016,"lang":"en","type":"article","venue":"Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":172,"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":"Fonds de recherche du Québec – Nature et technologies; Biotechnology and Biological Sciences Research Council; National Institute of General Medical Sciences; Wellcome; Medical Research Council; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Wellcome Trust","keywords":"Mutagenesis; DNA repair; DNA damage; DNA; Mutation; Cell; Biology; Molecular biology; Cell biology; Genetics; Chemistry; Gene","score_opus":0.0071565120610315655,"score_gpt":0.2379964864765034,"score_spread":0.23083997441547183,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2330875406","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":[0.9027481,0.000010831758,0.09693167,0.00012409591,0.000047096866,0.000093683004,0.0000033485217,0.000004879808,0.00003626236],"genre_scores_gemma":[0.9988328,0.0000021127796,0.0005787231,0.00004413366,0.00003405903,0.000007003045,0.0000035811172,0.0000059821296,0.00049157435],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991668,0.00009287018,0.0001309639,0.0002816112,0.00018000064,0.00014778877],"domain_scores_gemma":[0.99931604,0.000039150236,0.00011356434,0.00028589138,0.00018303872,0.00006229437],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080116634,0.00006800728,0.00006476511,0.00012264529,0.000078807025,0.000014105796,0.00017245539,0.000037885435,0.000010221473],"category_scores_gemma":[0.00034303905,0.00005319894,0.000028419392,0.00045515486,0.000116434094,0.000013199791,0.000060421033,0.000014462549,0.000013834274],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010687869,0.000017592227,0.000081901686,0.0000026997411,0.0000026754624,1.882282e-7,0.00009203101,0.0056917355,0.99370533,0.0000066868342,0.000031043786,0.00026125027],"study_design_scores_gemma":[0.00019269099,0.00013070063,0.03648703,0.0000091649945,0.00001033026,4.6214285e-7,0.00002955427,0.0006762023,0.96226645,0.000051771098,0.00007098053,0.00007464162],"about_ca_topic_score_codex":0.000004294217,"about_ca_topic_score_gemma":0.0000037584048,"teacher_disagreement_score":0.09635295,"about_ca_system_score_codex":0.000031127933,"about_ca_system_score_gemma":0.00020197037,"threshold_uncertainty_score":0.21693897},"labels":[],"label_agreement":null},{"id":"W2331964784","doi":"10.1101/pdb.prot088799","title":"Liquid Growth of Arrayed Fluorescently Tagged <i>Saccharomyces cerevisiae</i> Strains for Live-Cell High-Throughput Microscopy Screens","year":2016,"lang":"en","type":"article","venue":"Cold Spring Harbor Protocols","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"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":"Saccharomyces cerevisiae; Throughput; Yeast; Live cell imaging; Microscopy; Computational biology; Biology; High-throughput screening; Cell biology; Cell; Computer science; Genetics; Optics; Physics","score_opus":0.011472120127904155,"score_gpt":0.2552856604897873,"score_spread":0.24381354036188313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2331964784","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":[0.90127903,0.0005232361,0.027990168,0.00035908827,0.00011682503,0.06930808,0.00026306722,0.00008451367,0.000075975244],"genre_scores_gemma":[0.9523199,0.000062721025,0.011088247,0.000100977,0.00045673345,0.035607316,0.000010629902,0.00009510625,0.00025833162],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99773926,0.00010432644,0.0005834457,0.00075920764,0.00023860898,0.0005751308],"domain_scores_gemma":[0.9981107,0.000036286197,0.0004218237,0.00090121164,0.0003475385,0.00018239887],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003940913,0.00036661144,0.00050573517,0.00007511263,0.00012478435,0.00003984599,0.00058641675,0.00025011483,0.00004277487],"category_scores_gemma":[0.00010021073,0.0003057401,0.00036474067,0.0001586733,0.00017235492,0.000013867277,0.00018641131,0.00008213004,0.000016562484],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041091934,0.00017073807,0.0032384407,0.00028796686,0.00015623683,0.0000014568018,0.00000951955,0.000012379301,0.9939353,0.00062854687,0.0010702813,0.000078214965],"study_design_scores_gemma":[0.00228998,0.0010309954,0.001718637,0.00029097445,0.00008096236,3.07206e-7,0.0000060225525,0.000013423977,0.97446513,0.000016204862,0.019698242,0.00038913297],"about_ca_topic_score_codex":0.000020644875,"about_ca_topic_score_gemma":0.000011556902,"teacher_disagreement_score":0.05104089,"about_ca_system_score_codex":0.00004446554,"about_ca_system_score_gemma":0.00019334274,"threshold_uncertainty_score":0.99993944},"labels":[],"label_agreement":null},{"id":"W2335093401","doi":"10.4161/cc.9.19.13380","title":"A swim in the same cytoplasm is no cure for nonconformity","year":2010,"lang":"en","type":"letter","venue":"Cell Cycle","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"National Cancer Institute; McGill University","keywords":"Nonconformity; Biology; Cytoplasm; Cell cycle; Cell biology; Cell; Genetics","score_opus":0.006703349014093828,"score_gpt":0.22390407895373324,"score_spread":0.2172007299396394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2335093401","genre_codex":"empirical","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.622374,0.0026424231,0.00048492002,0.3457707,0.0019291991,0.0024951843,0.0005344708,0.00004465539,0.023724452],"genre_scores_gemma":[0.1132716,0.0003034615,0.0011470007,0.84161466,0.013622771,0.00032667,0.0028144205,0.00016223844,0.026737196],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99858814,0.00005774778,0.00025725213,0.0004986645,0.00018038301,0.00041779524],"domain_scores_gemma":[0.9987161,0.000035327066,0.00015828155,0.00096797734,0.00008540205,0.00003686996],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00025239403,0.00029043833,0.00028883744,0.000053260323,0.000084958214,0.00004410575,0.0006303442,0.0017350477,0.000088835994],"category_scores_gemma":[0.000020923495,0.0002268124,0.00038083544,0.00009315817,0.00007438623,0.0000020818757,0.00009804072,0.0010978641,0.00009178894],"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":[0.000012533829,0.000022334163,0.00021057656,0.00007552633,0.000043195167,0.00000868483,0.00005502941,0.000024728668,0.01293829,7.912282e-7,0.98634785,0.00026047888],"study_design_scores_gemma":[0.00031522367,0.00006677392,0.00009310283,0.000007938209,0.00008238374,0.000007540589,0.0000152225975,0.00021099702,0.018606119,0.00009825335,0.98021144,0.00028501544],"about_ca_topic_score_codex":0.00003260524,"about_ca_topic_score_gemma":0.00017284983,"teacher_disagreement_score":0.5091024,"about_ca_system_score_codex":0.000015941248,"about_ca_system_score_gemma":0.00010458898,"threshold_uncertainty_score":0.9995609},"labels":[],"label_agreement":null},{"id":"W2336625144","doi":"","title":"Modeling pathways of differentiation in genetic regulatory networks with Boolean networks: Research Articles","year":2005,"lang":"en","type":"article","venue":"Complexity","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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 Calgary","funders":"","keywords":"Attractor; Observable; Cellular differentiation; Nonlinear system; Computer science; Gene regulatory network; Perturbation (astronomy); Gene; Topology (electrical circuits); Biology; Computational biology; Mathematics; Physics; Genetics; Gene expression; Mathematical analysis","score_opus":0.061934762255417816,"score_gpt":0.27942720585606573,"score_spread":0.2174924436006479,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2336625144","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":[0.9129031,0.0019908505,0.084775835,0.00003882646,0.000022545502,0.00016815249,0.0000017669737,0.000012107189,0.00008683459],"genre_scores_gemma":[0.99658656,0.00012926561,0.0027603598,0.000029052824,0.00035863416,0.000016892453,0.000057353132,0.00002881922,0.0000330634],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99819475,0.0002710419,0.00038059027,0.00041932228,0.00029266434,0.00044163925],"domain_scores_gemma":[0.99897873,0.000016849883,0.00008524221,0.0006278029,0.00019205963,0.00009931795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005720703,0.000162798,0.00024195584,0.00012566347,0.000107001106,0.000020542353,0.0002543772,0.00014412423,0.00002048121],"category_scores_gemma":[0.000020087735,0.00015345533,0.00008532319,0.00038230568,0.0002217559,0.000006505455,0.00016187191,0.0001889823,0.0000020004754],"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":[0.000101218924,0.00009893191,0.027590107,0.000010407852,0.000047439447,0.0000011795831,0.000054511187,0.957586,0.009944574,0.00018619777,0.00010025404,0.004279181],"study_design_scores_gemma":[0.00042540935,0.00011006931,0.0819801,0.00003235848,0.00001667287,0.0000032117825,0.00007650601,0.9127483,0.0040134965,0.00036407672,0.00006551006,0.00016433313],"about_ca_topic_score_codex":0.00005194244,"about_ca_topic_score_gemma":0.0017636877,"teacher_disagreement_score":0.083683476,"about_ca_system_score_codex":0.000049727678,"about_ca_system_score_gemma":0.000053250744,"threshold_uncertainty_score":0.62577266},"labels":[],"label_agreement":null},{"id":"W2342621714","doi":"10.1021/acssynbio.5b00215","title":"Sharing Structure and Function in Biological Design with SBOL 2.0","year":2016,"lang":"en","type":"article","venue":"ACS Synthetic Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":86,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Institute for Research in Immunology and Cancer","funders":"Division of Biological Infrastructure; Engineering and Physical Sciences Research Council","keywords":"Synthetic biology; Workflow; Function (biology); Computer science; Field (mathematics); Set (abstract data type); Software engineering; Software; Systems biology; Computational biology; Systems engineering; Data science; Engineering; Biology; Genetics; Database; Programming language","score_opus":0.01349545585732859,"score_gpt":0.21688710856147525,"score_spread":0.20339165270414666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2342621714","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":[0.9807512,0.0007563708,0.018079825,0.00020101409,0.00004247169,0.0001120525,0.0000049569535,0.00001103718,0.000041059284],"genre_scores_gemma":[0.9987445,0.00022358795,0.00073935563,0.000093570874,0.00008313004,0.000015020854,0.000013804318,0.0000129058,0.00007413961],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99894035,0.00012408516,0.0001464368,0.000497777,0.000034581288,0.00025677317],"domain_scores_gemma":[0.99954224,0.00003557357,0.000055874014,0.00028735097,0.000026902031,0.000052055162],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016848717,0.00015070688,0.0001770827,0.00005921398,0.000039257688,0.0000066825783,0.00012879295,0.0002723793,0.000041012707],"category_scores_gemma":[0.000048255642,0.0000834593,0.000026802842,0.000086841734,0.00021279317,0.0000023992457,0.00010418345,0.000054659926,0.0000040886766],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017050326,0.000012859507,0.13433011,0.0000024631108,0.00005595976,0.0000017877945,0.00000724674,0.000056641016,0.847748,0.0003078523,0.000026849852,0.017279739],"study_design_scores_gemma":[0.0031790496,0.0034514512,0.18219997,0.00010809601,0.00016758934,0.0003056011,0.00008035441,0.00027110355,0.77868855,0.0142340185,0.016097886,0.0012163076],"about_ca_topic_score_codex":0.000006706009,"about_ca_topic_score_gemma":0.000039911243,"teacher_disagreement_score":0.06905942,"about_ca_system_score_codex":0.0000116885385,"about_ca_system_score_gemma":0.000021203017,"threshold_uncertainty_score":0.34033713},"labels":[],"label_agreement":null},{"id":"W2369326609","doi":"","title":"Reconstruction of genetic regulatory network from omics data","year":2010,"lang":"en","type":"article","venue":"China Journal of Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Science North","funders":"","keywords":"Gene regulatory network; Bayesian network; Computational biology; Computer science; Biomedicine; Biological network; Artificial life; Systems biology; Biology; Gene; Theoretical computer science; Artificial intelligence; Data science; Genetics","score_opus":0.007905341687873928,"score_gpt":0.217805065736015,"score_spread":0.20989972404814106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2369326609","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":[0.98791474,0.0009963589,0.009903813,0.00003087053,0.0008664381,0.000055686603,0.00003952797,0.0000031612788,0.0001894274],"genre_scores_gemma":[0.8498212,0.00052064663,0.14823066,0.00003836605,0.001232835,2.7321354e-7,0.00011626405,0.000017195469,0.000022533495],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9985074,0.00003512451,0.00093635736,0.00011676533,0.00022566969,0.00017869308],"domain_scores_gemma":[0.99752825,0.00001590174,0.0011689939,0.0009909881,0.00017918379,0.00011666487],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005194766,0.00014654007,0.00030483416,0.000074668416,0.000057341906,0.000022649925,0.0006862838,0.00019898277,0.000032665586],"category_scores_gemma":[0.000102024205,0.0001288954,0.00015717227,0.00013761336,0.00014739213,0.000025601763,0.0002150956,0.00024574003,0.000002722087],"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":[0.00041760496,0.00019985442,0.1552691,0.00017813391,0.002293116,0.000010728953,0.0005433617,0.03837418,0.3759188,0.00012354123,0.032723647,0.3939479],"study_design_scores_gemma":[0.005109032,0.0013960287,0.49948516,0.00040968915,0.002230246,0.0027164184,0.00088894274,0.21392024,0.20024359,0.005513108,0.06623985,0.0018476858],"about_ca_topic_score_codex":0.000004598709,"about_ca_topic_score_gemma":0.000022619899,"teacher_disagreement_score":0.39210021,"about_ca_system_score_codex":0.000008850794,"about_ca_system_score_gemma":0.00017703018,"threshold_uncertainty_score":0.52562016},"labels":[],"label_agreement":null},{"id":"W2395638817","doi":"10.1088/1478-3975/12/6/060401","title":"The eighth q-bio conference: meeting report and special issue preface","year":2015,"lang":"en","type":"article","venue":"Physical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Hillsborough Hospital","funders":"National Institute of General Medical Sciences; University of California, San Diego; National Institutes of Health; University of Pittsburgh","keywords":"Library science; Engineering ethics; Computer science; Engineering","score_opus":0.015927486235927314,"score_gpt":0.2751102658754262,"score_spread":0.2591827796394989,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2395638817","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":[0.9885599,0.00064422784,0.00013307446,0.0007048397,0.00019465157,0.00009470819,0.0000036440458,0.000012780206,0.009652169],"genre_scores_gemma":[0.9922245,0.00009019389,0.00010233404,0.00006580238,0.005640158,0.000010821337,0.00006451798,0.000010018564,0.0017916417],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99903774,0.00012024574,0.0001590604,0.0003585797,0.00007554808,0.0002488169],"domain_scores_gemma":[0.9993121,0.000027236967,0.000096416945,0.00033470418,0.00011083794,0.00011869135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002512522,0.00013152014,0.00017682204,0.000010932799,0.00011524571,0.000024422707,0.00016329586,0.000104995685,0.0000073126275],"category_scores_gemma":[0.00013534124,0.00008709932,0.000068120906,0.00006546491,0.0002911624,0.0000018501883,0.00019754887,0.00007994229,0.000023958724],"study_design_candidate":"not_applicable","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":[0.00038646793,0.00025434268,0.048186734,0.000017439319,0.00081369036,0.000049531518,0.0005917802,0.00021298943,0.7426222,0.011190538,0.1508442,0.044830065],"study_design_scores_gemma":[0.00040043276,0.0003620909,0.0017703392,0.000004145471,0.00007102685,0.00007471527,0.00016848231,0.00063228374,0.067049794,0.0069667622,0.922214,0.00028592962],"about_ca_topic_score_codex":0.0000116101,"about_ca_topic_score_gemma":0.00003484246,"teacher_disagreement_score":0.7713698,"about_ca_system_score_codex":0.0000088248835,"about_ca_system_score_gemma":0.00006449959,"threshold_uncertainty_score":0.3551807},"labels":[],"label_agreement":null},{"id":"W2399555112","doi":"10.1103/physreve.93.012402","title":"Automated inference procedure for the determination of cell growth parameters","year":2016,"lang":"en","type":"article","venue":"Physical review. E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Impact; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Inference; Metric (unit); Context (archaeology); Population; Bayesian probability; Process (computing); Data mining; Experimental data; Bayes' theorem; Statistics; Artificial intelligence; Mathematics","score_opus":0.012068728955304062,"score_gpt":0.3031837855899401,"score_spread":0.291115056634636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2399555112","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":[0.96669406,0.0064898175,0.025055267,0.00082688284,0.00004146759,0.0007386091,0.0000172694,0.0000283986,0.00010822659],"genre_scores_gemma":[0.99574965,0.0033408343,0.0005475855,0.00013788525,0.000060746093,0.00008569063,0.000010790548,0.000009194203,0.000057609355],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99945885,0.000037528076,0.00013926599,0.00016843562,0.00008522573,0.00011068924],"domain_scores_gemma":[0.99939376,0.000090330235,0.00012219274,0.00023898271,0.00012579342,0.000028930272],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010726934,0.00008677054,0.00015713315,0.0000084412795,0.000026443524,0.0000033474407,0.00016067602,0.000026541013,0.0000021916023],"category_scores_gemma":[0.00026211754,0.000044669647,0.00016808503,0.00008956471,0.000054759537,0.0000025164165,0.000036246875,0.00001751966,0.0000045350284],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013039825,0.000065491826,0.00054570194,0.00050921954,0.000040169918,7.398048e-8,0.000008493983,0.000011707796,0.9760525,0.00015973399,0.002085003,0.020508844],"study_design_scores_gemma":[0.00024344953,0.00017734067,0.0015805855,0.00026521544,0.00025412082,6.8735295e-7,0.000002703563,0.006609932,0.9869819,0.0010260623,0.002708067,0.00014989871],"about_ca_topic_score_codex":0.0000010292792,"about_ca_topic_score_gemma":0.0000016570701,"teacher_disagreement_score":0.029055603,"about_ca_system_score_codex":0.000005599868,"about_ca_system_score_gemma":0.000030292655,"threshold_uncertainty_score":0.18215753},"labels":[],"label_agreement":null},{"id":"W2402390708","doi":"10.1103/physreve.92.022713","title":"Effect and evolution of gene expression noise on the fitness landscape","year":2015,"lang":"en","type":"article","venue":"Physical Review E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"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":"Laufer Center for Physical and Quantitative Biology, Stony Brook University; Natural Sciences and Engineering Research Council of Canada","keywords":"Fitness landscape; Expression (computer science); Genetic Fitness; Fitness function; Gene expression; Noise (video); Population; Biology; Gene; Regulation of gene expression; Fitness approximation; Computer science; Genetics; Artificial intelligence; Genetic algorithm; Machine learning; Medicine","score_opus":0.0098785323425416,"score_gpt":0.2717897955603197,"score_spread":0.2619112632177781,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2402390708","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":[0.9631724,0.03614985,0.00014730057,0.00011877349,0.000018008841,0.00014863549,0.0000019080246,0.0000027602302,0.00024041893],"genre_scores_gemma":[0.9981908,0.0014922933,0.000022401662,0.00007732423,0.00015426849,0.000020527328,0.000013688429,0.000006461884,0.000022205064],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993919,0.00017727994,0.00008646583,0.00015022502,0.000117405354,0.00007669752],"domain_scores_gemma":[0.99953413,0.00002978418,0.00006035373,0.00027953007,0.00004339099,0.000052809533],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027532602,0.0000815262,0.00017470174,0.000007299977,0.0000210422,0.0000029423904,0.00008392644,0.000022263173,0.000002746602],"category_scores_gemma":[0.00012435194,0.000045612218,0.00008727104,0.00007769408,0.000036074263,0.0000012516914,0.000047353475,0.000035165533,0.0000068188997],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007979993,0.000099161996,0.0035901018,0.00041667462,0.00005970045,5.5009946e-7,0.000020571757,0.00026161398,0.9786509,0.00027038011,0.008305994,0.008244537],"study_design_scores_gemma":[0.00046053831,0.00079346594,0.0033472767,0.00065113534,0.00025497598,0.0000037321963,0.000010004436,0.0012376811,0.98552394,0.0003534481,0.0071633337,0.00020044952],"about_ca_topic_score_codex":0.0000012839212,"about_ca_topic_score_gemma":3.6093186e-7,"teacher_disagreement_score":0.03501848,"about_ca_system_score_codex":0.0000053748395,"about_ca_system_score_gemma":0.000015256099,"threshold_uncertainty_score":0.18600123},"labels":[],"label_agreement":null},{"id":"W2403610646","doi":"10.1007/978-1-61779-361-5_12","title":"Algorithms for Systematic Identification of Small Subgraphs","year":2011,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Institute for Cancer Research","funders":"Canadian Institutes of Health Research","keywords":"Biological network; Identification (biology); Computer science; Computational biology; Strengths and weaknesses; Graph; Task (project management); Data science; Artificial intelligence; Machine learning; Theoretical computer science; Biology; Engineering","score_opus":0.038631165569062535,"score_gpt":0.3562136608874269,"score_spread":0.31758249531836436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2403610646","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08007814,0.0014918452,0.9176418,0.000007073553,0.000119553406,0.00055250013,0.000007869921,0.000006809179,0.00009436961],"genre_scores_gemma":[0.20750733,0.00004041191,0.7919554,0.00004562856,0.000029250503,0.00024631957,0.00006678031,0.000026585149,0.00008229136],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9977253,0.00091189175,0.0006516535,0.00042202405,0.00004461126,0.0002445198],"domain_scores_gemma":[0.9988391,0.000050334886,0.00031464183,0.00061591563,0.00013779836,0.000042226813],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020079443,0.00016112419,0.00041116113,0.00018381613,0.00002353398,0.000003750422,0.00032164284,0.0002585645,0.000005495737],"category_scores_gemma":[0.0003930452,0.00015175612,0.00025233073,0.00024893068,0.00012014906,0.000001176848,0.000077079916,0.000052396543,0.0000010054664],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028600833,0.00005433334,0.0019363125,0.0005947167,0.0001564992,8.8271383e-7,0.00005475043,0.00006321693,0.99447036,0.0014693232,0.00000509131,0.001165895],"study_design_scores_gemma":[0.00030561516,0.00019135165,0.0007038007,0.00006433087,0.0001085741,0.000006092335,0.00005521839,0.0012529194,0.9910726,0.006002232,0.00006460237,0.00017268129],"about_ca_topic_score_codex":0.0000159496,"about_ca_topic_score_gemma":0.000020424359,"teacher_disagreement_score":0.12742919,"about_ca_system_score_codex":0.000010427135,"about_ca_system_score_gemma":0.000031086664,"threshold_uncertainty_score":0.6188435},"labels":[],"label_agreement":null},{"id":"W2411164352","doi":"10.1007/978-1-61779-197-0_9","title":"Array-Based Synthetic Genetic Screens to Map Bacterial Pathways and Functional Networks in Escherichia coli","year":2011,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Epistasis; Genetic Fitness; Mutant; Biology; Gene; Phenotype; Genetic screen; Genetics; Computational biology; Function (biology); Mutation","score_opus":0.023117125593077218,"score_gpt":0.28227603036319865,"score_spread":0.25915890477012143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2411164352","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4391808,0.0006499313,0.5596422,0.000036470115,0.00018670883,0.00019256031,0.0000044101944,0.000008120952,0.00009884073],"genre_scores_gemma":[0.48524734,0.000026677766,0.51393867,0.00047410233,0.00011346423,0.00008814574,0.00005798775,0.000035620556,0.000017991939],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99679184,0.001354436,0.00044144513,0.00080941804,0.000074749856,0.00052810746],"domain_scores_gemma":[0.9990819,0.00004666529,0.000100176025,0.00055263424,0.000055192195,0.00016341657],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00093815423,0.00030360703,0.00040808474,0.00022945748,0.00004538474,0.000013307794,0.00022653156,0.00044186544,0.00008643403],"category_scores_gemma":[0.00014887609,0.00031491375,0.00012797673,0.00034465294,0.0001825947,0.0000020054463,0.00016395649,0.00018535332,0.0000050551585],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023211152,0.00007413148,0.012784741,0.000008779492,0.000055997887,0.000016875822,0.000027999726,0.00490897,0.97814465,0.00013808561,0.000028062157,0.0035795993],"study_design_scores_gemma":[0.002026276,0.0010681023,0.087477975,0.000047862508,0.0001192703,0.000022258473,0.000065712586,0.0067957975,0.89237475,0.0019290954,0.0069589075,0.0011139815],"about_ca_topic_score_codex":0.00006051325,"about_ca_topic_score_gemma":0.00016874737,"teacher_disagreement_score":0.085769884,"about_ca_system_score_codex":0.000031392807,"about_ca_system_score_gemma":0.00008712348,"threshold_uncertainty_score":0.9999303},"labels":[],"label_agreement":null},{"id":"W2414592573","doi":"10.1007/978-1-61779-564-0_19","title":"Leading a Successful iGEM Team","year":2012,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Energy","funders":"","keywords":"Agile software development; Context (archaeology); Engineering management; Computer science; Knowledge management; Engineering ethics; Engineering; Software engineering; Biology","score_opus":0.0168936398056432,"score_gpt":0.37020257329065276,"score_spread":0.3533089334850096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2414592573","genre_codex":"methods","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":[0.445933,0.005199979,0.54543036,0.000058320813,0.0002906648,0.00013367875,0.0000022601632,0.000017442248,0.0029343066],"genre_scores_gemma":[0.59854466,0.00008517561,0.40024376,0.00038143492,0.00028203567,0.000043539945,0.000054651737,0.000038570608,0.00032620647],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99706435,0.0013088773,0.0003497459,0.00048113204,0.000076967444,0.00071892113],"domain_scores_gemma":[0.99903005,0.000043854292,0.00011141565,0.0006220771,0.00004616241,0.00014642626],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0017356982,0.00024999748,0.0003580018,0.00018025454,0.00005434305,0.000011614963,0.00034664397,0.00038364023,0.00004837873],"category_scores_gemma":[0.0002612145,0.00024525804,0.00020382862,0.00036802352,0.00014395859,0.0000041090184,0.00025849784,0.00017898352,0.000024657369],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016678296,0.000055216664,0.085634865,0.0000070676547,0.00008575825,0.0000021470457,0.000033806504,0.0003126182,0.9025529,0.0006516316,0.00021298918,0.010434315],"study_design_scores_gemma":[0.00040699588,0.00012197883,0.0025501314,0.000008101309,0.00005633729,0.000030391344,0.00006791669,0.0003120764,0.91363853,0.00076033286,0.081612796,0.00043443282],"about_ca_topic_score_codex":0.000017786148,"about_ca_topic_score_gemma":0.000015976759,"teacher_disagreement_score":0.15261163,"about_ca_system_score_codex":0.000035061043,"about_ca_system_score_gemma":0.00003885224,"threshold_uncertainty_score":0.99999994},"labels":[],"label_agreement":null},{"id":"W2414864971","doi":"10.1088/0951-7715/28/7/2515","title":"Dynamics and stability of a three-dimensional model of cell signal transduction with delay","year":2015,"lang":"en","type":"article","venue":"Nonlinearity","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Killam Trusts","keywords":"Mathematics; Delay differential equation; Stability (learning theory); Differential equation; Algebraic number; Exponential stability; Cytosol; Control theory (sociology); Applied mathematics; SIGNAL (programming language); Constant (computer programming); Dynamics (music); Mathematical analysis; Enzyme; Chemistry; Computer science; Physics; Nonlinear system","score_opus":0.017355130255691985,"score_gpt":0.2244181507291608,"score_spread":0.2070630204734688,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2414864971","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":[0.96168673,0.00016936017,0.037939038,0.000029272935,0.000008795913,0.000069346,0.000047483078,0.0000028098536,0.00004714678],"genre_scores_gemma":[0.97948253,0.000005097651,0.020363677,0.000006345567,0.000028069582,0.0000015481286,0.000091912814,0.000007634159,0.000013159574],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99936366,0.000032608,0.0001644834,0.00019606797,0.00015352046,0.00008964272],"domain_scores_gemma":[0.9994062,0.0000048416705,0.000081983715,0.00020207962,0.0002351865,0.0000697107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022561576,0.000085740015,0.00015579625,0.000019428815,0.000016813048,0.000002084298,0.0000552922,0.000095920164,0.000005225979],"category_scores_gemma":[0.0000063144857,0.00007379087,0.000049950926,0.00006951506,0.00014199018,0.0000028968318,0.000033219116,0.000054798875,1.06806105e-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":[0.0007282463,0.0004607914,0.091829784,0.00007614813,0.00012808543,6.801318e-7,0.00006757779,0.13632378,0.7692737,0.00004172036,0.000021242087,0.0010482313],"study_design_scores_gemma":[0.0004249485,0.00022488057,0.0009876095,0.0000033047227,0.000064125,0.0000034272728,0.000021719346,0.67108685,0.3269808,0.00012264775,0.0000043160358,0.00007534142],"about_ca_topic_score_codex":0.000057158002,"about_ca_topic_score_gemma":0.0011470779,"teacher_disagreement_score":0.5347631,"about_ca_system_score_codex":0.0000116975625,"about_ca_system_score_gemma":0.00018944172,"threshold_uncertainty_score":0.3009104},"labels":[],"label_agreement":null},{"id":"W2419232261","doi":"10.4103/1008-682x.174858","title":"Cancer/testis antigens and obligate participation in multiple hallmarks of cancer: an update","year":2016,"lang":"en","type":"article","venue":"Asian Journal of Andrology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"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 Waterloo","funders":"","keywords":"Cancer; Obligate; Antigen; Perspective (graphical); Biology; Reductionism; Computational biology; Immunology; Genetics; Epistemology; Computer science; Philosophy","score_opus":0.009707589269541569,"score_gpt":0.2760888698305803,"score_spread":0.2663812805610387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2419232261","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":[0.99527174,0.0028916807,0.0004727559,0.0012233659,0.00007452274,0.00003814337,0.000009832781,0.0000011188004,0.000016817137],"genre_scores_gemma":[0.9962786,0.0032084922,0.00027924214,0.000068788315,0.00012981168,0.0000033687809,0.000003572611,0.000009285181,0.000018841507],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991243,0.00011866435,0.00035849822,0.0001491481,0.00006857506,0.00018084428],"domain_scores_gemma":[0.9993205,0.000010607625,0.0003220054,0.00013109382,0.000116909534,0.000098893404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023617806,0.000089330206,0.00024888237,0.00010046306,0.000023026321,0.0000039416627,0.0001056752,0.00010745327,0.000029518973],"category_scores_gemma":[0.0000339752,0.00006615971,0.000057680627,0.0000836435,0.000121944446,0.000010275599,0.00002873163,0.000051711944,3.3577837e-7],"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":[0.00017807582,0.00003854623,0.6662516,0.0000059363697,0.00011458704,0.000010742888,0.00007590731,0.00048633717,0.26872167,0.000008796124,0.00009472639,0.064013086],"study_design_scores_gemma":[0.0022837294,0.0010293245,0.8513399,0.00007315288,0.00011873048,0.00007930259,0.000059921636,0.00039883328,0.14020419,0.00028383042,0.00394686,0.00018223056],"about_ca_topic_score_codex":0.00005870118,"about_ca_topic_score_gemma":0.0027272103,"teacher_disagreement_score":0.18508829,"about_ca_system_score_codex":0.000011723793,"about_ca_system_score_gemma":0.000089044304,"threshold_uncertainty_score":0.26979145},"labels":[],"label_agreement":null},{"id":"W2438112359","doi":"10.1007/978-1-59745-406-3_1","title":"The Intranuclear Environment","year":2008,"lang":"en","type":"review","venue":"Methods in molecular biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Hotel Dieu Hospital","funders":"National Institute of General Medical Sciences","keywords":"Counterintuitive; Nucleus; Range (aeronautics); Space (punctuation); Macromolecule; Chemical physics; Physics; Nanotechnology; Biophysics; Statistical physics; Chemistry; Biology; Neuroscience; Computer science; Materials science; Quantum mechanics","score_opus":0.0244160673110184,"score_gpt":0.37359882426375,"score_spread":0.3491827569527316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2438112359","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000055081623,0.87139094,0.12769328,0.000023651926,0.0001940258,0.0004040271,0.0000070436795,0.000009012062,0.0002724948],"genre_scores_gemma":[6.14136e-7,0.86711615,0.13194032,0.000070766924,0.00017769783,0.00015654336,0.00015936946,0.00008875681,0.00028978518],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99374384,0.003828164,0.00078584865,0.0009242701,0.000109117915,0.0006087479],"domain_scores_gemma":[0.9979907,0.00015420595,0.0003255493,0.0014120048,0.000020837238,0.00009665237],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010919217,0.0005552824,0.0012199789,0.0001443625,0.00015542246,0.000018158722,0.000914941,0.00095650036,0.000021370683],"category_scores_gemma":[0.00019520866,0.00039115237,0.00092589395,0.00026830594,0.00048020616,7.5407723e-7,0.00049872894,0.000462241,0.000041919684],"study_design_candidate":"not_applicable","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":[0.00000626241,0.000024950055,0.0000048876655,0.00012731426,0.00037731449,0.000019953179,0.0000043482682,0.000044319324,0.0028797435,0.00021697322,0.00030212957,0.9959918],"study_design_scores_gemma":[0.00011275582,0.00009523402,0.0000011193521,0.00010487019,0.00018239424,0.00010690887,0.0000036620922,0.000013204138,0.00067797065,0.0002511137,0.9980538,0.00039700276],"about_ca_topic_score_codex":0.0000057815455,"about_ca_topic_score_gemma":0.0000055240307,"teacher_disagreement_score":0.99775165,"about_ca_system_score_codex":0.00007307751,"about_ca_system_score_gemma":0.00015204518,"threshold_uncertainty_score":0.999854},"labels":[],"label_agreement":null},{"id":"W2461066852","doi":"10.1016/j.jtbi.2016.06.036","title":"Design principles for the analysis and construction of robustly homeostatic biological networks","year":2016,"lang":"en","type":"article","venue":"Journal of Theoretical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Impact; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science","score_opus":0.017495077087496987,"score_gpt":0.2521624612913624,"score_spread":0.2346673842038654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2461066852","genre_codex":"methods","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":[0.36460492,0.0013624306,0.6334272,0.00045258112,0.000064877975,0.000076813434,0.0000049286073,0.0000012186279,0.0000050197427],"genre_scores_gemma":[0.97998565,0.0017648153,0.017997667,0.0000484776,0.00018046716,0.0000044464628,0.00000389748,0.000006346092,0.0000082143815],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99878293,0.00033193422,0.00047306667,0.00016880796,0.000058899106,0.00018433991],"domain_scores_gemma":[0.9983749,0.00073940953,0.0004037803,0.00019670922,0.00021568566,0.00006952333],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011519511,0.00011325052,0.00036491192,0.00009187558,0.000052261144,0.0000066547013,0.00020741478,0.0001906102,0.000038613045],"category_scores_gemma":[0.0005369179,0.000050218317,0.00029285022,0.0001662586,0.0013635532,0.0000023453615,0.00007088712,0.000060333416,2.1248535e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0037191575,0.00016407097,0.0912367,0.00002318536,0.011475367,0.0000037131279,0.00004234501,0.018526157,0.5161109,0.25723028,0.00029555793,0.10117257],"study_design_scores_gemma":[0.010238122,0.018320104,0.09549791,0.00017639874,0.018842844,0.0010650477,0.0006522586,0.07788191,0.46485218,0.300774,0.009860441,0.0018387564],"about_ca_topic_score_codex":3.8402115e-7,"about_ca_topic_score_gemma":9.204984e-7,"teacher_disagreement_score":0.6154295,"about_ca_system_score_codex":0.000008491005,"about_ca_system_score_gemma":0.000034651828,"threshold_uncertainty_score":0.50240684},"labels":[],"label_agreement":null},{"id":"W2465452122","doi":"10.1504/ijbir.2016.077609","title":"Environmental decision-making under uncertainty using a biologically-inspired simulation-optimisation algorithm for generating alternative perspectives","year":2016,"lang":"en","type":"article","venue":"International Journal of Business Innovation and Research","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Set (abstract data type); Mathematical optimization; Algorithm; Mathematics","score_opus":0.0554558381510364,"score_gpt":0.38553965774098503,"score_spread":0.33008381958994865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2465452122","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":[0.5296847,0.00014718689,0.46973014,0.00023878115,0.000115079405,0.00006758758,0.000011404846,0.0000014092191,0.0000037254435],"genre_scores_gemma":[0.96639234,0.00018076725,0.032312155,0.00006642784,0.0009781597,0.0000048258125,0.000018787705,0.00001243647,0.000034078203],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99858564,0.00010089239,0.00043741392,0.00022770776,0.0004988781,0.00014948401],"domain_scores_gemma":[0.99659604,0.00023100058,0.00032846714,0.000090284855,0.002723894,0.000030335095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010106827,0.000101888705,0.00012747754,0.00045476112,0.00015801257,0.000070267946,0.00020039809,0.000095273506,0.000032178403],"category_scores_gemma":[0.000693062,0.00006993473,0.000059833394,0.00031090333,0.00016918285,0.000034340686,0.0001111076,0.00007726344,5.179506e-7],"study_design_candidate":"simulation_or_modeling","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":[0.00023529392,0.00007408197,0.0009910685,0.0000021605624,0.00025039018,0.0000031170784,0.00008752714,0.2948743,0.38166788,0.00030318965,0.000038226986,0.32147276],"study_design_scores_gemma":[0.0039183623,0.00043625516,0.017352775,0.00037721853,0.000049713388,0.0001336361,0.0019215235,0.94654316,0.017766386,0.00817937,0.0028577105,0.00046388237],"about_ca_topic_score_codex":0.0000029724404,"about_ca_topic_score_gemma":0.0000016485344,"teacher_disagreement_score":0.65166885,"about_ca_system_score_codex":0.00016408028,"about_ca_system_score_gemma":0.00012090919,"threshold_uncertainty_score":0.28518555},"labels":[],"label_agreement":null},{"id":"W2476037388","doi":"10.4324/9781315731544-27","title":"Systems biology and mechanistic explanation","year":2017,"lang":"en","type":"book-chapter","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":25,"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 Alberta","funders":"University of Oxford; Princeton University","keywords":"Systems biology; Biological network; Computer science; Synthetic biology; Network motif; Cognitive science; Management science; Computational biology; Data science; Biology; Engineering; Psychology","score_opus":0.013892192561829268,"score_gpt":0.242722837114115,"score_spread":0.22883064455228572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2476037388","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00084682764,0.01409455,0.00964621,0.00006944157,0.000656468,0.0003771999,0.00007438668,0.000032085452,0.9742028],"genre_scores_gemma":[0.23858921,0.0015610866,0.00012392024,0.000037237696,0.0006266072,0.000010120481,0.000684983,0.000042700518,0.75832415],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.999184,0.000015217477,0.00017636409,0.00042337572,0.000068338726,0.00013271486],"domain_scores_gemma":[0.99909043,0.0000057556467,0.00020492364,0.0005576027,0.00007394845,0.0000673439],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011585417,0.00021934792,0.00026218744,0.00006260528,0.0001021306,0.000039342867,0.00015940894,0.0005140907,0.000062612104],"category_scores_gemma":[0.0000147787705,0.00020112176,0.000084924555,0.000002720766,0.000077803976,8.9637757e-7,0.00012229463,0.00006706245,0.000028840015],"study_design_candidate":"not_applicable","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":[0.00005118331,0.000015339925,0.00020206881,0.00017547776,0.0018262385,0.000019248948,0.000011412724,0.00011257286,0.07061648,0.88982564,0.024194974,0.012949346],"study_design_scores_gemma":[0.00024699658,0.00018270458,0.000025817279,0.000047360692,0.0002979601,0.00004930129,0.000006102538,0.00049742335,0.0013544317,0.010241934,0.9864893,0.000560657],"about_ca_topic_score_codex":0.000015649075,"about_ca_topic_score_gemma":0.000056299647,"teacher_disagreement_score":0.96229434,"about_ca_system_score_codex":0.000011040931,"about_ca_system_score_gemma":0.000036458965,"threshold_uncertainty_score":0.82015073},"labels":[],"label_agreement":null},{"id":"W2483530691","doi":"10.1088/1478-3975/13/4/046004","title":"Multiparticle collision dynamics for diffusion-influenced signaling pathways","year":2016,"lang":"en","type":"article","venue":"Physical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Ryerson University","keywords":"Mesoscopic physics; Collision; Statistical physics; Diffusion; Biological system; Chemotaxis; Molecular dynamics; Computer science; Anomalous diffusion; Dynamics (music); Particle (ecology); Physics; Chemistry; Computational chemistry; Biology; Ecology; Innovation diffusion; Quantum mechanics","score_opus":0.010250940872349292,"score_gpt":0.256009591067113,"score_spread":0.24575865019476373,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2483530691","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":[0.9629245,0.000060336944,0.036470864,0.00021151376,0.000058352718,0.00016659834,0.000060631028,0.000022346094,0.000024874473],"genre_scores_gemma":[0.9984151,0.000014663155,0.00075699616,0.00009294251,0.0003968726,0.00005825343,0.0001182604,0.000018406361,0.00012850351],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990005,0.000062305335,0.00016427148,0.00040191982,0.000054581815,0.00031641527],"domain_scores_gemma":[0.99934596,0.00009541354,0.000073521696,0.00029948933,0.00009268339,0.000092959475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010010694,0.00014144981,0.00019632133,0.000022951699,0.00009458673,0.0000068152012,0.00016928668,0.00012031701,0.0000051096245],"category_scores_gemma":[0.00012153335,0.00009264368,0.00018488258,0.00008122258,0.00012467228,0.0000028067486,0.0001089801,0.000028850072,0.000025341504],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008444817,0.000080254176,0.0037471906,0.000003264195,0.000044446544,2.3210713e-7,0.000012028012,0.00020337413,0.9865241,0.0016076317,0.00013788395,0.0075551546],"study_design_scores_gemma":[0.0011475412,0.0005471313,0.0014614164,0.000011135623,0.000048799586,0.0000014299079,0.000020777225,0.0153300855,0.97122574,0.0056309304,0.0042957836,0.00027923973],"about_ca_topic_score_codex":0.000003356957,"about_ca_topic_score_gemma":0.000013946241,"teacher_disagreement_score":0.035713866,"about_ca_system_score_codex":0.000025247822,"about_ca_system_score_gemma":0.000026857537,"threshold_uncertainty_score":0.37778997},"labels":[],"label_agreement":null},{"id":"W2487471610","doi":"10.4018/978-1-60566-685-3.ch008","title":"Modeling Gene Regulatory Networks with Delayed Stochastic Dynamics","year":2010,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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 Calgary","funders":"","keywords":"Gene regulatory network; Computer science; Stochastic modelling; Dynamics (music); Noise (video); Gene; Gene expression; Biology; Artificial intelligence; Mathematics; Physics; Genetics","score_opus":0.006097709433195986,"score_gpt":0.20278789791212615,"score_spread":0.19669018847893016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2487471610","genre_codex":"methods","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":[0.045372956,0.004134221,0.61138624,0.00002888935,0.0007593117,0.0009180162,0.00028514126,0.00016822833,0.33694696],"genre_scores_gemma":[0.96805614,0.000018435165,0.0028816275,0.00019358043,0.0012349101,0.000023150635,0.00034865947,0.00019755108,0.027045948],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973912,0.00002534167,0.00050255656,0.0010540693,0.0004272587,0.0005995651],"domain_scores_gemma":[0.9976482,0.000005761502,0.00028339308,0.0014575111,0.00028687483,0.00031827373],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0001536309,0.00079150236,0.000634361,0.0000679353,0.00018768143,0.00006125719,0.000517492,0.0015133432,0.000015291014],"category_scores_gemma":[0.0000067009896,0.0007716612,0.00041472565,0.000029730969,0.00022486575,0.0000023996745,0.00028309057,0.00054713635,0.00001633977],"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":[0.000490505,0.000022952614,0.000014725663,0.000021671747,0.0019254152,0.00006575642,0.000008264488,0.89043087,0.003381251,0.09918169,0.0003258616,0.004131037],"study_design_scores_gemma":[0.0020241179,0.0009510242,0.000022117727,0.0003263472,0.003099457,0.0007124634,0.000020059173,0.95240873,0.001228904,0.032497622,0.0025076643,0.0042014862],"about_ca_topic_score_codex":0.000033232165,"about_ca_topic_score_gemma":0.0016953232,"teacher_disagreement_score":0.9226832,"about_ca_system_score_codex":0.00017161353,"about_ca_system_score_gemma":0.00031765952,"threshold_uncertainty_score":0.9997829},"labels":[],"label_agreement":null},{"id":"W2490699154","doi":"10.1017/cbo9781139012751.011","title":"Phenotype state spaces and strategies for exploring them","year":2015,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Institute of Cancer Research","funders":"","keywords":"Phenotype; Epistasis; Gene; Genetics; Biology; Computational biology","score_opus":0.058272489889993145,"score_gpt":0.21639755349028658,"score_spread":0.15812506360029344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2490699154","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024759145,0.0017012852,0.0019074657,0.000008455323,0.0001379006,0.00038269005,0.0002483103,0.000039928225,0.9708148],"genre_scores_gemma":[0.028600464,0.00050176034,0.00025986286,0.000012481118,0.0002175166,0.00000257716,0.0001348325,0.00005329795,0.9702172],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99907994,0.000019404313,0.000111076515,0.0004572105,0.00011920483,0.00021316478],"domain_scores_gemma":[0.9991458,0.0000109399425,0.00013861756,0.0003759587,0.0001919517,0.00013672792],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009372623,0.00028167013,0.00027786437,0.00005326711,0.000105904845,0.000052479663,0.00021394793,0.00020493157,0.0000010367929],"category_scores_gemma":[0.0000040919576,0.00032002124,0.00014187154,0.000004439866,0.00015901742,0.0000074914797,0.0002662177,0.000101666745,0.000001619556],"study_design_candidate":"not_applicable","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":[0.00090627593,0.000018740293,0.000026122094,0.00037060806,0.0021455092,0.0000677053,0.00022774938,0.00062802585,0.008704936,0.8912434,0.087908685,0.0077522118],"study_design_scores_gemma":[0.0004426377,0.00009626941,0.000008268393,0.00003399317,0.00029328323,0.0000044838707,0.00017063583,0.00005923149,0.0018664609,0.00010055927,0.9965342,0.0003899237],"about_ca_topic_score_codex":0.000025413932,"about_ca_topic_score_gemma":0.0000113832475,"teacher_disagreement_score":0.90862554,"about_ca_system_score_codex":0.00003483314,"about_ca_system_score_gemma":0.00014502322,"threshold_uncertainty_score":0.9999252},"labels":[],"label_agreement":null},{"id":"W2496202180","doi":"10.1016/b978-0-12-394447-4.40027-1","title":"Understanding of ‘Networks’ In Vitro and/or In Vivo","year":2015,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network","funders":"","keywords":"In vitro; In vivo; Computer science; Biology; Genetics","score_opus":0.04204651685949819,"score_gpt":0.2507633717217065,"score_spread":0.2087168548622083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2496202180","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0050938246,0.010995286,0.00011227088,0.00001995406,0.0001407947,0.00044272258,0.000024726844,0.000008344088,0.9831621],"genre_scores_gemma":[0.3699117,0.0007023307,0.00017235131,0.000048820653,0.0002095831,0.000011858453,0.000042295444,0.00007148652,0.6288296],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986746,0.00004212025,0.00044184327,0.00042984335,0.00016629706,0.00024530917],"domain_scores_gemma":[0.99924654,0.000015491913,0.00020404556,0.0004020537,0.000042550877,0.00008933888],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003693784,0.00028967482,0.00053779135,0.00020063347,0.000018038048,0.000009396816,0.00016117508,0.00047416193,0.00003016338],"category_scores_gemma":[0.000013232172,0.00027323051,0.0001260804,0.00002829675,0.00014484716,0.0000013630694,0.0001744673,0.0001954779,0.0000010349623],"study_design_candidate":"not_applicable","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":[0.0025589506,0.00010686353,0.0015613514,0.0006284533,0.0015082617,0.000297093,0.0005494079,0.0043706363,0.07509467,0.0042429217,0.0025205351,0.90656084],"study_design_scores_gemma":[0.0026032953,0.00040289052,0.000060667393,0.00093225366,0.00035520853,0.00005209684,0.00013859863,0.0012513278,0.01066675,0.010027039,0.97192496,0.0015848947],"about_ca_topic_score_codex":0.0000012797581,"about_ca_topic_score_gemma":0.0004331828,"teacher_disagreement_score":0.96940446,"about_ca_system_score_codex":0.00010394476,"about_ca_system_score_gemma":0.00012771653,"threshold_uncertainty_score":0.999972},"labels":[],"label_agreement":null},{"id":"W2497124121","doi":"10.1101/063784","title":"Precision of readout at the hunchback gene","year":2016,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"McMaster University","funders":"Agence Nationale de la Recherche","keywords":"Transcription (linguistics); Biology; Transcription factor; Computational biology; Gene expression; Gene; Promoter; Cell biology; Genetics","score_opus":0.009602428701371369,"score_gpt":0.21640987802148642,"score_spread":0.20680744932011505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2497124121","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":[0.9898255,0.006618469,0.0019155086,0.00021432676,0.0006057948,0.0005001659,0.00024395088,0.000043535118,0.000032757263],"genre_scores_gemma":[0.99639744,0.0011510787,0.001074461,0.000097357806,0.00089588587,0.00008743601,0.000002390786,0.00012490118,0.00016907328],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.997079,0.0002504101,0.0006333855,0.0011038762,0.00044814227,0.00048514182],"domain_scores_gemma":[0.9955299,0.00003852624,0.00067372614,0.0030231532,0.0005501668,0.00018455727],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007619979,0.00052373693,0.0005501526,0.00010960506,0.0001527958,0.000046162026,0.00094003486,0.0007366139,0.000079238656],"category_scores_gemma":[0.00016963494,0.0003820405,0.00043943487,0.0002434944,0.00027974232,0.000004542204,0.0017436361,0.00025696127,0.00007123896],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000668284,0.000046663303,0.0065003065,0.00006827376,0.000401198,0.0000039372535,0.0000019274985,0.00024802514,0.98928034,0.000029102825,0.0033460038,0.0000073925753],"study_design_scores_gemma":[0.0003180328,0.000059395166,0.022619983,0.00013157005,0.00021829717,2.588761e-8,6.5100716e-7,0.000047360132,0.9565277,0.0000042038173,0.01960146,0.0004713124],"about_ca_topic_score_codex":0.000010343813,"about_ca_topic_score_gemma":0.0000064509,"teacher_disagreement_score":0.032752633,"about_ca_system_score_codex":0.00012421554,"about_ca_system_score_gemma":0.00038243653,"threshold_uncertainty_score":0.99986315},"labels":[],"label_agreement":null},{"id":"W2500916322","doi":"10.1088/1478-3975/13/4/046001","title":"Analysis of a minimal Rho-GTPase circuit regulating cell shape","year":2016,"lang":"en","type":"article","venue":"Physical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":68,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Division of Social and Economic Sciences; Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"GTPase; Guanine nucleotide exchange factor; Motility; Cytoskeleton; CDC42; Cell biology; Biology; Actin; Nucleotide; Physics; Topology (electrical circuits); Cell; Biophysics; Genetics; Gene; Mathematics; Combinatorics","score_opus":0.011776236309284191,"score_gpt":0.24866723564554918,"score_spread":0.236890999336265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2500916322","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":[0.99769485,0.00018853848,0.0013202692,0.00007700122,0.000030117413,0.0000621211,0.000047672376,0.000013044713,0.000566381],"genre_scores_gemma":[0.9989937,0.000021686375,0.00014834921,0.000057180452,0.00032511732,0.0000117922245,0.0001078105,0.000016126854,0.00031825755],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99864775,0.00013625379,0.00028572252,0.0005162173,0.000090917485,0.0003231347],"domain_scores_gemma":[0.99900615,0.00007082206,0.00019761156,0.00052976777,0.00009767083,0.00009797339],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013314217,0.00018067834,0.00046204962,0.00012896633,0.000040857045,0.0000039000197,0.0002461104,0.00016518595,0.00009627722],"category_scores_gemma":[0.000060824772,0.00012769683,0.00050984183,0.00048074336,0.00022493298,0.0000025513061,0.00015005394,0.000047034566,0.000018214729],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039533683,0.000113013855,0.028529895,0.000005957009,0.00081204367,5.3917194e-7,0.000024398762,0.0001134535,0.9628078,0.0003008823,0.00015577833,0.0070967022],"study_design_scores_gemma":[0.0009478524,0.0006614465,0.038375903,0.0000111486615,0.0019532992,0.0000019356503,0.000035272846,0.005305085,0.94717866,0.0009896395,0.004021016,0.00051875314],"about_ca_topic_score_codex":0.0000082201,"about_ca_topic_score_gemma":0.000009919279,"teacher_disagreement_score":0.015629154,"about_ca_system_score_codex":0.000013071864,"about_ca_system_score_gemma":0.00003511715,"threshold_uncertainty_score":0.5207325},"labels":[],"label_agreement":null},{"id":"W2502937008","doi":"10.1137/1.9780898718256.ch2","title":"Chapter 2: Discrete-Time Models","year":2006,"lang":"en","type":"book-chapter","venue":"Society for Industrial and Applied Mathematics eBooks","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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 Alberta","funders":"","keywords":"Discrete time and continuous time; Discrete modelling; Statistical physics; Computer science; Mathematics; Applied mathematics; Algorithm; Discrete system; Physics; Statistics","score_opus":0.028518081317440384,"score_gpt":0.21650946810671765,"score_spread":0.18799138678927726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2502937008","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0033201622,0.0005945285,0.008762123,0.00006611849,0.00013196297,0.0020901465,0.0004822088,0.00007232485,0.98448044],"genre_scores_gemma":[0.014165029,0.00010030518,0.012643372,0.00017717715,0.003090101,0.0001804943,0.0011503756,0.00032686192,0.9681663],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99834037,0.0000026090886,0.000498275,0.0005928965,0.00023091532,0.00033492863],"domain_scores_gemma":[0.99894834,0.000028250472,0.00035997495,0.00047833784,0.000064767206,0.000120319724],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00023756931,0.00053020683,0.0006312646,0.000030618972,0.00019848162,0.00005600365,0.0002070337,0.0012250862,0.000026421849],"category_scores_gemma":[0.0000033348167,0.0004922457,0.0009125399,0.000009090401,0.00023611682,0.0000017927354,0.0002028078,0.00025169435,0.000008196968],"study_design_candidate":"theoretical_or_conceptual","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":[0.0001867995,0.00008200421,5.640999e-7,0.0005013065,0.00452115,0.0000015250525,0.00044675104,0.0017941571,0.040344194,0.8016611,0.13357867,0.01688179],"study_design_scores_gemma":[0.0035322004,0.00032198045,9.794695e-8,0.00024744676,0.00264553,0.000015911906,0.00013192731,0.0063445563,0.01420919,0.46390703,0.5062305,0.0024136459],"about_ca_topic_score_codex":0.000001263523,"about_ca_topic_score_gemma":0.0000018866988,"teacher_disagreement_score":0.3726518,"about_ca_system_score_codex":0.000021639744,"about_ca_system_score_gemma":0.00006423678,"threshold_uncertainty_score":0.99975294},"labels":[],"label_agreement":null},{"id":"W2509582984","doi":"10.4236/am.2016.713124","title":"Convergence Properties of Piecewise Power Approximations","year":2016,"lang":"en","type":"article","venue":"Applied Mathematics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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 Victoria","funders":"Norges Forskningsråd; Universidad Complutense de Madrid","keywords":"Convergence (economics); Piecewise; Applied mathematics; Mathematics; Power (physics); Mathematical optimization; Computer science; Mathematical analysis; Physics; Economics","score_opus":0.011979395170503218,"score_gpt":0.20489703221447692,"score_spread":0.1929176370439737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2509582984","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":[0.9441038,0.0002463863,0.05185035,0.000075837335,0.000033717995,0.00020300529,0.0000057091165,0.000016703083,0.003464523],"genre_scores_gemma":[0.98835915,0.000051579744,0.010905944,0.000024013701,0.000029945819,0.000037078396,0.0000036970566,0.00001824027,0.0005703341],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99930644,0.000007556347,0.00024792977,0.00016789939,0.00012885725,0.00014133079],"domain_scores_gemma":[0.9992955,0.000008550927,0.00013016391,0.0004513593,0.00007180615,0.00004266852],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012041337,0.00010874188,0.00015739819,0.000029672961,0.00003190301,0.000004623081,0.00016611215,0.00007300858,0.00005912963],"category_scores_gemma":[0.00003235645,0.00007055425,0.00007094526,0.00008476049,0.00011747886,0.0000019381632,0.00007880219,0.00001856119,0.000040142124],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000068553927,0.00006777123,0.00006915499,0.000046846235,0.00006998567,8.905812e-8,0.000098556666,0.000023126066,0.9911162,0.007399949,0.00061156217,0.0004898879],"study_design_scores_gemma":[0.00022556253,0.000027865493,0.000056877383,0.00003168214,0.00004440787,0.000002782196,0.00014333626,0.000092373186,0.9957681,0.0018114992,0.0016529334,0.00014262112],"about_ca_topic_score_codex":4.2877784e-7,"about_ca_topic_score_gemma":0.0000014531253,"teacher_disagreement_score":0.0442554,"about_ca_system_score_codex":0.0000065791687,"about_ca_system_score_gemma":0.000033316333,"threshold_uncertainty_score":0.28771186},"labels":[],"label_agreement":null},{"id":"W2517281749","doi":"10.1016/j.neuron.2016.07.037","title":"Proneurogenic Ligands Defined by Modeling Developing Cortex Growth Factor Communication Networks","year":2016,"lang":"en","type":"article","venue":"Neuron","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":50,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"","keywords":"Glial cell line-derived neurotrophic factor; Neurotrophic factors; Neurogenesis; Neurturin; Autocrine signalling; Paracrine signalling; Neural stem cell; Biology; Neuroscience; Cell biology; Neurosphere; Embryonic stem cell; Precursor cell; Stem cell; Receptor; Cell; Adult stem cell; Biochemistry","score_opus":0.01198670050164636,"score_gpt":0.22230383684871025,"score_spread":0.2103171363470639,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2517281749","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":[0.9513565,0.0012808169,0.046618458,0.00044235878,0.00007361692,0.00012155054,0.0000057807265,0.000035140736,0.00006579867],"genre_scores_gemma":[0.99728525,0.0015640424,0.0003537352,0.00030024783,0.00010039895,0.000019530455,0.00008335647,0.00004353608,0.00024988857],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988752,0.00007872631,0.00024359688,0.00039161404,0.00012608919,0.00028479163],"domain_scores_gemma":[0.9991561,0.000019200541,0.00009917373,0.00055249635,0.00009465498,0.0000783374],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000086972024,0.0001804528,0.00015005669,0.00003353134,0.00011981018,0.000023275847,0.00030146466,0.00013818644,0.0000089006935],"category_scores_gemma":[0.00005084902,0.00014577518,0.00010016961,0.000121379686,0.000039183113,0.0000067223714,0.00016537301,0.000075894044,0.000009836418],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037229343,0.000031875363,0.0051677036,0.000007175592,0.00006882482,9.40884e-7,0.000009468435,0.0014554629,0.9873954,0.00006740055,0.0018857131,0.0038727822],"study_design_scores_gemma":[0.0028333408,0.0006244495,0.017356178,0.00013395427,0.00024827872,0.000052115567,0.000022156211,0.11893667,0.83910406,0.0004210594,0.01847566,0.0017920698],"about_ca_topic_score_codex":0.000006476531,"about_ca_topic_score_gemma":0.000015725947,"teacher_disagreement_score":0.14829135,"about_ca_system_score_codex":0.00002385972,"about_ca_system_score_gemma":0.000045163608,"threshold_uncertainty_score":0.59445393},"labels":[],"label_agreement":null},{"id":"W2536804470","doi":"10.5539/ijsp.v5n6p32","title":"Linear Hybrid Deterministic Dynamic Modeling for Time-to-Event Processes: State and Parameter Estimations","year":2016,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Division of Mathematical Sciences","keywords":"Discrete time and continuous time; Computer science; Discretization; Event (particle physics); Process (computing); Discrete event dynamic system; Mathematical optimization; Hazard; Estimation theory; Scope (computer science); Mathematics; Discrete system; Algorithm; Statistics","score_opus":0.010297710199725614,"score_gpt":0.2818029173542002,"score_spread":0.27150520715447457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2536804470","genre_codex":"methods","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":[0.4295294,0.00007557423,0.5697277,0.00024540795,0.00003816566,0.00008807795,0.00029237205,9.63594e-7,0.0000023237374],"genre_scores_gemma":[0.90851057,0.00011408993,0.09107246,0.00005121965,0.00006474553,0.000009302026,0.000022802076,0.00000942192,0.00014540231],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99919474,0.000026996267,0.0003569431,0.00017291705,0.00014614651,0.00010223334],"domain_scores_gemma":[0.9986913,0.00012483142,0.0001672516,0.0000889186,0.0008286631,0.00009902705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030469283,0.000093398885,0.0001358012,0.00005048278,0.000039433755,0.00003344917,0.0001171212,0.000024828414,0.000013671406],"category_scores_gemma":[0.0008358439,0.00006821872,0.0000392603,0.000023472514,0.000057343175,0.000008439299,0.00005810146,0.000030508632,0.0000019812871],"study_design_candidate":"simulation_or_modeling","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":[0.0029082634,0.00073127676,0.010264249,0.00066329486,0.0025884125,0.00004978375,0.00041059646,0.19226952,0.09024084,0.00051312754,0.0026820006,0.69667864],"study_design_scores_gemma":[0.0019413894,0.0012979697,0.0023010257,0.00022448927,0.00025229325,0.0002527529,0.000012019414,0.88246626,0.003934706,0.10296915,0.0038834042,0.00046451986],"about_ca_topic_score_codex":0.0000011661157,"about_ca_topic_score_gemma":0.000010922827,"teacher_disagreement_score":0.6962141,"about_ca_system_score_codex":0.000026529118,"about_ca_system_score_gemma":0.000115055525,"threshold_uncertainty_score":0.27818784},"labels":[],"label_agreement":null},{"id":"W2537540552","doi":"10.1109/iembs.2004.1403818","title":"Consequences of deterministic and stochastic modeling of a promoter","year":2005,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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":"Stochastic modelling; Stochastic process; Statistical physics; Computer science; Mathematics; Applied mathematics; Physics; Statistics","score_opus":0.01277396747406305,"score_gpt":0.24350040378838025,"score_spread":0.23072643631431722,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2537540552","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":[0.97423923,0.000495996,0.024970353,0.000030933446,0.000006061395,0.000047949903,0.000001922842,0.0000019287384,0.00020559596],"genre_scores_gemma":[0.9973302,0.000017010165,0.0024847148,0.000017761198,0.000031677137,0.000002269505,0.000003415639,0.0000046780374,0.00010829554],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995706,0.00001484115,0.00016234504,0.00012422429,0.000054028354,0.00007393165],"domain_scores_gemma":[0.99973345,0.000004596905,0.000052240044,0.00013246342,0.000049336406,0.000027909304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007005803,0.000057510388,0.00011265617,0.000024776586,0.000011565324,0.0000022580707,0.00005241138,0.000043009768,0.000013179989],"category_scores_gemma":[0.000018340786,0.00004894365,0.000038033308,0.000032391814,0.00010748275,9.914024e-7,0.00003481196,0.000014055295,4.300031e-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":[0.000019670755,0.00002351517,0.00035213627,0.000023156299,0.00006473222,2.365198e-7,0.000043179105,0.08728274,0.9093618,0.000073610274,0.000013835779,0.0027414055],"study_design_scores_gemma":[0.00036949248,0.00027068556,0.00014451565,0.000028569826,0.00012806227,0.000027616457,0.00009990927,0.52929556,0.46907133,0.00032077485,0.00006240179,0.00018110892],"about_ca_topic_score_codex":0.000005865667,"about_ca_topic_score_gemma":0.000019954276,"teacher_disagreement_score":0.4420128,"about_ca_system_score_codex":0.0000016714578,"about_ca_system_score_gemma":0.000029401854,"threshold_uncertainty_score":0.1995864},"labels":[],"label_agreement":null},{"id":"W2548575444","doi":"10.1109/acssc.2011.6190310","title":"Biosensor arrays for collaborative detection of analytes","year":2011,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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":"","keywords":"Biosensor; Ordinary differential equation; Computer science; Analyte; Partial differential equation; Variance (accounting); Nonlinear system; Estimation theory; Biological system; Differential equation; Mathematics; Algorithm; Chemistry; Materials science; Physics; Nanotechnology; Chromatography; Mathematical analysis","score_opus":0.017510256443341247,"score_gpt":0.23013708353470455,"score_spread":0.2126268270913633,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2548575444","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":[0.95013773,0.00032862628,0.046259616,0.000010343998,0.000055211713,0.00017556573,0.000012611922,0.0000083518435,0.0030119685],"genre_scores_gemma":[0.9921419,0.000041687796,0.007209824,0.000020250962,0.00007111234,0.000015101908,0.000017008771,0.000008798677,0.00047429933],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99955153,0.000020935457,0.00012785468,0.00016203556,0.000041799478,0.00009581996],"domain_scores_gemma":[0.9995083,0.000005034083,0.00007521136,0.00018242828,0.00019863476,0.00003039706],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007760936,0.00007065475,0.00010454658,0.000039610964,0.000029444316,0.0000024008978,0.000060990962,0.00007054715,0.000021401798],"category_scores_gemma":[0.000023888602,0.0000619695,0.000095644784,0.00015373343,0.00004301278,0.0000011091073,0.000016147149,0.000011770321,0.000001767824],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007335747,0.00002649047,0.0010434871,0.0000050842177,0.00015127508,7.0984704e-8,0.000036353184,0.000050695144,0.99709916,0.00011440386,0.00023878194,0.001160867],"study_design_scores_gemma":[0.00017400547,0.00024283795,0.0013780968,0.00000119264,0.00004223051,6.014223e-7,0.0001909048,0.0002497012,0.9935457,0.00008694915,0.004011728,0.00007603462],"about_ca_topic_score_codex":0.000009928891,"about_ca_topic_score_gemma":0.0001249335,"teacher_disagreement_score":0.04200421,"about_ca_system_score_codex":0.0000037145398,"about_ca_system_score_gemma":0.000022591765,"threshold_uncertainty_score":0.2527043},"labels":[],"label_agreement":null},{"id":"W2548743006","doi":"10.1109/mlsp.2004.1423006","title":"Soon: self organising oscillator networks for use in clustering problems","year":2005,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Defence Science and Technology Agency - Singapore; University of Liverpool; Innovation, Science and Economic Development Canada","keywords":"Cluster analysis; Computer science; Data mining; Noise (video); Scheme (mathematics); Cluster (spacecraft); Variety (cybernetics); Artificial intelligence; Mathematics; Computer network","score_opus":0.011784737635843819,"score_gpt":0.22454160410922525,"score_spread":0.21275686647338143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2548743006","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":[0.8520223,0.00054158806,0.14670517,0.00011045242,0.00007932596,0.00032698864,0.0000016220176,0.00003895581,0.0001736297],"genre_scores_gemma":[0.9608894,0.00008518803,0.03733245,0.00026040766,0.00057660654,0.000024111296,0.00003609774,0.000037610054,0.00075814355],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989202,0.000032603697,0.00025335685,0.00037297644,0.00007490276,0.0003459647],"domain_scores_gemma":[0.9994806,0.000014240426,0.0000589161,0.0003142805,0.00005667785,0.000075298245],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021885129,0.00015539306,0.00016358503,0.00005141057,0.00006682143,0.000052219322,0.00012801822,0.00016421208,0.000021804022],"category_scores_gemma":[0.000017557233,0.00015136508,0.00010196212,0.00015359477,0.00001813824,0.000007299632,0.000104282335,0.00005443089,0.0000043463465],"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":[0.00007441076,0.00014237383,0.047334526,0.00004571208,0.0002396998,0.0000017731539,0.00009582988,0.8158616,0.11960792,0.000070423324,0.0051915054,0.011334227],"study_design_scores_gemma":[0.0014426486,0.00015685572,0.003383774,0.000030411555,0.00007609184,0.000022164375,0.000054042313,0.81588,0.03230825,0.000026193751,0.14596517,0.00065442437],"about_ca_topic_score_codex":0.000012325307,"about_ca_topic_score_gemma":0.0013567365,"teacher_disagreement_score":0.14077367,"about_ca_system_score_codex":0.000039555773,"about_ca_system_score_gemma":0.000033363744,"threshold_uncertainty_score":0.6172489},"labels":[],"label_agreement":null},{"id":"W2549104476","doi":"10.1091/mbc.e16-06-0354","title":"Model-guided optogenetic study of PKA signaling in budding yeast","year":2016,"lang":"en","type":"article","venue":"Molecular Biology of the Cell","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":25,"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":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; Paul G. Allen Family Foundation; University of California, San Francisco; Howard Hughes Medical Institute; National Science Foundation","keywords":"Optogenetics; Saccharomyces cerevisiae; Biology; Budding yeast; Adenylate kinase; Protein kinase A; Regulator; Yeast; Cell biology; Signal transduction; GTPase; Cyclase; TOR signaling; Small GTPase; Kinase; Computational biology; Biochemistry; Enzyme; Neuroscience; Gene","score_opus":0.013656243404004082,"score_gpt":0.2534877851947763,"score_spread":0.23983154179077223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2549104476","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":[0.99394196,0.0006755471,0.004900365,0.000043485892,0.000049546095,0.00022156179,0.0000065185977,0.0000031565148,0.00015786257],"genre_scores_gemma":[0.99906355,0.000025717936,0.0006562473,0.00003184001,0.000021088286,0.000011720039,0.000004508969,0.000020892465,0.00016442477],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9986589,0.0002599203,0.0003916847,0.00035238164,0.00010425352,0.0002328852],"domain_scores_gemma":[0.998992,0.000010885281,0.00022065121,0.00066702574,0.000072460396,0.000036977744],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028281182,0.00015877318,0.0002700987,0.00008310122,0.000028179862,0.0000019503216,0.00047572044,0.00015275083,0.00000859972],"category_scores_gemma":[0.000038159185,0.000103727696,0.00017728459,0.00017917786,0.00014112185,0.0000011904883,0.00029172812,0.00005030044,0.0000013709146],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002551363,0.00014136983,0.027767137,0.000008460993,0.00007486077,9.778333e-7,0.0000420344,0.02984475,0.94183,0.000017594164,0.000022439142,0.0002248573],"study_design_scores_gemma":[0.00083970604,0.00019908328,0.00098488,0.000019484627,0.00006299791,0.0000018857214,0.00006021699,0.0006517527,0.9967781,0.00023668584,0.000037368194,0.00012787162],"about_ca_topic_score_codex":0.00002090787,"about_ca_topic_score_gemma":0.000028775636,"teacher_disagreement_score":0.05494806,"about_ca_system_score_codex":0.000013740005,"about_ca_system_score_gemma":0.000049841045,"threshold_uncertainty_score":0.42298928},"labels":[],"label_agreement":null},{"id":"W2549616710","doi":"10.1145/2987373","title":"Multithreaded Stochastic PDES for Reactions and Diffusions in Neurons","year":2016,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Institutes of Health; National Institute of Mental Health; China Scholarship Council; U.S. National Library of Medicine; National Natural Science Foundation of China","keywords":"Computer science; Mathematical optimization; Parallel computing; Applied mathematics; Theoretical computer science; Mathematics","score_opus":0.023603215357950888,"score_gpt":0.26144662696955806,"score_spread":0.23784341161160716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2549616710","genre_codex":"methods","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":[0.42710844,0.000034422497,0.5725932,0.00012460243,0.000034841065,0.000089623536,0.000004991381,0.000009205329,6.600149e-7],"genre_scores_gemma":[0.9910728,0.0000645621,0.008645422,0.0000433848,0.000067052344,0.000027320417,0.000009863427,0.000013384268,0.0000562548],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999363,0.0000289864,0.00015520754,0.0002856489,0.00004857071,0.000118585755],"domain_scores_gemma":[0.99956435,0.00009300276,0.000027214579,0.00022372184,0.000042867614,0.000048853162],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000065043154,0.000100888145,0.00009359685,0.000097090924,0.00014420715,0.000015621512,0.000050076884,0.000075911594,0.0000014642364],"category_scores_gemma":[0.000015500715,0.000083822546,0.000047309077,0.000059251233,0.000024706957,0.0000082142415,0.000008136972,0.000039920982,4.945879e-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":[0.000040383067,0.00003724001,0.000061264924,0.000004041697,0.000019208384,7.197835e-8,0.000028979004,0.93981713,0.006437908,0.0000098924265,0.0000014121316,0.053542465],"study_design_scores_gemma":[0.000719593,0.00010579163,0.0005171648,0.000029032602,0.000032080457,0.0000020958516,0.000010239883,0.997668,0.00021727718,0.000535096,0.000057390374,0.00010623676],"about_ca_topic_score_codex":0.000011016983,"about_ca_topic_score_gemma":0.000056379045,"teacher_disagreement_score":0.5639643,"about_ca_system_score_codex":0.0000091978845,"about_ca_system_score_gemma":0.000010855015,"threshold_uncertainty_score":0.34181842},"labels":[],"label_agreement":null},{"id":"W2550116789","doi":"10.1007/978-3-319-45318-7","title":"Simple Mathematical Models of Gene Regulatory Dynamics","year":2016,"lang":"en","type":"book","venue":"Lecture notes on mathematical modelling in the life sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Simple (philosophy); Gene regulatory network; Computer science; Field (mathematics); Focus (optics); Computational biology; Point (geometry); Gene; Biology; Mathematics; Genetics; Physics; Gene expression; Epistemology","score_opus":0.026757136325815552,"score_gpt":0.257800932701153,"score_spread":0.23104379637533745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2550116789","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":[0.0051340354,0.0016083128,0.96617997,0.00040015127,0.00005237399,0.00044693085,0.000042632124,0.000018856854,0.026116762],"genre_scores_gemma":[0.9444338,0.00042542044,0.04532752,0.0010561321,0.0009960525,0.00007050385,0.00013349611,0.00016572421,0.007391323],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9965124,0.00020570193,0.00088347174,0.00080625893,0.0010572696,0.00053490355],"domain_scores_gemma":[0.9974441,0.0007128848,0.00043789583,0.0011714471,0.000106812935,0.00012685804],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0016626948,0.00052955333,0.00082237396,0.00020571711,0.000153375,0.000043901397,0.0013739351,0.0006653555,0.0000529508],"category_scores_gemma":[0.0003022472,0.00029899826,0.00044814157,0.00024321732,0.00092721457,0.00000833705,0.00013396319,0.0003564551,0.00003012545],"study_design_candidate":"simulation_or_modeling","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":[0.00003513021,0.00012500944,0.0000036902395,0.00019179787,0.000120920115,0.0000030126384,0.00016554161,0.9192387,0.00062768196,0.078297354,0.00043965864,0.0007515311],"study_design_scores_gemma":[0.00009548449,0.00013087835,4.3229508e-7,0.00022081603,0.00009069759,0.000007669095,0.000009624529,0.4112605,0.0014747796,0.58638763,0.00007277719,0.00024873664],"about_ca_topic_score_codex":0.0000013101322,"about_ca_topic_score_gemma":0.0000071628806,"teacher_disagreement_score":0.9392998,"about_ca_system_score_codex":0.000059177593,"about_ca_system_score_gemma":0.00036327593,"threshold_uncertainty_score":0.99994624},"labels":[],"label_agreement":null},{"id":"W2552320392","doi":"10.15252/msb.20167216","title":"Dynamical compensation in physiological circuits","year":2016,"lang":"en","type":"article","venue":"Molecular Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":103,"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":"Azrieli Foundation","keywords":"Biology; Compensation (psychology); Computational biology; Neuroscience","score_opus":0.011335472549584929,"score_gpt":0.2391861055719336,"score_spread":0.22785063302234868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2552320392","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":[0.9636166,0.0010202655,0.034462687,0.00015415155,0.00021539394,0.00020178466,0.000009762496,0.000019968144,0.00029937664],"genre_scores_gemma":[0.9993034,0.000047103287,0.00005563978,0.00010635791,0.00015519667,0.000050892486,0.00010302575,0.000020081445,0.00015828967],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9981844,0.00046049553,0.00034181628,0.000558832,0.00008577367,0.0003687285],"domain_scores_gemma":[0.9992849,0.000015768936,0.000103307844,0.00045368084,0.00006274209,0.00007959156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026355422,0.00019002483,0.00030045834,0.00009220877,0.000031219908,0.000009435636,0.00023473022,0.00035447214,0.00001555739],"category_scores_gemma":[0.000079005535,0.00013175227,0.0001280702,0.0001517373,0.000133069,0.0000022210568,0.000109793815,0.00006147807,0.0000509625],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012412848,0.000033486118,0.01433295,0.0000058021024,0.00005340932,0.000010361651,0.0000032594567,0.00034713172,0.98144674,0.0016999636,0.00014588828,0.0019085882],"study_design_scores_gemma":[0.011011237,0.0034502966,0.34148866,0.0003818954,0.00022879016,0.0004939426,0.0001740755,0.011980457,0.5540133,0.0038322893,0.068659455,0.004285585],"about_ca_topic_score_codex":0.000026690514,"about_ca_topic_score_gemma":0.000030000883,"teacher_disagreement_score":0.42743343,"about_ca_system_score_codex":0.00004695763,"about_ca_system_score_gemma":0.00003590215,"threshold_uncertainty_score":0.5372702},"labels":[],"label_agreement":null},{"id":"W2552619932","doi":"10.1016/j.cels.2016.10.008","title":"Design and Construction of Generalizable RNA-Protein Hybrid Controllers by Level-Matched Genetic Signal Amplification","year":2016,"lang":"en","type":"article","venue":"Cell Systems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Complementary and Integrative Health; National Institute of General Medical Sciences; Bill and Melinda Gates Foundation; Natural Sciences and Engineering Research Council of Canada; Defense Advanced Research Projects Agency; National Institutes of Health; National Science Foundation","keywords":"Synthetic biology; Software portability; Computer science; Modularity (biology); Orthogonality; Biology; Computational biology; Genetics; Mathematics","score_opus":0.011454280594163202,"score_gpt":0.1900069228470999,"score_spread":0.1785526422529367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2552619932","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":[0.5884534,0.0028146696,0.40829363,0.00001773057,0.00005484965,0.00028825886,0.000018974653,0.0000061528294,0.000052325355],"genre_scores_gemma":[0.9941185,0.00018152517,0.0038475287,0.000008900556,0.000105394945,0.000053528714,0.000029606746,0.000021634753,0.0016333482],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99881095,0.00021205768,0.0003322748,0.00032872305,0.00012941638,0.00018655688],"domain_scores_gemma":[0.999238,0.000015093404,0.00025552674,0.00030003782,0.000109446926,0.00008190328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024353589,0.0001465505,0.0002445187,0.00004035029,0.000054629385,0.00001929377,0.00010714302,0.00010451036,0.00001519172],"category_scores_gemma":[0.000008008552,0.000116109695,0.000060828417,0.000060238555,0.00011297997,0.0000037932598,0.000026038395,0.000021750187,0.0000057683187],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043494092,0.000014401385,0.0004079088,0.000034196128,0.00007693251,4.3410654e-7,0.00000567415,0.0027625095,0.99286926,0.000010952486,0.002805559,0.0009686986],"study_design_scores_gemma":[0.0009066496,0.00010578297,0.000074785356,0.000025873409,0.000055769422,0.00001293784,0.000034620443,0.0035961089,0.9924744,0.00003368022,0.0025074272,0.0001719846],"about_ca_topic_score_codex":0.00004720119,"about_ca_topic_score_gemma":0.0000010060685,"teacher_disagreement_score":0.40566513,"about_ca_system_score_codex":0.000021470052,"about_ca_system_score_gemma":0.00004723284,"threshold_uncertainty_score":0.4734816},"labels":[],"label_agreement":null},{"id":"W2553095237","doi":"10.1007/978-3-319-45318-7_2","title":"General Dynamic Considerations","year":2016,"lang":"en","type":"book-chapter","venue":"Lecture notes on mathematical modelling in the life sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Operon; Population; Physics; Stereochemistry; Chemistry; Biology; Biochemistry; Gene","score_opus":0.03183110868580181,"score_gpt":0.2691898880346501,"score_spread":0.2373587793488483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2553095237","genre_codex":"methods","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":[0.005196984,0.003938402,0.86962223,0.0066448417,0.00019141627,0.0006291214,0.000031914267,0.000035272213,0.11370979],"genre_scores_gemma":[0.9560077,0.0004712806,0.025463484,0.0035322935,0.00080666045,0.00003344212,0.000027436114,0.000071183946,0.013586522],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981715,0.0000785519,0.00039633247,0.00058177277,0.00046162633,0.00031017972],"domain_scores_gemma":[0.99874854,0.00040745767,0.00016130858,0.0005581432,0.00005085536,0.000073707386],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064875593,0.00033703138,0.00034497463,0.00011945296,0.00023193963,0.00007023811,0.00046142068,0.00035422936,0.00014878031],"category_scores_gemma":[0.00022504746,0.00018275667,0.00023057233,0.000060840026,0.0004927174,0.000003225392,0.00006280746,0.00024924052,0.00008365603],"study_design_candidate":"theoretical_or_conceptual","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":[0.000012385538,0.000036398305,0.0000035891846,0.000031320284,0.000101863414,0.00000608404,0.00010631572,0.7498266,0.00094934914,0.2479846,0.00023912852,0.0007023423],"study_design_scores_gemma":[0.00008942956,0.000121870704,7.315777e-7,0.00012750119,0.00007360607,0.000016504264,0.0000028666466,0.12394335,0.00033930613,0.8738268,0.0011636397,0.0002944147],"about_ca_topic_score_codex":8.5534487e-7,"about_ca_topic_score_gemma":0.000018555465,"teacher_disagreement_score":0.95081073,"about_ca_system_score_codex":0.000017112045,"about_ca_system_score_gemma":0.00014103207,"threshold_uncertainty_score":0.74526006},"labels":[],"label_agreement":null},{"id":"W2555961475","doi":"10.1371/journal.pcbi.1005256","title":"Precision of Readout at the hunchback Gene: Analyzing Short Transcription Time Traces in Living Fly Embryos","year":2016,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"European Research Council; Fondation ARC pour la Recherche sur le Cancer; Agence Nationale de la Recherche","keywords":"Biology; Transcription (linguistics); Transcription factor; Cell biology; Gene expression; Live cell imaging; Drosophila embryogenesis; Genetics; Computational biology; Gene; Cell","score_opus":0.01245493433862981,"score_gpt":0.24066952202929695,"score_spread":0.22821458769066713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2555961475","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":[0.99162793,0.0010660399,0.0067410744,0.00025802254,0.0000420478,0.00014350556,0.000027171318,0.000007868374,0.00008634719],"genre_scores_gemma":[0.99824727,0.00011620349,0.00090431835,0.00004636775,0.00011395588,0.000014106619,0.00017139353,0.000013498331,0.00037291562],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99868876,0.00026247636,0.00037027345,0.0003625756,0.00012257794,0.00019331407],"domain_scores_gemma":[0.99932057,0.0002015322,0.000105766325,0.00021984191,0.00011509354,0.000037194568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034110562,0.00013621023,0.00021474098,0.00009134638,0.000064643915,0.0000057315674,0.00019396831,0.00015215632,0.00009307425],"category_scores_gemma":[0.000085984495,0.00008717597,0.00013065527,0.00015510907,0.00014556957,0.000005429439,0.00008277746,0.00004659163,0.000025115081],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058576676,0.000053725096,0.03836875,0.0000052358046,0.00012884312,4.3220254e-7,0.00004050017,0.011746058,0.9428091,0.000027131648,0.00016009789,0.006601515],"study_design_scores_gemma":[0.001179043,0.000740874,0.3332656,0.00021617155,0.00026552018,0.000041449137,0.000052848194,0.030949071,0.6281716,0.002409371,0.0019412433,0.00076715334],"about_ca_topic_score_codex":0.0000054795114,"about_ca_topic_score_gemma":0.00005244065,"teacher_disagreement_score":0.31463748,"about_ca_system_score_codex":0.00003583346,"about_ca_system_score_gemma":0.00004818616,"threshold_uncertainty_score":0.35549328},"labels":[],"label_agreement":null},{"id":"W2558482369","doi":"10.1016/j.biosystems.2016.11.006","title":"An efficient finite-difference strategy for sensitivity analysis of stochastic models of biochemical systems","year":2016,"lang":"en","type":"article","venue":"Biosystems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Compute Canada","keywords":"Sensitivity (control systems); Parametric statistics; Computer science; Range (aeronautics); Parametric model; Stochastic modelling; Applied mathematics; Stochastic process; Mathematical optimization; Mathematics; Biological system; Statistics","score_opus":0.021981694982131747,"score_gpt":0.25580892588395765,"score_spread":0.2338272309018259,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2558482369","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":[0.68417627,0.0004670802,0.31474382,0.000004364423,0.00006107107,0.00021854235,0.00031433767,0.000007253852,0.000007274779],"genre_scores_gemma":[0.9995522,0.000007099843,0.0001105571,0.0000023309915,0.000108632405,0.000027450527,0.00012095166,0.000018686023,0.000052071548],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99836415,0.00016623027,0.0005216155,0.00047260144,0.00022428112,0.0002511069],"domain_scores_gemma":[0.9983397,0.0000998953,0.00036048336,0.0007284677,0.00035651482,0.000114926945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049942743,0.00019231708,0.0005886072,0.00019215891,0.000031346954,0.0000102366785,0.00018183455,0.00020688814,0.0000019297447],"category_scores_gemma":[0.000061907886,0.00013925202,0.00034285418,0.00037909416,0.00010493687,0.0000027180497,0.000042892578,0.000022532093,5.6024675e-7],"study_design_candidate":"simulation_or_modeling","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":[0.000054344393,0.000073319614,0.0003797298,0.000058839618,0.00065051287,2.2203953e-7,0.00001152839,0.37011155,0.62837875,0.00014971633,0.000017453187,0.00011401349],"study_design_scores_gemma":[0.00041583963,0.00029368722,0.0009168227,0.00007599513,0.0009194017,0.0000024289343,0.00009307118,0.77917325,0.21785803,0.000011220898,0.000009349829,0.00023090171],"about_ca_topic_score_codex":0.00007756047,"about_ca_topic_score_gemma":0.00003714669,"teacher_disagreement_score":0.4105207,"about_ca_system_score_codex":0.00002249951,"about_ca_system_score_gemma":0.000073556774,"threshold_uncertainty_score":0.5678533},"labels":[],"label_agreement":null},{"id":"W2559752444","doi":"10.1038/ncomms13788","title":"Transcriptional bursting is intrinsically caused by interplay between RNA polymerases on DNA","year":2016,"lang":"en","type":"article","venue":"Nature Communications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":73,"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":"Institute of Genetics; RIKEN","keywords":"Bursting; Biology; RNA; Transcriptional regulation; Polymerase; Cell biology; DNA; RNA polymerase; Gene; Gene expression; Genetics; Computational biology; Neuroscience","score_opus":0.013001019722169282,"score_gpt":0.29070205323747983,"score_spread":0.27770103351531056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2559752444","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":[0.9636163,0.010473663,0.0020280734,0.021181133,0.00012921175,0.00018525262,0.000424694,0.000053026968,0.0019086344],"genre_scores_gemma":[0.9963039,0.00051711703,0.0004901441,0.0011308735,0.0002110723,0.000020118854,0.00044059072,0.000023590821,0.00086255436],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99899817,0.00013569885,0.00022832207,0.00028327384,0.0001620404,0.00019251773],"domain_scores_gemma":[0.99819136,0.00011830766,0.0000922762,0.0013918963,0.00011082066,0.000095354066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012940998,0.0001568203,0.00015095682,0.0000629161,0.00019936837,0.000020049029,0.00081278745,0.00031835423,0.000047547735],"category_scores_gemma":[0.00010156237,0.00012214827,0.00014955524,0.00015636104,0.00015442725,0.0000052089954,0.00016744096,0.00027732766,0.000022847302],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001712944,0.00008512606,0.0071031754,0.0000021528272,0.0002480636,2.3025916e-7,0.00003227897,0.000002003149,0.94455343,0.00072428485,0.034716338,0.012515773],"study_design_scores_gemma":[0.0007539235,0.00015301666,0.02258683,0.0000705689,0.00015620903,0.0000027653705,0.000025747431,0.000030604475,0.51472396,0.00013798215,0.46094817,0.00041025033],"about_ca_topic_score_codex":0.0000050911035,"about_ca_topic_score_gemma":0.00005926807,"teacher_disagreement_score":0.4298295,"about_ca_system_score_codex":0.000033083823,"about_ca_system_score_gemma":0.000051604686,"threshold_uncertainty_score":0.49810618},"labels":[],"label_agreement":null},{"id":"W2562068785","doi":"10.1515/gmj-2016-0065","title":"Piecewise synergetic systems and applications in biochemical systems theory","year":2016,"lang":"en","type":"article","venue":"Georgian Mathematical Journal","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Victoria","funders":"Norges Forskningsråd; Universidad Complutense de Madrid","keywords":"Piecewise; Convergence (economics); Mathematics; Applied mathematics; Mathematical optimization; Sequence (biology); Mathematical analysis","score_opus":0.005782077941406548,"score_gpt":0.22033480392373292,"score_spread":0.21455272598232636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2562068785","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":[0.835058,0.007510628,0.15598553,0.00020583883,0.00010652094,0.00034573587,0.000009990671,0.000017161361,0.00076058955],"genre_scores_gemma":[0.99785686,0.00028730574,0.0003821392,0.000017529675,0.00041922843,0.00004756727,0.0000048973357,0.000026677568,0.00095778797],"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99851406,0.00019307432,0.00046998216,0.0002842288,0.0001993594,0.0003393023],"domain_scores_gemma":[0.99907935,0.00009221708,0.00013680873,0.00035329862,0.0000781906,0.0002601448],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007824095,0.00018150629,0.0002852023,0.00010136843,0.00008567922,0.00007647235,0.00021730759,0.00017659318,0.000034964647],"category_scores_gemma":[0.00012902179,0.000115064824,0.00009790588,0.00012600844,0.00016538841,0.0000063797224,0.00009223604,0.00011776191,0.000034787023],"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":[0.0001529615,0.0005841516,0.009409728,0.00058052945,0.0007483242,0.000066848756,0.00018456772,0.0008473149,0.84869057,0.12443343,0.004989886,0.009311691],"study_design_scores_gemma":[0.024186412,0.0024972984,0.025394067,0.008935618,0.0035099352,0.030045953,0.013107352,0.01983617,0.12875731,0.50035906,0.23210253,0.011268316],"about_ca_topic_score_codex":8.043224e-7,"about_ca_topic_score_gemma":4.9020895e-7,"teacher_disagreement_score":0.7199333,"about_ca_system_score_codex":0.000036093763,"about_ca_system_score_gemma":0.000048020873,"threshold_uncertainty_score":0.46922073},"labels":[],"label_agreement":null},{"id":"W2562785893","doi":"","title":"Evolving Reaction-Diffusion Systems on GPU","year":2011,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Reaction–diffusion system; Computation; Diffusion; Simple (philosophy); Work (physics); Optimization problem; Mathematical optimization; Algorithm; Mathematics; Physics","score_opus":0.015058656914411427,"score_gpt":0.21584671482586115,"score_spread":0.2007880579114497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2562785893","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":[0.94051015,0.00041686543,0.0009910128,0.000012956294,0.00024184292,0.00008315162,8.006506e-7,0.00002515649,0.05771806],"genre_scores_gemma":[0.9928901,0.00005634706,0.00025496475,0.000068666275,0.00022953586,0.000008759425,0.000021379346,0.00001514129,0.0064550606],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993394,0.00003758687,0.00012814271,0.00024838955,0.000099045246,0.00014744738],"domain_scores_gemma":[0.9994501,0.0000033411627,0.000051074912,0.00037717103,0.000055521192,0.00006277458],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000104679115,0.00009915728,0.00009052751,0.000040901596,0.00006347706,0.000010777796,0.000099868645,0.00010261333,0.00009863765],"category_scores_gemma":[0.00001490877,0.000083934145,0.000079846664,0.000071245384,0.000017958057,0.0000015716661,0.000044678138,0.000039637427,0.00008179748],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047704685,0.00010332006,0.009232932,0.000010374738,0.00012441775,0.0000034518714,0.000043714266,0.00016000657,0.9743217,0.00060159643,0.014080493,0.0012702713],"study_design_scores_gemma":[0.001277834,0.0011995616,0.10249479,0.000085069245,0.00023501251,0.00007585244,0.00086487306,0.008505492,0.7285373,0.00019647181,0.15521798,0.0013097528],"about_ca_topic_score_codex":0.00009683163,"about_ca_topic_score_gemma":0.000025049774,"teacher_disagreement_score":0.2457844,"about_ca_system_score_codex":0.00001301154,"about_ca_system_score_gemma":0.000015536769,"threshold_uncertainty_score":0.3422735},"labels":[],"label_agreement":null},{"id":"W2563600868","doi":"10.3934/mbe.2017034","title":"Modeling and simulation for toxicity assessment","year":2017,"lang":"en","type":"article","venue":"Mathematical Biosciences & Engineering","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Health; University of Calgary; University of Alberta; MacEwan University","funders":"","keywords":"Toxicant; Biological system; Toxicity; Computer science; Maximization; Cytotoxicity; Chemistry; Intracellular; Applied mathematics; Statistics; In vitro; Mathematics; Biology; Mathematical optimization; Biochemistry","score_opus":0.018667492934862685,"score_gpt":0.29742593198629963,"score_spread":0.27875843905143693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2563600868","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":[0.53124774,0.00003157535,0.46852162,0.000040131054,0.0000259379,0.00007056855,9.734258e-7,0.0000059623194,0.00005550212],"genre_scores_gemma":[0.9663212,0.0000066786515,0.03352773,0.000010613208,0.000077943216,0.000014243555,0.0000022805393,0.000006649241,0.000032672862],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994334,0.000004135583,0.00011819692,0.000199675,0.00009345683,0.00015115009],"domain_scores_gemma":[0.99961984,0.00001687646,0.000034217217,0.00024392757,0.000027283486,0.00005784304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027150364,0.00007965588,0.000097549586,0.000021448834,0.0002003137,0.00010219114,0.00015902684,0.00004814954,0.0000026425655],"category_scores_gemma":[0.0001819251,0.000068704496,0.000047685742,0.000021070977,0.000043669526,0.000008067304,0.00008878096,0.000023540897,5.31522e-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":[0.0000028061852,0.000013924019,0.0002387438,0.00003267381,0.000015759126,1.4225597e-7,0.000013678709,0.80813926,0.18898036,0.001828609,0.0000035530722,0.00073046447],"study_design_scores_gemma":[0.00011602272,0.00003188733,0.00035300155,0.000010972976,0.000014344016,9.1370634e-7,0.000010108912,0.9903089,0.008381755,0.0005722875,0.00010972976,0.00009010222],"about_ca_topic_score_codex":8.088385e-7,"about_ca_topic_score_gemma":0.0000013610247,"teacher_disagreement_score":0.43507347,"about_ca_system_score_codex":0.000006844477,"about_ca_system_score_gemma":0.000011509221,"threshold_uncertainty_score":0.2801688},"labels":[],"label_agreement":null},{"id":"W2563968870","doi":"10.1109/cibcb.2016.7758126","title":"Evolving graph compression using similarity measures for bioinformatics applications","year":2016,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Crossover; Computer science; Graph; Similarity (geometry); Theoretical computer science; Modular decomposition; Data compression; Data mining; Algorithm; Artificial intelligence; Pathwidth; Line graph","score_opus":0.022232868545273995,"score_gpt":0.2699936205688718,"score_spread":0.24776075202359776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2563968870","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":[0.04547004,0.0003379462,0.9532717,0.000098248114,0.000030151996,0.00026392724,0.00001569359,0.0000193028,0.0004929886],"genre_scores_gemma":[0.947997,0.00005768354,0.051338837,0.00009240221,0.00015254074,0.00004496821,0.000033308454,0.000014329643,0.00026892585],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999352,0.000018802071,0.00018643278,0.00017393463,0.000095428906,0.00017343168],"domain_scores_gemma":[0.99934125,0.000014287647,0.00007858498,0.00034560554,0.00015604273,0.00006424356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001474295,0.00010040824,0.0001033912,0.0000437839,0.00014752838,0.000016370015,0.00013825222,0.00009788721,0.00001677559],"category_scores_gemma":[0.000028454855,0.00006732126,0.00012861259,0.000085193344,0.00004904091,0.00000482588,0.00006772815,0.000017605798,0.00000285452],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017303413,0.00003482718,0.00411831,0.000024474337,0.00011617255,4.487484e-8,0.000009907017,0.0005961533,0.96619904,0.00021313963,0.0048898268,0.02378081],"study_design_scores_gemma":[0.0015241224,0.00013568124,0.0024529132,0.00006821214,0.00028632188,0.000010775034,0.00013604398,0.03935889,0.7934769,0.0032464087,0.15851513,0.0007886193],"about_ca_topic_score_codex":0.0000029141481,"about_ca_topic_score_gemma":0.000016860331,"teacher_disagreement_score":0.902527,"about_ca_system_score_codex":0.000013208153,"about_ca_system_score_gemma":0.000033950168,"threshold_uncertainty_score":0.27452815},"labels":[],"label_agreement":null},{"id":"W2566463892","doi":"10.1007/s11229-016-1307-6","title":"Network analyses in systems biology: new strategies for dealing with biological complexity","year":2017,"lang":"en","type":"article","venue":"Synthese","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":129,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Biological network; Computer science; Systems biology; Philosophy of science; Network science; Network analysis; Complex system; Management science; Network theory; Class (philosophy); Data science; Complex network; Artificial intelligence; Epistemology; Biology; Computational biology; Mathematics","score_opus":0.14738379338061366,"score_gpt":0.3650359315099182,"score_spread":0.21765213812930453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2566463892","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":[0.97028756,0.0036883208,0.024497349,0.00015608591,0.000108400745,0.00030361308,0.000017236745,0.000018162948,0.0009232802],"genre_scores_gemma":[0.9958879,0.00007965901,0.0032548194,0.00002981782,0.00055175246,0.000031133884,0.000058108526,0.000016373262,0.000090457455],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99891067,0.000079941165,0.00020914637,0.00039978317,0.000054332984,0.0003461513],"domain_scores_gemma":[0.99898535,0.00003756912,0.00018795411,0.0006511218,0.00005358278,0.000084437335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002749738,0.00017802969,0.00032130934,0.000028704417,0.00022615583,0.00010542378,0.00037792017,0.00017502364,0.000010138471],"category_scores_gemma":[0.00008990103,0.00012873801,0.00010325351,0.00004076032,0.00024354654,0.0000056892623,0.00009939683,0.000059457845,0.0000023749596],"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":[0.001351201,0.00016192294,0.41273078,0.00010405483,0.0015517452,0.000022991888,0.000096139294,0.15992534,0.3663972,0.048229724,0.002469745,0.00695915],"study_design_scores_gemma":[0.012159932,0.006795215,0.5346117,0.0013322845,0.0017541875,0.00019215902,0.0059049064,0.07752954,0.061047193,0.16510853,0.12562528,0.00793907],"about_ca_topic_score_codex":0.0007115512,"about_ca_topic_score_gemma":0.0013163993,"teacher_disagreement_score":0.30535,"about_ca_system_score_codex":0.00001117023,"about_ca_system_score_gemma":0.000091911475,"threshold_uncertainty_score":0.5249784},"labels":[],"label_agreement":null},{"id":"W2570327462","doi":"10.1002/cjs.11309","title":"Bernstein approximations in glasso‐based estimation of biological networks","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Graphical model; Inference; Computer science; Coordinate descent; Measure (data warehouse); Statistical inference; Polynomial; Algorithm; Preprocessor; Lasso (programming language); Scale (ratio); Artificial intelligence; Theoretical computer science; Mathematics; Data mining; Statistics","score_opus":0.019470177851136708,"score_gpt":0.2477278420205126,"score_spread":0.22825766416937587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2570327462","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":[0.5967406,0.00038417318,0.40227577,0.00013037062,0.00014633314,0.000067163644,0.00010155545,6.7518255e-7,0.00015336619],"genre_scores_gemma":[0.9745257,0.000027794968,0.025236975,0.00002803076,0.0000844106,0.0000010655167,0.00006511868,0.0000074715695,0.000023459415],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992741,0.00005045366,0.0003467535,0.00008837252,0.00007672881,0.00016361095],"domain_scores_gemma":[0.99890316,0.00002149114,0.0004591023,0.00025120593,0.0001785692,0.00018646785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027600082,0.000079055375,0.00017758203,0.00011139708,0.00010331266,0.00003210992,0.00024934064,0.00010703078,0.000020640891],"category_scores_gemma":[0.00042904518,0.00007544348,0.00005839181,0.000052825577,0.00016378485,0.0000047509766,0.000012517489,0.000088018154,6.527272e-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":[0.000054559605,0.000055902765,0.21422847,0.000033540466,0.0001586142,0.0000970725,0.000063293744,0.7484028,0.0028406563,0.002365293,0.0051582484,0.02654161],"study_design_scores_gemma":[0.0019612617,0.0007001931,0.47164658,0.0001735444,0.00017244376,0.00005994824,0.00009759582,0.5124637,0.005640691,0.0026233448,0.0039894264,0.00047128825],"about_ca_topic_score_codex":0.00046082312,"about_ca_topic_score_gemma":0.013448275,"teacher_disagreement_score":0.3777851,"about_ca_system_score_codex":0.000037541555,"about_ca_system_score_gemma":0.00050416664,"threshold_uncertainty_score":0.7504453},"labels":[],"label_agreement":null},{"id":"W2570629027","doi":"10.1371/journal.pbio.1002585","title":"Single-Cell-Based Analysis Highlights a Surge in Cell-to-Cell Molecular Variability Preceding Irreversible Commitment in a Differentiation Process","year":2016,"lang":"en","type":"article","venue":"PLoS Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":302,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Beijing Advanced Innovation Center for Structural Biology, Tsinghua University; École Normale Supérieure de Lyon; Ligue Contre le Cancer; Université Claude Bernard Lyon 1; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Agence Nationale de la Recherche","keywords":"Biology; Gene expression; Cellular differentiation; Progenitor cell; Cell; Population; Gene; Cell fate determination; Gene expression profiling; Phenotype; Genetics; Computational biology; Cell biology; Stem cell; Transcription factor","score_opus":0.010436860354343302,"score_gpt":0.22645304808662597,"score_spread":0.21601618773228268,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2570629027","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":[0.9852529,0.00015494988,0.013492774,0.00028096765,0.00005274226,0.00040169148,0.000019349429,0.000016690909,0.00032791353],"genre_scores_gemma":[0.99887234,0.000024041685,0.00051213277,0.00009706375,0.000039113886,0.000112947455,0.00021552389,0.000022694901,0.00010412743],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9975015,0.0005186719,0.00047809433,0.00086764916,0.00013878001,0.0004953224],"domain_scores_gemma":[0.9988976,0.000089044974,0.00018558191,0.0005990905,0.00009921999,0.00012947405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043857654,0.0002766704,0.00048458486,0.00043002967,0.00006429257,0.000021457006,0.00030742626,0.0003123464,0.0000531432],"category_scores_gemma":[0.00007406977,0.00022233302,0.00021450693,0.0009592077,0.000056502515,0.0000049714445,0.00012312939,0.00008250532,0.000011297258],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007582231,0.0006996165,0.28419825,0.000036864258,0.0001115655,0.0000025589886,0.000032192664,0.001958801,0.71276385,0.000006249646,0.000021428958,0.000092781615],"study_design_scores_gemma":[0.0013364474,0.0002617618,0.007813045,0.00002291942,0.0003006883,2.789895e-7,0.000018415947,0.002447765,0.9869558,0.00011485632,0.00037330948,0.00035466233],"about_ca_topic_score_codex":0.00005511017,"about_ca_topic_score_gemma":0.0005189903,"teacher_disagreement_score":0.27638522,"about_ca_system_score_codex":0.00015083425,"about_ca_system_score_gemma":0.00008663964,"threshold_uncertainty_score":0.9066478},"labels":[],"label_agreement":null},{"id":"W2576634470","doi":"10.1109/bibm.2016.7822520","title":"Optimal control for context-sensitive probabilistic Boolean networks with perturbation using probabilisitic model checking","year":2016,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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 Calgary","funders":"National Natural Science Foundation of China","keywords":"Reachability; Probabilistic logic; Computer science; Model checking; Context (archaeology); Optimal control; Computation; Theoretical computer science; Reachability problem; Mathematical optimization; Algorithm; Artificial intelligence; Mathematics","score_opus":0.012560266620809944,"score_gpt":0.2266012482448214,"score_spread":0.21404098162401144,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2576634470","genre_codex":"methods","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":[0.4090664,0.000082640014,0.59012973,0.000075682714,0.000018401282,0.00053243636,0.000008696356,0.00001720204,0.00006880258],"genre_scores_gemma":[0.9848311,0.0000070130545,0.01385648,0.0002039705,0.00023854413,0.00008006695,0.0000364945,0.000049388334,0.0006969688],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99856436,0.00008057054,0.00025963227,0.0005560465,0.00013364173,0.00040572835],"domain_scores_gemma":[0.99895316,0.00006673758,0.00013247921,0.00035112852,0.0003886717,0.00010784076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003174637,0.00024736795,0.0002769707,0.000039545605,0.00013203135,0.0000320732,0.000111779984,0.00016141344,0.000005526945],"category_scores_gemma":[0.0000916461,0.00015953103,0.00015541493,0.0000793902,0.0001437611,0.00000991698,0.000035914476,0.00004384159,9.426567e-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":[0.00055179663,0.000037214635,0.00043475386,0.000018823317,0.00022575313,9.2108826e-7,0.000019408499,0.88340175,0.11341908,0.0008422666,0.00009721617,0.00095103495],"study_design_scores_gemma":[0.0019411343,0.00030056745,0.00012725589,0.00006538007,0.00025158742,0.000018015828,0.000056098503,0.9803781,0.01622218,0.00022014721,0.000083928106,0.00033558614],"about_ca_topic_score_codex":0.000004066318,"about_ca_topic_score_gemma":0.00003847305,"teacher_disagreement_score":0.57627326,"about_ca_system_score_codex":0.0000767189,"about_ca_system_score_gemma":0.00013403482,"threshold_uncertainty_score":0.65054864},"labels":[],"label_agreement":null},{"id":"W2577175977","doi":"10.1109/tcbb.2017.2653110","title":"Dynamics in Epistasis Analysis","year":2017,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Computational Biology and Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ottawa Hospital; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Health Canada","keywords":"Epistasis; Identifiability; Discriminative model; Observable; Computational biology; Biology; Genetics; Gene; Computer science; Artificial intelligence; Machine learning; Physics","score_opus":0.01157112162546123,"score_gpt":0.2768004508786912,"score_spread":0.26522932925322995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2577175977","genre_codex":"methods","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":[0.4731085,0.00006541514,0.5254308,0.0006794886,0.00012277655,0.00010541649,0.0001408338,0.000011590105,0.00033516044],"genre_scores_gemma":[0.97969824,0.00013530056,0.019527787,0.00017110683,0.000033725795,0.000010463126,0.0003224488,0.000006843348,0.000094113886],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913156,0.00004427591,0.00032511452,0.00022363315,0.000084815496,0.00019062699],"domain_scores_gemma":[0.99913174,0.00004910955,0.00016908567,0.00050950085,0.000071437535,0.00006911832],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019935532,0.0001580704,0.00022651549,0.00026116197,0.0004018853,0.00005318504,0.00028566195,0.00019917276,0.000016487706],"category_scores_gemma":[0.000028327284,0.00014924143,0.00015729734,0.00017811457,0.00023225273,0.000012874596,0.000016655811,0.00011895891,0.000009321911],"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":[0.0002697311,0.00036142717,0.14023186,0.00006826554,0.0034776682,0.000006004667,0.00019534069,0.6959851,0.00069398043,0.0017769167,0.0001592377,0.15677446],"study_design_scores_gemma":[0.0011881845,0.00032778727,0.10285,0.000016757578,0.00056171726,0.00002161174,0.000233486,0.8869676,0.0014283163,0.0053071906,0.0005510215,0.00054633763],"about_ca_topic_score_codex":0.000032387758,"about_ca_topic_score_gemma":0.00070489995,"teacher_disagreement_score":0.5065897,"about_ca_system_score_codex":0.000037000835,"about_ca_system_score_gemma":0.000045770572,"threshold_uncertainty_score":0.60858893},"labels":[],"label_agreement":null},{"id":"W2578454336","doi":"10.1109/bibm.2016.7822523","title":"The MSS of complex networks with centrality based preference and its application to biomolecular networks","year":2016,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"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 Saskatchewan","funders":"","keywords":"Centrality; Controllability; Biological network; Network controllability; Complex network; Computer science; Betweenness centrality; Network science; Value (mathematics); Theoretical computer science; Computational biology; Mathematics; Biology; Machine learning","score_opus":0.012202262401056194,"score_gpt":0.2251873735313509,"score_spread":0.21298511113029472,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2578454336","genre_codex":"methods","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":[0.2711282,0.00053742796,0.7273561,0.0005575451,0.000012864686,0.00028619065,0.000003957243,0.0000091816555,0.000108545035],"genre_scores_gemma":[0.9988344,0.00013607123,0.0005829684,0.00017570333,0.00005780009,0.000032531647,0.000025622292,0.000012771795,0.00014215606],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990701,0.00007943214,0.00017732449,0.00032008576,0.00011225622,0.0002408053],"domain_scores_gemma":[0.99918306,0.00002308802,0.000088811925,0.00045983624,0.00013356128,0.00011161496],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001940214,0.00012813494,0.00012707287,0.00001599537,0.00008723529,0.000012949933,0.0001926272,0.00008284394,0.000008493194],"category_scores_gemma":[0.000012173396,0.000067664805,0.000045005694,0.00016580374,0.00010873096,0.0000018761896,0.00007977467,0.000026223423,0.000001101672],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031079524,0.00005268831,0.015094379,0.000011603377,0.00019659067,4.647306e-7,0.0000055583632,0.051244333,0.9008314,0.0009705877,0.0009405835,0.030340996],"study_design_scores_gemma":[0.0018485972,0.00077035796,0.09947479,0.00006609768,0.00022049852,0.000007991474,0.0000335606,0.24864538,0.6102742,0.000088830275,0.0377617,0.0008080401],"about_ca_topic_score_codex":0.000009418324,"about_ca_topic_score_gemma":0.00012694862,"teacher_disagreement_score":0.72770613,"about_ca_system_score_codex":0.00000856661,"about_ca_system_score_gemma":0.000025116064,"threshold_uncertainty_score":0.27592906},"labels":[],"label_agreement":null},{"id":"W2596548604","doi":"10.3934/dcdsb.2017091","title":"Domain control of nonlinear networked systems and applications to complex disease networks","year":2017,"lang":"en","type":"article","venue":"Discrete and Continuous Dynamical Systems - B","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"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 Saskatchewan","funders":"","keywords":"Controllability; Domain (mathematical analysis); Complex network; Attractor; Nonlinear system; Computer science; Biological network; Gene regulatory network; State (computer science); State space; Control (management); Topology (electrical circuits); Distributed computing; Mathematics; Artificial intelligence; Physics; Biology; Applied mathematics","score_opus":0.006418144702127781,"score_gpt":0.2395056491316779,"score_spread":0.23308750442955012,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2596548604","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":[0.6654498,0.0059412965,0.3266333,0.00016274351,0.00013629829,0.0011806772,0.00022425063,0.00001828678,0.00025335862],"genre_scores_gemma":[0.99838334,0.00010248326,0.00012238162,0.00004715299,0.00061566057,0.00017465177,0.00018617739,0.00002776878,0.000340398],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985254,0.00012562827,0.00040639905,0.00048105163,0.00014725285,0.0003142849],"domain_scores_gemma":[0.9984013,0.000022310243,0.00027893655,0.00080766814,0.00010684949,0.00038295815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002595566,0.0002218458,0.0004964146,0.00003267155,0.0003040413,0.00016964684,0.0002910825,0.00014544626,0.0000012543138],"category_scores_gemma":[0.000018620853,0.00019581479,0.00011158238,0.000051038973,0.00022218851,0.000006280192,0.0001843269,0.00007031577,7.9495226e-7],"study_design_candidate":"simulation_or_modeling","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":[0.0024260185,0.0004917509,0.64544487,0.0012797308,0.0039332295,0.000059531463,0.00015430394,0.20029604,0.07881196,0.040629897,0.0034362408,0.023036405],"study_design_scores_gemma":[0.00232646,0.00031183855,0.077970766,0.00019403879,0.00048743136,0.000026190824,0.00027560577,0.8465058,0.00001682287,0.000080802,0.070997305,0.0008069096],"about_ca_topic_score_codex":0.00016734844,"about_ca_topic_score_gemma":0.00005571657,"teacher_disagreement_score":0.6462098,"about_ca_system_score_codex":0.000009956853,"about_ca_system_score_gemma":0.000018536095,"threshold_uncertainty_score":0.79850954},"labels":[],"label_agreement":null},{"id":"W2603514654","doi":"10.1371/journal.pone.0090781","title":"CaSPIAN: A Causal Compressive Sensing Algorithm for Discovering Directed Interactions in Gene Networks","year":2014,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":23,"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 Emerging Frontiers; Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Granger causality; Subspace topology; Inference; Compressed sensing; Gene regulatory network; Computer science; Algorithm; False positive paradox; Causality (physics); Causal inference; Data mining; Noise (video); Artificial intelligence; Pattern recognition (psychology); Machine learning; Mathematics; Biology; Gene; Statistics; Gene expression","score_opus":0.01894893612154544,"score_gpt":0.2377189697917797,"score_spread":0.21877003367023426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2603514654","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":[0.8151658,0.00026481124,0.18413024,0.000047090587,0.00007634661,0.00020222239,0.000011929804,0.000023161794,0.00007836476],"genre_scores_gemma":[0.9665038,0.00004265515,0.031898245,0.000066482186,0.00090735446,0.000039296763,0.0002254675,0.000032663207,0.0002840124],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990516,0.000072096,0.00020006063,0.00031884367,0.00009223987,0.00026521628],"domain_scores_gemma":[0.99944353,0.000035075307,0.00008706107,0.00027972524,0.000087701555,0.00006688225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010225693,0.00013949558,0.00023285516,0.000058457208,0.00007839007,0.000026445852,0.000084793566,0.000073258285,0.000004989214],"category_scores_gemma":[0.000050438037,0.00015112865,0.00008493374,0.0001268522,0.000031497144,0.000004580015,0.00008022174,0.00009210784,0.0000017297175],"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":[0.000065958906,0.0004615479,0.0032078188,0.000032046744,0.0009216975,0.000006273955,0.00007421052,0.03254169,0.94105095,0.0000066396447,0.00037182198,0.021259356],"study_design_scores_gemma":[0.00046948416,0.00006678905,0.0013558236,0.00006793475,0.00014744837,0.000005203153,0.000019658717,0.78934944,0.20775814,0.00001608609,0.00053882896,0.00020518483],"about_ca_topic_score_codex":0.000057876645,"about_ca_topic_score_gemma":0.00045858196,"teacher_disagreement_score":0.75680774,"about_ca_system_score_codex":0.000029517832,"about_ca_system_score_gemma":0.000017297292,"threshold_uncertainty_score":0.6162848},"labels":[],"label_agreement":null},{"id":"W2604023245","doi":"10.1111/biom.12685","title":"Estimating Time-Varying Directed Gene Regulation Networks","year":2017,"lang":"en","type":"article","venue":"Biometrics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Computational biology; Gene regulatory network; Gene; Biology; Genetics; Gene expression","score_opus":0.015354681371267553,"score_gpt":0.2591898043408331,"score_spread":0.24383512296956555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2604023245","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":[0.9027989,0.0020513781,0.09267752,0.00006897285,0.00059795956,0.00018164658,0.000008352618,0.000087982175,0.0015272868],"genre_scores_gemma":[0.9690496,0.00005696639,0.028364273,0.000034836663,0.00096860307,0.000006727667,0.00027745176,0.0000327389,0.0012088349],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99885374,0.000045364774,0.0002303571,0.00038729777,0.00019532563,0.0002879364],"domain_scores_gemma":[0.9984745,0.000017555849,0.00030844685,0.0009497474,0.00014698559,0.00010280834],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034850786,0.00016316811,0.00017831498,0.0002837306,0.0005167943,0.00015365057,0.0003857944,0.0002072123,0.000030658222],"category_scores_gemma":[0.00049021986,0.00016911664,0.0001244827,0.0006586969,0.000076002434,0.000007987988,0.00023897657,0.000060599203,0.000028098922],"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":[0.000038961694,0.00006966347,0.020147333,0.000016869655,0.00028851745,0.0000066628622,0.000010183052,0.059225176,0.8238914,0.000011226605,0.0070705716,0.08922345],"study_design_scores_gemma":[0.00056283275,0.000090086665,0.1169766,0.000018516896,0.00012488672,0.000014821923,0.0000015912775,0.81347924,0.06133847,0.000052495,0.006853015,0.00048743014],"about_ca_topic_score_codex":0.000015727666,"about_ca_topic_score_gemma":0.000002324353,"teacher_disagreement_score":0.7625529,"about_ca_system_score_codex":0.000027651991,"about_ca_system_score_gemma":0.000026733233,"threshold_uncertainty_score":0.68963766},"labels":[],"label_agreement":null},{"id":"W2608677323","doi":"10.1371/journal.pone.0176228","title":"Transcriptional bursting in Drosophila development: Stochastic dynamics of eve stripe 2 expression","year":2017,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"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 Victoria; British Columbia Institute of Technology","funders":"National Institutes of Health","keywords":"Drosophila embryogenesis; Gap gene; Krüppel; Biology; Genetics; Transcription factor; Gene; Gene expression; Transcription (linguistics); Drosophila melanogaster; Regulation of gene expression","score_opus":0.029239507116077798,"score_gpt":0.23100086934053357,"score_spread":0.2017613622244558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2608677323","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":[0.9977607,0.00025937252,0.0015852517,0.00006575263,0.000016796117,0.000089360394,0.000007414561,0.000004127172,0.00021120241],"genre_scores_gemma":[0.9969236,0.000016497901,0.0026074005,0.000009286989,0.00008624305,0.000013308614,0.00012262205,0.00001416105,0.00020686757],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991464,0.000023864282,0.00023197144,0.00022999392,0.00020565589,0.00016213841],"domain_scores_gemma":[0.9993517,0.000006449618,0.0001608799,0.00035897383,0.000074814256,0.00004717548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013727954,0.00010443607,0.00017938286,0.000051373525,0.000118117736,0.000014587587,0.00024163976,0.000106298365,0.000014439835],"category_scores_gemma":[0.00008334576,0.00011190417,0.000049791193,0.000038551054,0.00006385572,0.0000047872672,0.000078943965,0.00006775289,0.000002130106],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043335505,0.00031604967,0.025734007,0.000043525957,0.000120901794,0.0000011674246,0.000047899557,0.0012094255,0.97205395,0.00004717295,0.0000055088512,0.000377063],"study_design_scores_gemma":[0.0012562758,0.0000894503,0.19886214,0.0005435703,0.00014054927,0.000001853193,0.000056032073,0.017345477,0.7808907,0.00037902503,0.000032647113,0.00040229232],"about_ca_topic_score_codex":0.000004875496,"about_ca_topic_score_gemma":0.00006946392,"teacher_disagreement_score":0.19116324,"about_ca_system_score_codex":0.000026547217,"about_ca_system_score_gemma":0.00006763716,"threshold_uncertainty_score":0.45633197},"labels":[],"label_agreement":null},{"id":"W2609433445","doi":"10.1101/129296","title":"System Identification Using Compressed Sensing Reveals Signaling-Decoding System by Gene Expression","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Core Research for Evolutional Science and Technology; Institute of Genetics; Japan Science and Technology Agency; Japan Society for the Promotion of Science; Research Organization of Information and Systems","keywords":"Decoding methods; Computer science; Identification (biology); Computational biology; Gene expression; Gene; Compressed sensing; Biology; Algorithm; Genetics","score_opus":0.01675570234796958,"score_gpt":0.23323152918640497,"score_spread":0.2164758268384354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2609433445","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":[0.9073891,0.004353519,0.08576723,0.000013478526,0.0012727326,0.00071230385,0.00024479337,0.00024149008,0.0000053601066],"genre_scores_gemma":[0.98612285,0.00009549068,0.012106152,0.000019047613,0.0013469404,0.000046544876,0.00001344734,0.00023587051,0.000013668687],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9952282,0.00051164615,0.0011142766,0.0018525275,0.00057720905,0.0007161625],"domain_scores_gemma":[0.9934266,0.0000241642,0.0020473027,0.0033460725,0.00081711356,0.00033874708],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0013681544,0.0008160494,0.00096302025,0.00023192275,0.0008248165,0.0006282404,0.0010103197,0.0011171134,0.0000029775563],"category_scores_gemma":[0.00012058387,0.0009392427,0.00040647705,0.00019480346,0.00013208785,0.000022487602,0.00092297833,0.0004468662,0.000017910648],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029398836,0.000030357949,0.0013197577,0.001042564,0.00034149023,0.00002621778,0.0000034932598,0.005417926,0.99125034,0.000011882378,0.00052521616,0.0000013703815],"study_design_scores_gemma":[0.00035219744,0.00001646071,0.00068431866,0.0017127458,0.00045292336,2.4226495e-7,0.000012774185,0.023286423,0.9722143,2.0364138e-7,0.00035081556,0.00091664284],"about_ca_topic_score_codex":0.000049719,"about_ca_topic_score_gemma":8.3229924e-7,"teacher_disagreement_score":0.07873374,"about_ca_system_score_codex":0.0004986914,"about_ca_system_score_gemma":0.00033916402,"threshold_uncertainty_score":0.9993058},"labels":[],"label_agreement":null},{"id":"W2610597045","doi":"10.1186/s13040-017-0136-6","title":"Study of Meta-analysis strategies for network inference using information-theoretic approaches","year":2017,"lang":"en","type":"article","venue":"BioData Mining","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Princess Margaret Cancer Centre; University of Toronto; Ontario Institute for Cancer Research","funders":"Université de Liège; Fonds De La Recherche Scientifique - FNRS","keywords":"Pairwise comparison; Computer science; Data mining; Inference; Set (abstract data type); Reverse engineering; Machine learning; Artificial intelligence","score_opus":0.21284763766452527,"score_gpt":0.3422631988385581,"score_spread":0.12941556117403283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2610597045","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":[0.95629406,0.0005366302,0.04253909,0.00001626934,0.000039098748,0.00028536873,0.00006582367,0.0000058900487,0.00021778408],"genre_scores_gemma":[0.9896316,0.000008498205,0.009926555,0.000015495361,0.00008976804,0.000038129456,0.00025903908,0.000008985703,0.000021913505],"study_design_codex":"simulation_or_modeling","study_design_gemma":"meta_analysis","domain_scores_codex":[0.9989002,0.00006826757,0.00039479884,0.0002753216,0.00014650777,0.0002149025],"domain_scores_gemma":[0.99795383,0.000030920633,0.0005800706,0.0012683623,0.000121212186,0.00004559193],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056296866,0.00017008561,0.00051986286,0.00008841585,0.000340019,0.0001996672,0.0005709426,0.00008969317,0.000015374473],"category_scores_gemma":[0.000115070936,0.00014573953,0.0004133616,0.00015678868,0.00011655289,0.000044075357,0.00028277698,0.00003262347,6.489064e-7],"study_design_candidate":"meta_analysis","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":[0.0001979097,0.0003402522,0.104759015,0.00014887434,0.28348234,0.000001878172,0.0022562162,0.6001625,0.0028390302,0.0027611929,0.00085784914,0.0021929147],"study_design_scores_gemma":[0.0033634573,0.0018685057,0.031245654,0.000023080524,0.7075258,0.000008455584,0.043986678,0.19258279,0.01084753,0.0012539403,0.0048993467,0.0023947875],"about_ca_topic_score_codex":0.0000546036,"about_ca_topic_score_gemma":0.00017054382,"teacher_disagreement_score":0.42404342,"about_ca_system_score_codex":0.00000515617,"about_ca_system_score_gemma":0.00008053051,"threshold_uncertainty_score":0.5943085},"labels":[],"label_agreement":null},{"id":"W2613960469","doi":"10.1101/369371","title":"Backward evolution from gene network dynamics","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Laufer Center for Physical and Quantitative Biology, Stony Brook University; Division of Integrative Organismal Systems; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; National Science Foundation","keywords":"Regulator; Effector; Population; Gene regulatory network; Gene; Mutation; Mutant; Regulation of gene expression","score_opus":0.006762785134557506,"score_gpt":0.19844742653599093,"score_spread":0.19168464140143343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2613960469","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":[0.9521039,0.005926339,0.03873799,0.00007423856,0.002009855,0.00045119177,0.0005135925,0.00016672403,0.000016163447],"genre_scores_gemma":[0.97780657,0.0004588124,0.014470736,0.00016703665,0.0067119347,0.000102093894,0.000036709065,0.00022284112,0.000023271483],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9959941,0.00028786992,0.00066323916,0.0017674403,0.0004278319,0.00085952313],"domain_scores_gemma":[0.9956629,0.000019424384,0.00058396836,0.0027278254,0.00064468285,0.00036114207],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00059709355,0.0007883877,0.00069471396,0.00013413429,0.00024424226,0.00015717352,0.00093878765,0.0015371154,0.000071724266],"category_scores_gemma":[0.0001056471,0.00092237873,0.00045452913,0.00044552327,0.00023730112,0.000008353769,0.0012882412,0.00055757543,0.00015044358],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012264756,0.00014921749,0.066887744,0.000100501115,0.001830382,0.000026470558,0.0000026037428,0.010931746,0.90638304,0.00017132005,0.013389626,0.0000046902305],"study_design_scores_gemma":[0.0015122163,0.0003291049,0.3951068,0.0004907538,0.001863611,7.0946484e-8,0.0000050395884,0.031745438,0.5321853,0.000083577084,0.032194875,0.004483186],"about_ca_topic_score_codex":0.000102921374,"about_ca_topic_score_gemma":0.000058615326,"teacher_disagreement_score":0.37419772,"about_ca_system_score_codex":0.00041442545,"about_ca_system_score_gemma":0.0006568124,"threshold_uncertainty_score":0.9997591},"labels":[],"label_agreement":null},{"id":"W2615110909","doi":"10.1109/tcbb.2017.2705143","title":"MGT-SM: A Method for Constructing Cellular Signal Transduction Networks","year":2017,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Computational Biology and Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"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 Saskatchewan","funders":"Central South University; National Natural Science Foundation of China","keywords":"Granger causality; Inference; Multivariate statistics; Statistical hypothesis testing; Bivariate analysis; Computer science; Artificial intelligence; Algorithm; Data mining; Mathematics; Machine learning; Statistics","score_opus":0.016372546606702097,"score_gpt":0.2880722316815223,"score_spread":0.2716996850748202,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2615110909","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":[0.05053613,0.0001262022,0.9482531,0.00027898,0.0003755645,0.0002560264,0.00008196677,0.000022653092,0.00006940105],"genre_scores_gemma":[0.72505367,0.00006224307,0.27412266,0.00017873658,0.00023269179,0.00003146542,0.00022275822,0.000013060263,0.00008273697],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989321,0.000059426133,0.00038407664,0.00028391668,0.00008507753,0.00025538597],"domain_scores_gemma":[0.9990164,0.00012301275,0.00025406695,0.00036576792,0.00014950433,0.00009126716],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035419132,0.00021175247,0.00023451232,0.00009166904,0.00092265866,0.00007318715,0.00024891013,0.00029411563,0.000025549758],"category_scores_gemma":[0.00002401491,0.00020060087,0.00018737788,0.000055846263,0.0002622066,0.000019850933,0.000010280018,0.00014806484,0.0000025392465],"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":[0.00040677618,0.00013699457,0.00083343935,0.00009056905,0.0009407693,0.000001105473,0.0001738069,0.6326753,0.024795784,0.0005503,0.00036301083,0.33903217],"study_design_scores_gemma":[0.001965169,0.00072952034,0.00037244102,0.00003263006,0.00032322283,0.00010835163,0.00027758384,0.9390014,0.048338365,0.0043243687,0.003936144,0.0005907944],"about_ca_topic_score_codex":0.000005748304,"about_ca_topic_score_gemma":0.000013675346,"teacher_disagreement_score":0.6745175,"about_ca_system_score_codex":0.000013833235,"about_ca_system_score_gemma":0.0000627293,"threshold_uncertainty_score":0.8180266},"labels":[],"label_agreement":null},{"id":"W2615815819","doi":"10.1007/s11538-017-0283-4","title":"Stability of Control Networks in Autonomous Homeostatic Regulation of Stem Cell Lineages","year":2017,"lang":"en","type":"article","venue":"Bulletin of Mathematical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"National Cancer Institute; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Stem cell; Control (management); Biology; Homeostasis; Stability (learning theory); Cell biology; Computer science; Artificial intelligence","score_opus":0.01061827700159802,"score_gpt":0.2362359483604191,"score_spread":0.2256176713588211,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2615815819","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":[0.98689,0.0006392526,0.011260418,0.00019315172,0.000032312604,0.00023822408,0.000018126286,0.0000033768044,0.00072510086],"genre_scores_gemma":[0.99792564,0.000052774176,0.0018482446,0.00001367337,0.000034191868,0.000010971708,0.000018761812,0.000011381674,0.00008437861],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985487,0.0002028436,0.00072202587,0.00025689305,0.00007854354,0.00019099856],"domain_scores_gemma":[0.99820185,0.00015708758,0.0006926087,0.00077630446,0.00012845355,0.000043681674],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074582745,0.00013626911,0.0005831817,0.000042297528,0.000029693172,0.000003870782,0.00032047782,0.00024304597,0.00016381525],"category_scores_gemma":[0.000161115,0.00011835392,0.00016006888,0.000034211767,0.00046415048,0.0000010432441,0.00012078526,0.00006694111,0.0000033594088],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00077898445,0.0014377547,0.11470914,0.0013890842,0.00041887577,0.0000022292136,0.00018193027,0.00687682,0.8591403,0.0047894623,0.00075915834,0.009516309],"study_design_scores_gemma":[0.0048705735,0.0018253837,0.10703055,0.0002252345,0.0003412777,0.000007969324,0.00024119689,0.02110455,0.8558272,0.005523126,0.0023586042,0.00064433395],"about_ca_topic_score_codex":0.0000206769,"about_ca_topic_score_gemma":0.000009783951,"teacher_disagreement_score":0.01422773,"about_ca_system_score_codex":0.000008819347,"about_ca_system_score_gemma":0.00003494132,"threshold_uncertainty_score":0.4826333},"labels":[],"label_agreement":null},{"id":"W2617921759","doi":"10.1007/s11538-017-0356-4","title":"A Multi-stage Representation of Cell Proliferation as a Markov Process","year":2017,"lang":"en","type":"article","venue":"Bulletin of Mathematical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":104,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University Health Centre","funders":"National Centre for the Replacement, Refinement and Reduction of Animals in Research; University of Bath; London Mathematical Society; Medical Research Scotland","keywords":"Markov chain; Exponential growth; Process (computing); Exponential function; Markov process; Computer science; Representation (politics); Algorithm; Variance (accounting); Cell cycle; Exponential distribution; Biological system; Applied mathematics; Mathematics; Biology; Cell; Statistics; Machine learning","score_opus":0.023624746668218642,"score_gpt":0.31725087438763844,"score_spread":0.2936261277194198,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2617921759","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":[0.9897597,0.00010449253,0.0055963797,0.00032526968,0.000027760412,0.00026263195,0.000010315607,0.000005714737,0.0039077587],"genre_scores_gemma":[0.9861812,0.000032424938,0.011280874,0.00003460703,0.00005532701,0.000031461976,0.000042289612,0.000012453132,0.00232939],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99902654,0.00009244645,0.0003673198,0.00027451603,0.00009157431,0.00014761827],"domain_scores_gemma":[0.99868125,0.000029189783,0.00045367898,0.00062725134,0.00016150296,0.000047108126],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027066364,0.000115123665,0.00028748412,0.00003444581,0.00006928481,0.000009924435,0.00029615487,0.0001821101,0.00032600865],"category_scores_gemma":[0.00062820374,0.000098626246,0.00012495789,0.000028892413,0.00024514625,0.0000012950983,0.00012220372,0.000046502424,0.00003084429],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018168174,0.00042204693,0.008854375,0.00037042447,0.00012064849,0.0000015397117,0.00010175311,0.00006637128,0.98745555,0.0007409396,0.0007772944,0.0009073757],"study_design_scores_gemma":[0.00077945896,0.00032151278,0.001560674,0.000028989532,0.00006414847,0.0000064876454,0.00010429777,0.0008497632,0.99303466,0.0012551416,0.0018425885,0.00015225605],"about_ca_topic_score_codex":0.000014345992,"about_ca_topic_score_gemma":0.0000043579425,"teacher_disagreement_score":0.0072937016,"about_ca_system_score_codex":0.0000036431693,"about_ca_system_score_gemma":0.00003655883,"threshold_uncertainty_score":0.40218616},"labels":[],"label_agreement":null},{"id":"W2618386243","doi":"10.1101/142893","title":"Optogenetic single-cell control of transcription achieves mRNA tunability and reduced variability","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"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":"Université de Montréal; Eidgenössische Technische Hochschule Zürich","keywords":"Optogenetics; Population; Cell; Computer science; Biology; Transcription (linguistics); Messenger RNA; Cell biology; Biological system; Neuroscience; Gene; Genetics","score_opus":0.010971606585926842,"score_gpt":0.2109966752286553,"score_spread":0.20002506864272848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2618386243","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":[0.9900558,0.0034913933,0.004974738,0.00009183951,0.00039648297,0.00070633966,0.00022499124,0.000044917822,0.000013497185],"genre_scores_gemma":[0.99673474,0.0003765405,0.0023153492,0.00003223432,0.0003569423,0.00008569574,0.000002265579,0.00008796626,0.000008281509],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9965978,0.0004884712,0.0007209038,0.0014309399,0.00030345056,0.0004584293],"domain_scores_gemma":[0.99569196,0.00003294917,0.00076652184,0.0026883378,0.0005497543,0.00027050613],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0011753963,0.00059001683,0.0008292199,0.000112875285,0.00018221317,0.000113667054,0.0006541374,0.00088381115,0.000014473172],"category_scores_gemma":[0.000318652,0.0006477635,0.00036647706,0.00011432153,0.00047091217,0.000010524032,0.00035738666,0.00036745047,0.0000026717282],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001243632,0.00027261136,0.022561314,0.00048798314,0.00029568953,0.0000020494574,0.000004247542,0.00037486156,0.97582686,0.0000139255235,0.000028307817,0.000007814316],"study_design_scores_gemma":[0.0007988406,0.00015422497,0.14708622,0.0000862585,0.00051048154,2.1756748e-8,0.0000011640632,0.00043193952,0.8497454,0.0000075156045,0.0006154774,0.00056246255],"about_ca_topic_score_codex":0.000030228024,"about_ca_topic_score_gemma":0.000004419276,"teacher_disagreement_score":0.12608144,"about_ca_system_score_codex":0.00008715436,"about_ca_system_score_gemma":0.0003645544,"threshold_uncertainty_score":0.9995974},"labels":[],"label_agreement":null},{"id":"W2620653540","doi":"10.1109/tnb.2017.2705106","title":"Biomolecular Network Controllability With Drug Binding Information","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on NanoBioscience","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Controllability; Biological network; Identification (biology); Computational biology; Biomolecule; Computer science; Drug discovery; Complex network; Biology; Nanotechnology; Bioinformatics; Mathematics; Materials science","score_opus":0.005929610558803339,"score_gpt":0.22289530003023786,"score_spread":0.21696568947143452,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2620653540","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":[0.64141303,0.000028281287,0.35745996,0.00020429118,0.0003221451,0.0001973356,0.000016373107,0.00002077619,0.0003377715],"genre_scores_gemma":[0.9983335,0.00003015185,0.0010032775,0.00015577346,0.00005452383,0.000025557294,0.00000624935,0.000009248577,0.00038169924],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99886423,0.00004947693,0.00019138948,0.00033276752,0.0002412965,0.00032085212],"domain_scores_gemma":[0.9986627,0.000009715521,0.00017992152,0.00092752633,0.000112224545,0.00010789491],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034737945,0.0001637388,0.00014548587,0.00006475356,0.0011017319,0.00018176534,0.00046176152,0.000080266225,0.000012509401],"category_scores_gemma":[0.000013312758,0.0001376643,0.00011054487,0.00020042421,0.00034993596,0.00004550644,0.0000051860306,0.00007997185,0.000029121542],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038046966,0.00016312832,0.003400506,0.000023477878,0.00018695222,0.0000048803095,0.00009434503,0.10987728,0.86802244,0.0000496772,0.00092190196,0.016874934],"study_design_scores_gemma":[0.0013617905,0.00039592173,0.0040790956,0.000044420874,0.00011398168,0.000022495333,0.00006585699,0.004304509,0.97997427,0.000031378182,0.009067153,0.00053912174],"about_ca_topic_score_codex":0.000033781515,"about_ca_topic_score_gemma":0.000119199205,"teacher_disagreement_score":0.35692048,"about_ca_system_score_codex":0.000030401148,"about_ca_system_score_gemma":0.00010737695,"threshold_uncertainty_score":0.8473742},"labels":[],"label_agreement":null},{"id":"W2624136113","doi":"10.1088/1742-5468/aa6de6","title":"Constrained target controllability of complex networks","year":2017,"lang":"en","type":"article","venue":"Journal of Statistical Mechanics Theory and Experiment","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":35,"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 Saskatchewan","funders":"China Postdoctoral Science Foundation; Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Controllability; Complex network; Computer science; Control theory (sociology); Artificial intelligence; Mathematics; Control (management); Applied mathematics; World Wide Web","score_opus":0.011389761980960394,"score_gpt":0.28398971248248817,"score_spread":0.27259995050152774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2624136113","genre_codex":"methods","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":[0.18330626,0.0013539038,0.81480473,0.00006981173,0.00016544205,0.00008962295,0.000030049883,0.000001421822,0.0001787329],"genre_scores_gemma":[0.9871747,0.00012130996,0.012478308,0.000050556842,0.00014074423,0.0000017013431,0.0000075634807,0.000008341715,0.000016814434],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99893427,0.0002137634,0.0004210728,0.00014043498,0.00014129748,0.00014917788],"domain_scores_gemma":[0.9988299,0.00009013785,0.00047090428,0.00029926613,0.00016867966,0.0001410899],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001206123,0.000115339695,0.0003469146,0.000021142685,0.00012912847,0.000027072821,0.00019548943,0.000083980565,0.00011057282],"category_scores_gemma":[0.00033598873,0.000093450304,0.00010071704,0.000013676756,0.00021643395,0.000004634843,0.00009922412,0.00008109093,2.680886e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020197127,0.00021904316,0.00025444647,0.000024968616,0.00059594854,0.000017154462,0.00006281337,0.0009085144,0.51912194,0.4712598,0.0004489569,0.0050667035],"study_design_scores_gemma":[0.008336792,0.0056819087,0.0039794003,0.000119506796,0.0007496109,0.00024849823,0.0012666888,0.040273882,0.5005308,0.43172884,0.0061953324,0.0008887652],"about_ca_topic_score_codex":0.0000012229374,"about_ca_topic_score_gemma":7.115523e-7,"teacher_disagreement_score":0.8038684,"about_ca_system_score_codex":0.000010040955,"about_ca_system_score_gemma":0.000044792727,"threshold_uncertainty_score":0.3810793},"labels":[],"label_agreement":null},{"id":"W2626941634","doi":"","title":"iGEM Team meetings: settings for conversations on teaching & learning","year":2017,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Pedagogy; Engineering ethics; Psychology; Medical education; Engineering; Medicine","score_opus":0.009547421541300232,"score_gpt":0.2697131996314424,"score_spread":0.2601657780901422,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2626941634","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":[0.93492573,0.00006312905,0.008080679,0.0013604312,0.00013465746,0.00024599515,0.0000053557774,0.000043270597,0.05514076],"genre_scores_gemma":[0.9843827,0.000009263416,0.0026927763,0.00032317947,0.00035708732,0.0000211267,0.000067187495,0.000021692755,0.012125012],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992417,0.00004062301,0.00012809155,0.0003031766,0.000083770006,0.00020264223],"domain_scores_gemma":[0.9992409,0.000023034885,0.00016102345,0.0004586659,0.000059536527,0.00005685006],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004213313,0.000113380775,0.000111757894,0.00002848875,0.0009391693,0.00008938161,0.0002361832,0.00009337498,0.000026191332],"category_scores_gemma":[0.00048281578,0.00010730754,0.00014275678,0.000011379598,0.000048110287,0.0000035744317,0.000091888454,0.00009698438,0.000018757932],"study_design_candidate":"not_applicable","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":[0.00015946281,0.00016051022,0.09851083,0.00006544003,0.0008047464,0.0000015768243,0.00047667086,0.012664574,0.6597915,0.0038457818,0.19163935,0.031879503],"study_design_scores_gemma":[0.001149127,0.00048300187,0.0067237,0.000040836378,0.00016023013,0.000004559866,0.00097559,0.010039151,0.17721075,0.00020658564,0.80245745,0.00054899615],"about_ca_topic_score_codex":0.000018592633,"about_ca_topic_score_gemma":0.000023107117,"teacher_disagreement_score":0.61081815,"about_ca_system_score_codex":0.000009840473,"about_ca_system_score_gemma":0.000024604191,"threshold_uncertainty_score":0.7223426},"labels":[],"label_agreement":null},{"id":"W2725073084","doi":"10.3791/55879","title":"ODELAY: A Large-scale Method for Multi-parameter Quantification of Yeast Growth","year":2017,"lang":"en","type":"article","venue":"Journal of Visualized Experiments","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"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":"National Center for Research Resources; National Institute of General Medical Sciences; Canadian Institutes of Health Research; Health Canada; National Institutes of Health; Université du Luxembourg","keywords":"Yeast; Biology; Biological system; Population; Genetics","score_opus":0.05421681646818225,"score_gpt":0.45198594639722783,"score_spread":0.39776912992904556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2725073084","genre_codex":"methods","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":[0.4550996,0.0006280273,0.5439071,0.000034517994,0.00017180595,0.00012102471,0.000013643478,0.0000015950225,0.00002267667],"genre_scores_gemma":[0.79320157,0.000068593494,0.20629422,0.000035531128,0.00015759263,0.000010706334,0.000016164136,0.000021238968,0.00019439745],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99885654,0.00010094449,0.0004948522,0.00018644893,0.00018671984,0.00017450063],"domain_scores_gemma":[0.99803615,0.000011402891,0.0010561326,0.0004265501,0.00038400266,0.000085770684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006386649,0.00012756258,0.00033078267,0.00007335491,0.00012729857,0.00003685833,0.00035577084,0.00011773881,0.000013086955],"category_scores_gemma":[0.0001774327,0.0001118791,0.0003631693,0.000033647775,0.000046989786,0.000012642891,0.00007769588,0.00004929204,0.0000013266886],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035141673,0.0003160224,0.0017480382,0.000016581296,0.00036304793,7.3805546e-7,0.00018686564,0.0000583307,0.9956847,0.000040770403,0.0007473656,0.00048613714],"study_design_scores_gemma":[0.0025846073,0.0002656329,0.002046983,0.000025075553,0.00012544479,0.00001034826,0.00015966615,0.010642259,0.9817243,0.00005316134,0.0022406918,0.00012178346],"about_ca_topic_score_codex":0.000008333945,"about_ca_topic_score_gemma":0.000004273354,"teacher_disagreement_score":0.33810192,"about_ca_system_score_codex":0.000015861384,"about_ca_system_score_gemma":0.00005069339,"threshold_uncertainty_score":0.45622972},"labels":[],"label_agreement":null},{"id":"W2726469502","doi":"10.46298/dmtcs.3410","title":"Infinite limits and folding","year":2005,"lang":"en","type":"article","venue":"Discrete Mathematics & Theoretical Computer Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Statistics Canada; Dalhousie University; Wilfrid Laurier University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Mathematics; Induced subgraph isomorphism problem; Isomorphism (crystallography); Combinatorics; Homomorphism; Vertex (graph theory); Induced subgraph; Discrete mathematics; Subgraph isomorphism problem; Graph isomorphism; Graph; Line graph; Voltage graph","score_opus":0.009301348971610265,"score_gpt":0.2479846557950595,"score_spread":0.23868330682344924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2726469502","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":[0.7039127,0.00015785095,0.29320914,0.000383118,0.000052642754,0.00009728066,0.0000016491754,0.0000218428,0.002163804],"genre_scores_gemma":[0.8824815,0.000028917755,0.116989024,0.00022690618,0.00022653364,0.000003968135,0.0000032377873,0.000013297858,0.000026606687],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986325,0.000032880005,0.00023370924,0.00044365946,0.0002992319,0.00035802808],"domain_scores_gemma":[0.9991249,0.000039363655,0.00006628599,0.00048624448,0.00008539004,0.0001978375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006713489,0.00016562708,0.0001717654,0.0000761283,0.0002192876,0.00014686114,0.00043981534,0.00006447669,0.000026183965],"category_scores_gemma":[0.000075283344,0.00013628021,0.000072772666,0.0002721602,0.0013144948,0.000012488732,0.00042006545,0.00007346001,0.000013682281],"study_design_candidate":"simulation_or_modeling","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":[0.000014341203,0.00009805736,0.00055364985,0.000045479726,0.000067269386,0.0000030947826,0.00070194056,0.001283336,0.15295704,0.8253902,0.00026742744,0.018618144],"study_design_scores_gemma":[0.00047147018,0.0003170546,0.00082994363,0.00007822592,0.000096617354,0.000099741206,0.000092006936,0.8662817,0.0899379,0.03801646,0.0030515927,0.00072732475],"about_ca_topic_score_codex":1.9414286e-7,"about_ca_topic_score_gemma":0.0000010426644,"teacher_disagreement_score":0.86499834,"about_ca_system_score_codex":0.000010135468,"about_ca_system_score_gemma":0.00003492984,"threshold_uncertainty_score":0.5557346},"labels":[],"label_agreement":null},{"id":"W2730785852","doi":"10.1371/journal.pone.0180179","title":"Formal reasoning about systems biology using theorem proving","year":2017,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Automated theorem proving; Mathematical proof; Computer science; HOL; Systems biology; Abstraction; Formal methods; Theoretical computer science; Modelling biological systems; Biological network; Artificial intelligence; Computational biology; Programming language; Biology; Mathematics","score_opus":0.030746957982701755,"score_gpt":0.2511486317638904,"score_spread":0.22040167378118866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2730785852","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":[0.9943398,0.0016965441,0.0019448772,0.00002272211,0.00007318678,0.00016013098,0.00000605948,0.000016189386,0.0017404617],"genre_scores_gemma":[0.99630857,0.00008027297,0.002381991,0.000021622609,0.0006880603,0.000014284184,0.00003577033,0.00002723567,0.00044218876],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99896365,0.00006613564,0.00018797544,0.0003149197,0.00011041699,0.00035691864],"domain_scores_gemma":[0.99876374,0.0000056045683,0.00024417875,0.00081212807,0.000099500256,0.00007484213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031577976,0.0001410698,0.00023315665,0.000035195393,0.0004789234,0.00010008922,0.00034976625,0.0001643534,0.000008254901],"category_scores_gemma":[0.00013854537,0.00013364076,0.00008513369,0.00002836398,0.00011308789,0.0000092967475,0.00026364464,0.00007577278,0.000007811213],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026455575,0.0000981585,0.056088254,0.00005473793,0.00052565965,0.0000021893907,0.000019540745,0.00036012236,0.9413939,0.00082634366,0.00002204763,0.0005826013],"study_design_scores_gemma":[0.0013867203,0.00043808133,0.016752694,0.00069376995,0.0011162515,0.000038352304,0.00017269977,0.111171834,0.864929,0.00028073875,0.0018555744,0.0011642644],"about_ca_topic_score_codex":0.00005815219,"about_ca_topic_score_gemma":0.00001893373,"teacher_disagreement_score":0.11081172,"about_ca_system_score_codex":0.000020065976,"about_ca_system_score_gemma":0.00005214477,"threshold_uncertainty_score":0.54497117},"labels":[],"label_agreement":null},{"id":"W2734032589","doi":"10.1007/s11192-017-2452-5","title":"Tracking the emergence of synthetic biology","year":2017,"lang":"en","type":"article","venue":"Scientometrics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":109,"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":"Office of Naval Research; Office of Defense Programs; National Key Research and Development Program of China; Biotechnology and Biological Sciences Research Council; Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; Defense Advanced Research Projects Agency; Directorate for Biological Sciences; National Institutes of Health; Bundesministerium für Bildung und Forschung; Russian Foundation for Basic Research; National Natural Science Foundation of China; Deutsche Forschungsgemeinschaft; Wellcome Trust; Council of Scientific and Industrial Research, India; U.S. Department of Energy; U.S. Department of Defense; European Commission; Canadian Institutes of Health Research; National Science Foundation; American Heart Association; Ministry of Education, Culture, Sports, Science and Technology; Howard Hughes Medical Institute","keywords":"Synthetic biology; Systems biology; Domain (mathematical analysis); Computer science; Set (abstract data type); Benchmark (surveying); Multidisciplinary approach; Data science; Biology; Computational biology; Mathematics; Political science","score_opus":0.03642355739386737,"score_gpt":0.32851887235283084,"score_spread":0.29209531495896346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2734032589","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":[0.9926937,0.001580049,0.003008665,0.00020196103,0.0004005225,0.00006538563,0.000005616296,0.0000035259595,0.0020405382],"genre_scores_gemma":[0.99905026,0.00021031068,0.00024257302,0.000025500996,0.000096018004,0.0000027480062,0.0000045894076,0.000006416781,0.0003615691],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99917406,0.000041450556,0.00015293462,0.00024515597,0.00018598865,0.00020039604],"domain_scores_gemma":[0.9985289,0.000017921808,0.00020958147,0.0010231213,0.00017115926,0.00004929112],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008364201,0.00007407833,0.00010350511,0.00023904628,0.00031562004,0.000040506096,0.00088702573,0.00006813406,0.000034224846],"category_scores_gemma":[0.0010275554,0.00005166066,0.000108754604,0.00084111426,0.0003761695,0.0000029825565,0.00025226857,0.000042879536,0.0000072005187],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012692345,0.000075900345,0.33604503,0.000017022643,0.00013801683,9.535326e-7,0.00008753241,0.0008272759,0.5895551,0.001276123,0.0024422598,0.06952211],"study_design_scores_gemma":[0.00038392143,0.00024559948,0.3406213,0.000015592856,0.00013380843,0.000010517568,0.0001679736,0.0018110318,0.6046208,0.0009085478,0.050694484,0.0003864427],"about_ca_topic_score_codex":0.000012634854,"about_ca_topic_score_gemma":0.000014020991,"teacher_disagreement_score":0.06913567,"about_ca_system_score_codex":0.000003892438,"about_ca_system_score_gemma":0.000035724475,"threshold_uncertainty_score":0.2427526},"labels":[],"label_agreement":null},{"id":"W2736359841","doi":"10.1016/j.bpj.2017.08.036","title":"Untangling the Hairball: Fitness-Based Asymptotic Reduction of Biological Networks","year":2017,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Algorithm; Computer science; Artificial intelligence; Machine learning; Function (biology); Biology","score_opus":0.017705952622037266,"score_gpt":0.2630219730555037,"score_spread":0.2453160204334664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2736359841","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":[0.98993874,0.00020533326,0.008879469,0.0004559311,0.00034599268,0.00006271895,0.0000018924302,0.000005533594,0.000104384344],"genre_scores_gemma":[0.9975817,0.0000922894,0.00025188376,0.000047797752,0.0019413616,0.0000030495767,0.000011047519,0.000013006095,0.00005784505],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999031,0.00011064707,0.0002489436,0.00020889341,0.00016836867,0.00023213231],"domain_scores_gemma":[0.99882096,0.000014837618,0.00038019635,0.0005576514,0.00013371688,0.000092651164],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000294351,0.00013865563,0.00019296267,0.000022736873,0.0005329254,0.00008483165,0.000528905,0.00014242997,0.000015478388],"category_scores_gemma":[0.0000778627,0.00008735112,0.00031725725,0.000060062666,0.000378972,0.000005414454,0.000106839885,0.00019041143,0.0000031637778],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013915234,0.0001211837,0.0055209775,0.0000046800833,0.00019440458,0.0000066549665,0.000008517049,0.030005284,0.9581693,0.00018171454,0.00065850146,0.004989632],"study_design_scores_gemma":[0.0022071963,0.0014013994,0.1431678,0.00012296265,0.0004586568,0.00028899833,0.00015791757,0.08012506,0.76478297,0.0005904325,0.005839376,0.00085725466],"about_ca_topic_score_codex":0.000004810645,"about_ca_topic_score_gemma":0.0000020614486,"teacher_disagreement_score":0.19338635,"about_ca_system_score_codex":0.000016152911,"about_ca_system_score_gemma":0.000057893696,"threshold_uncertainty_score":0.40988854},"labels":[],"label_agreement":null},{"id":"W2738432244","doi":"10.1109/icnf.2017.7985933","title":"Stochastic dynamics of gene expression in developing fly embryos","year":2017,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"British Columbia Institute of Technology","funders":"","keywords":"Gene; Transcription (linguistics); Gene expression; Biology; Messenger RNA; Cis-regulatory module; Transcription factor; Genetics; Cell biology; Promoter","score_opus":0.010713163935664651,"score_gpt":0.251600442037323,"score_spread":0.24088727810165836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2738432244","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":[0.8780258,0.00015458108,0.12099434,0.000096596654,0.000054430613,0.0000657584,0.0000024031594,0.0000033826204,0.0006026514],"genre_scores_gemma":[0.9899292,0.00002599913,0.0093317665,0.000026630361,0.000053318894,0.0000054261477,0.000038402108,0.000011274074,0.0005779639],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99935263,0.000020988511,0.00018093988,0.00021343942,0.00008497308,0.00014700225],"domain_scores_gemma":[0.99921733,0.0000038987837,0.00012930829,0.0005646843,0.000050971055,0.000033820215],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011909006,0.00009167038,0.00013985905,0.000042826985,0.00007736072,0.000014292089,0.00027557768,0.00009977258,0.000012354248],"category_scores_gemma":[0.000050427738,0.0000847318,0.000059433358,0.00003355415,0.00005277336,0.000002652929,0.0001507195,0.00003339046,0.000002401862],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033036777,0.000029201034,0.016958363,0.0000174604,0.000044239136,0.000002356472,0.000019097877,0.007882941,0.9721831,0.00021546039,0.00019630794,0.0024184512],"study_design_scores_gemma":[0.0005799085,0.00005159168,0.052685134,0.000052653282,0.000023145589,0.000005205222,0.000067333356,0.016297253,0.9295547,0.00021152185,0.00019678834,0.00027478242],"about_ca_topic_score_codex":0.000024158817,"about_ca_topic_score_gemma":0.00045876426,"teacher_disagreement_score":0.11190336,"about_ca_system_score_codex":0.000018925544,"about_ca_system_score_gemma":0.000057654393,"threshold_uncertainty_score":0.34552628},"labels":[],"label_agreement":null},{"id":"W2739241668","doi":"10.1016/j.artmed.2017.06.007","title":"Employing decomposable partially observable Markov decision processes to control gene regulatory networks","year":2017,"lang":"en","type":"article","venue":"Artificial Intelligence in Medicine","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Observability; Partially observable Markov decision process; Computer science; Gene regulatory network; Probabilistic logic; Markov chain; Markov model; Artificial intelligence; Mathematical optimization; Machine learning; Mathematics; Gene; Biology","score_opus":0.03558361627813448,"score_gpt":0.3235021851016336,"score_spread":0.2879185688234991,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2739241668","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":[0.74683934,0.0015200264,0.24952796,0.000976614,0.00050621195,0.00037977583,0.0000023992352,0.000020768162,0.00022690526],"genre_scores_gemma":[0.9938644,0.00036267485,0.0035759443,0.0006808277,0.0012221939,0.000059993497,0.000026299298,0.000040844076,0.00016680198],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9974634,0.00009080744,0.0007621259,0.0007250449,0.0003569895,0.00060159917],"domain_scores_gemma":[0.9977781,0.00010182856,0.00026084037,0.0012871833,0.00030567337,0.00026638462],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0012412808,0.00028912185,0.00047472384,0.00012951583,0.00042954675,0.000093215654,0.0008692367,0.00021275849,0.0001024598],"category_scores_gemma":[0.0015104011,0.0002634628,0.00008820377,0.0003021966,0.00027138376,0.000020732441,0.00021413228,0.00015999044,0.000037123897],"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":[0.0012434903,0.0002223025,0.05590541,0.000046293804,0.00017316136,0.000075312026,0.00024445957,0.37861055,0.27874663,0.0003123739,0.004375239,0.2800448],"study_design_scores_gemma":[0.0009348143,0.001623437,0.055799212,0.001092388,0.00032065003,0.00004330215,0.00066630886,0.15078518,0.76730317,0.009379319,0.010325336,0.0017268996],"about_ca_topic_score_codex":0.00021762168,"about_ca_topic_score_gemma":0.0036886563,"teacher_disagreement_score":0.48855653,"about_ca_system_score_codex":0.00004291049,"about_ca_system_score_gemma":0.00012508011,"threshold_uncertainty_score":0.99998176},"labels":[],"label_agreement":null},{"id":"W2739335964","doi":"10.1016/j.cels.2017.06.013","title":"Incoherent Inputs Enhance the Robustness of Biological Oscillators","year":2017,"lang":"en","type":"article","venue":"Cell Systems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":47,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"National Institute of General Medical Sciences; National Institutes of Health; National Science Foundation","keywords":"Robustness (evolution); Computer science; Biological system; Biology; Genetics","score_opus":0.016061821564896293,"score_gpt":0.24977733606725536,"score_spread":0.23371551450235906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2739335964","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":[0.9943785,0.0022047667,0.0012107024,0.000043807664,0.0005153094,0.00017394964,0.0000038629237,0.0000053654576,0.0014637149],"genre_scores_gemma":[0.9982442,0.00012561561,0.000025032745,0.00001010618,0.00044472888,0.000020557358,0.000010717173,0.000010665223,0.0011083628],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99910223,0.000107433196,0.00023192547,0.0002624265,0.00012146759,0.00017452585],"domain_scores_gemma":[0.9985002,0.000009799972,0.00032269006,0.0010346272,0.00008099431,0.000051675466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030739783,0.00012287617,0.00020109942,0.000014551056,0.00020989099,0.00004142525,0.00057353196,0.00014797377,0.000007496421],"category_scores_gemma":[0.000034099307,0.00007697428,0.000121547964,0.000037599963,0.00018805143,0.000001819759,0.0002108619,0.000051174004,0.000007687035],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000437148,0.00009691556,0.06619094,0.000117720745,0.00021323649,0.00000249995,0.000051084608,0.031236244,0.89470375,0.000064277134,0.0060578124,0.0012218262],"study_design_scores_gemma":[0.00048741407,0.00024822715,0.021057563,0.00006489757,0.00008255681,0.00001267931,0.00017189725,0.0037384615,0.89666486,0.0000115996045,0.07699804,0.00046180052],"about_ca_topic_score_codex":0.00003798057,"about_ca_topic_score_gemma":0.000020788399,"teacher_disagreement_score":0.070940234,"about_ca_system_score_codex":0.00000949203,"about_ca_system_score_gemma":0.000031512747,"threshold_uncertainty_score":0.31389198},"labels":[],"label_agreement":null},{"id":"W2747130326","doi":"10.1007/978-3-319-66799-7_13","title":"Simplifying Analyses of Chemical Reaction Networks for Approximate Majority","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Correctness; Mathematical proof; Binary logarithm; Simple (philosophy); Computer science; Population; Context (archaeology); Protocol (science); Discrete mathematics; Theoretical computer science; Distributed algorithm; Combinatorics; Algorithm; Mathematics; Distributed computing","score_opus":0.02891216986072359,"score_gpt":0.2989851397757355,"score_spread":0.2700729699150119,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2747130326","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":[0.005489798,0.00088734255,0.99273914,0.000028179007,0.00030833264,0.00022388175,0.000007777834,0.000009427593,0.00030612393],"genre_scores_gemma":[0.9604585,0.000092508024,0.038032897,0.00007893173,0.00105402,0.000009072399,0.00009751607,0.000031956955,0.0001445822],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9982942,0.00001269805,0.00032784848,0.0007999654,0.00024607996,0.00031920717],"domain_scores_gemma":[0.9982843,0.00005083401,0.00042315706,0.000954609,0.00021413412,0.00007295792],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00043767624,0.00028004014,0.000425533,0.00015449533,0.00012418295,0.000057760666,0.00074529665,0.0004209803,0.0000024269918],"category_scores_gemma":[0.00008079314,0.000264398,0.00025357047,0.00006907538,0.0004802526,0.000007769032,0.00035769862,0.0002044274,4.3940094e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009129609,0.000038355844,0.00028153567,0.00013950179,0.00021265326,0.000004300872,0.000029281424,0.17235795,0.5710273,0.0001791531,0.000067844674,0.25557086],"study_design_scores_gemma":[0.00046681127,0.00019542764,0.00012620809,0.0002229427,0.00021359304,0.000024942448,1.5288525e-7,0.49092394,0.49349782,0.011842828,0.001708341,0.000776974],"about_ca_topic_score_codex":0.000010893272,"about_ca_topic_score_gemma":0.00002233969,"teacher_disagreement_score":0.9549687,"about_ca_system_score_codex":0.00004506051,"about_ca_system_score_gemma":0.00013592024,"threshold_uncertainty_score":0.9999808},"labels":[],"label_agreement":null},{"id":"W2750932767","doi":"10.1101/181537","title":"Functional effects of heating and cooling gene networks","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Laufer Center for Physical and Quantitative Biology, Stony Brook University; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; National Science Foundation","keywords":"Gene regulatory network; TetR; Gene expression; Gene; Regulation of gene expression; Negative feedback; Biology; Positive feedback; Electronic circuit; Function (biology); Biophysics; Repressor; Computational biology; Cell biology; Biological system; Genetics; Physics","score_opus":0.007866084191822758,"score_gpt":0.20464185276855354,"score_spread":0.1967757685767308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2750932767","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":[0.96960837,0.013807467,0.015430189,0.000019909055,0.000743298,0.0003247173,0.000024183348,0.00003848088,0.0000033702872],"genre_scores_gemma":[0.99446255,0.0012073215,0.0028168242,0.000053753905,0.0012875547,0.00006530988,0.000002519775,0.000094672105,0.000009500476],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99789387,0.00012044148,0.0004243351,0.0009133254,0.00023967198,0.00040838323],"domain_scores_gemma":[0.99738544,0.000035977017,0.0006195697,0.0013977733,0.00036135694,0.00019988192],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00044396782,0.00045111467,0.0005673441,0.000115341725,0.00024306039,0.00010205731,0.00037087486,0.0006746986,0.000005174753],"category_scores_gemma":[0.00021477164,0.0005065465,0.00022020204,0.00010523554,0.00019488974,0.000006566635,0.00080981856,0.00035562782,0.0000021488697],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045455337,0.00004456887,0.018670226,0.0003674356,0.0005574109,0.000011724723,0.0000014488716,0.010809699,0.96922183,0.000028051832,0.00023362196,0.000008514362],"study_design_scores_gemma":[0.0005443241,0.0000772606,0.15631506,0.000328507,0.0003793996,5.6130958e-8,6.175525e-7,0.0060971193,0.8350573,0.0000015184914,0.00056391995,0.0006349297],"about_ca_topic_score_codex":0.000026106345,"about_ca_topic_score_gemma":0.0000026346975,"teacher_disagreement_score":0.13764483,"about_ca_system_score_codex":0.000040126055,"about_ca_system_score_gemma":0.0002592634,"threshold_uncertainty_score":0.99973863},"labels":[],"label_agreement":null},{"id":"W2751738974","doi":"","title":"Optimal control for context-sensitive probabilistic Boolean networks with perturbation using probabilisitic model checking","year":2016,"lang":"en","type":"article","venue":"IEEE Conference Proceedings","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Calgary","funders":"","keywords":"Reachability; Probabilistic logic; Computer science; Model checking; Optimal control; Context (archaeology); Computation; Reachability problem; Theoretical computer science; Time horizon; Mathematical optimization; Algorithm; Artificial intelligence; Mathematics","score_opus":0.019684073826620727,"score_gpt":0.23441036028581286,"score_spread":0.21472628645919212,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2751738974","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":[0.53860116,0.000043831038,0.46055812,0.00009053253,0.000030506591,0.00058721023,0.0000102537415,0.000023185747,0.000055202996],"genre_scores_gemma":[0.99344254,0.00001339946,0.005553758,0.00013715679,0.0003045756,0.00016329176,0.000014855225,0.000055087003,0.00031531535],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982524,0.000022794464,0.00030833948,0.0007184759,0.00018857387,0.00050942047],"domain_scores_gemma":[0.99817055,0.00004133137,0.00023772687,0.00018851133,0.0012194568,0.00014241034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035921537,0.00032357706,0.00035096696,0.00005916239,0.00016768462,0.000090322384,0.00019418812,0.00021147625,0.000003496964],"category_scores_gemma":[0.00013771058,0.00023163942,0.00013337718,0.00011257421,0.00022991003,0.000028838693,0.00003383758,0.000081899794,0.0000011172489],"study_design_candidate":"simulation_or_modeling","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":[0.0012476024,0.00007431258,0.0021120838,0.00011886751,0.00033648015,0.0000012956035,0.0002686444,0.19883691,0.79261476,0.0022241925,0.00021330224,0.0019515274],"study_design_scores_gemma":[0.001851117,0.00041403197,0.00014893121,0.00025104044,0.00027684958,0.000027142705,0.00018411054,0.9452639,0.05046528,0.00056913926,0.000067917375,0.0004805326],"about_ca_topic_score_codex":0.00000310838,"about_ca_topic_score_gemma":0.000010440902,"teacher_disagreement_score":0.746427,"about_ca_system_score_codex":0.0000907021,"about_ca_system_score_gemma":0.00022945728,"threshold_uncertainty_score":0.94459814},"labels":[],"label_agreement":null},{"id":"W2754170863","doi":"10.1109/tcsii.2017.2751306","title":"M-Matrix-Based State Observer Design for Genetic Regulatory Networks With Mixed Delays","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Circuits & Systems II Express Briefs","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Observer (physics); State (computer science); Mathematical optimization; Set (abstract data type); Computer science; Control theory (sociology); Separation principle; Controller (irrigation); Linear matrix inequality; Matrix (chemical analysis); Linear programming; State observer; Mathematics; Control (management); Algorithm; Artificial intelligence; Nonlinear system","score_opus":0.022040341261262458,"score_gpt":0.24017081252808914,"score_spread":0.2181304712668267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2754170863","genre_codex":"methods","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":[0.2467798,0.0008850279,0.75044304,0.000026678823,0.00067204994,0.0010279466,0.00008697524,0.00005635198,0.000022145801],"genre_scores_gemma":[0.99437165,0.00006776963,0.0021168683,0.00006487947,0.0003615889,0.0007144964,0.000039166498,0.00015358756,0.0021100019],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9970759,0.00027010846,0.00057425885,0.0009829204,0.0003981647,0.000698653],"domain_scores_gemma":[0.9965829,0.000070063135,0.00049692806,0.0022287008,0.00033636656,0.0002850159],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.00045972905,0.0005150261,0.0005540031,0.00011905065,0.0014598678,0.00023178496,0.00074605155,0.0003624298,0.000010288428],"category_scores_gemma":[0.0000106913785,0.00049808563,0.0003771188,0.000117218355,0.00022760482,0.00002428437,0.0000073447954,0.00019220526,0.0000059139443],"study_design_candidate":"simulation_or_modeling","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":[0.00023556041,0.00013607541,0.0001821944,0.00008229534,0.0005010578,0.000009155011,0.00003474847,0.9480267,0.046587735,0.0000040927907,0.0014007512,0.0027996043],"study_design_scores_gemma":[0.011755689,0.0038534566,0.008820089,0.0008990141,0.0020217886,0.00017096818,0.000144917,0.37621185,0.5621668,0.000033917644,0.030156838,0.0037646852],"about_ca_topic_score_codex":0.0001048147,"about_ca_topic_score_gemma":0.00013770664,"teacher_disagreement_score":0.7483262,"about_ca_system_score_codex":0.00007778965,"about_ca_system_score_gemma":0.00027561752,"threshold_uncertainty_score":0.9998401},"labels":[],"label_agreement":null},{"id":"W2760631172","doi":"10.1016/j.spa.2018.09.009","title":"Large deviations of Markov chains with multiple time-scales","year":2018,"lang":"en","type":"article","venue":"Stochastic Processes and their Applications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Statistics Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Markov chain; Large deviations theory; Statistical physics; Limit (mathematics); Central limit theorem; Mathematics; Markov process; Applied mathematics; Scale (ratio); Standard deviation; Path (computing); Computer science; Statistics; Physics; Mathematical analysis","score_opus":0.0041409945756752655,"score_gpt":0.21292860537670677,"score_spread":0.2087876108010315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2760631172","genre_codex":"methods","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":[0.09227447,0.0010004553,0.906054,0.00006304647,0.000004317665,0.00024476313,0.00007831985,0.000013116041,0.00026746525],"genre_scores_gemma":[0.99853045,0.000025059268,0.0007340541,0.000033987148,0.00014828908,0.00017261853,0.00012669389,0.000015132778,0.00021371499],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99942553,0.000009397366,0.00012712477,0.000237313,0.00005593729,0.00014470241],"domain_scores_gemma":[0.99929667,0.000025129513,0.00009052954,0.0002665148,0.0002633007,0.000057848407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006426426,0.00011050609,0.000121428115,0.00003639158,0.00017010963,0.000009513103,0.000112528665,0.00005174267,0.000011631702],"category_scores_gemma":[0.00002806408,0.00008399985,0.000027941413,0.0002494727,0.000179635,0.000003040933,0.00005801038,0.000026251155,0.0000054202087],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00069217104,0.0023142148,0.01013058,0.0012081208,0.0028451046,5.168095e-7,0.003117784,0.0012283286,0.9174406,0.030000959,0.003537312,0.027484298],"study_design_scores_gemma":[0.012914793,0.006632851,0.02450232,0.0007453523,0.0023313537,0.0002473904,0.009823026,0.12430606,0.6509328,0.034358244,0.12671612,0.0064897235],"about_ca_topic_score_codex":0.0000024434648,"about_ca_topic_score_gemma":0.000178036,"teacher_disagreement_score":0.90625596,"about_ca_system_score_codex":0.0000033988526,"about_ca_system_score_gemma":0.00007005119,"threshold_uncertainty_score":0.34254143},"labels":[],"label_agreement":null},{"id":"W2762690992","doi":"10.1109/cibcb.2017.8058530","title":"A novel representation for boolean networks designed to enhance heritability and scalability","year":2017,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"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 Guelph","funders":"","keywords":"Boolean network; Representation (politics); Boolean function; Crossover; Computer science; Theoretical computer science; And-inverter graph; Scalability; Boolean expression; Logical matrix; Standard Boolean model; Matrix representation; Population; Artificial intelligence; Algorithm","score_opus":0.015877708776581435,"score_gpt":0.31062813083980234,"score_spread":0.2947504220632209,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2762690992","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":[0.63269824,0.000073596835,0.3664539,0.0002865916,0.000039089937,0.0002997908,0.000003273746,0.0000070653614,0.00013848217],"genre_scores_gemma":[0.9819628,0.000013572421,0.017061343,0.00013398544,0.00018036521,0.00007199201,0.000021556358,0.000012323979,0.00054203154],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99900573,0.000031035906,0.00017138897,0.00052872347,0.00006545399,0.00019764177],"domain_scores_gemma":[0.9987008,0.00002030616,0.00008380042,0.00095660426,0.000121856596,0.000116652016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039526302,0.00011288446,0.00014898073,0.000012254189,0.00027242114,0.00007518602,0.00019035187,0.000101654136,0.000007707506],"category_scores_gemma":[0.00032427406,0.000108532695,0.00008696534,0.00003300723,0.00009948441,0.0000056474205,0.00016254577,0.000027330716,8.7419704e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000277632,0.00008954036,0.06682094,0.000021527332,0.000092144684,1.5322738e-7,0.000026702075,0.0027427147,0.89854324,0.00005237851,0.0012541731,0.030078866],"study_design_scores_gemma":[0.00073469785,0.0003890607,0.41954648,0.000011473536,0.00009461793,0.000004215794,0.00007477681,0.018581979,0.55656815,0.0003026566,0.0032037492,0.00048815328],"about_ca_topic_score_codex":0.000061465216,"about_ca_topic_score_gemma":0.0004937736,"teacher_disagreement_score":0.35272554,"about_ca_system_score_codex":0.000011850375,"about_ca_system_score_gemma":0.000020476935,"threshold_uncertainty_score":0.4425835},"labels":[],"label_agreement":null},{"id":"W2763196980","doi":"10.1109/cibcb.2017.8058531","title":"Inferring bistable lac operen Boolean regulatory networks using evolutionary computation","year":2017,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"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 Guelph","funders":"","keywords":"Bistability; Evolutionary computation; Particle swarm optimization; Differential evolution; Boolean network; Computer science; Computation; Fitness function; Evolutionary algorithm; Boolean function; Genetic algorithm; Algorithm; Theoretical computer science; Mathematical optimization; Mathematics; Artificial intelligence; Machine learning; Physics","score_opus":0.019943037414127025,"score_gpt":0.27223761586657685,"score_spread":0.25229457845244985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2763196980","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":[0.93318385,0.0008876748,0.062478345,0.00007077205,0.00019558056,0.000111553236,0.0000021912037,0.000027485556,0.0030425745],"genre_scores_gemma":[0.99364537,0.000043404783,0.0039475667,0.00009687772,0.00050852686,0.000004018108,0.00008760237,0.000029466786,0.0016371707],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99892753,0.00005112684,0.00021665177,0.00037345302,0.00014277535,0.00028844862],"domain_scores_gemma":[0.9988744,0.00000476119,0.0001731172,0.000732995,0.00011350733,0.00010116393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020465055,0.0001653004,0.00016577059,0.00005252554,0.00063818455,0.000109366876,0.0002895989,0.00016358928,0.000036111152],"category_scores_gemma":[0.000026516467,0.00016950985,0.00012257537,0.00005479284,0.00011965792,0.0000148518075,0.00031059023,0.00007485631,0.0000074482996],"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":[0.000035783847,0.000041407897,0.07816087,0.0000126088225,0.00022089147,0.0000031154755,0.0000092263635,0.86423516,0.046266623,0.00022170511,0.00727421,0.0035183744],"study_design_scores_gemma":[0.0007608918,0.000079187055,0.24873379,0.000039824954,0.0001372327,0.00002844139,0.000059108184,0.72699344,0.011207785,0.00019359685,0.011141806,0.00062493124],"about_ca_topic_score_codex":0.00012981056,"about_ca_topic_score_gemma":0.000110170404,"teacher_disagreement_score":0.17057292,"about_ca_system_score_codex":0.000041245436,"about_ca_system_score_gemma":0.000073703835,"threshold_uncertainty_score":0.6912411},"labels":[],"label_agreement":null},{"id":"W2766400130","doi":"10.1016/j.pbiomolbio.2017.10.005","title":"What is it like to be “the same”?","year":2017,"lang":"en","type":"review","venue":"Progress in Biophysics and Molecular Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Identity (music); Matching (statistics); Epistemology; Mathematics; Computer science; Living systems; Pure mathematics; Artificial intelligence; Philosophy","score_opus":0.0411557883149633,"score_gpt":0.36809901722185184,"score_spread":0.32694322890688854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766400130","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00075458176,0.99637514,0.00010225354,0.0013649154,0.0005004418,0.00079580647,0.0000465666,0.0000074997315,0.000052816402],"genre_scores_gemma":[0.000857606,0.99504405,0.0003220027,0.0022099912,0.0003404548,0.00038325763,0.000407186,0.00008083843,0.0003546273],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9973034,0.00028745751,0.00052016333,0.0011603028,0.00013947865,0.0005891616],"domain_scores_gemma":[0.997692,0.000019955925,0.00039785856,0.0016360363,0.000089622416,0.00016454446],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00034239382,0.000631633,0.0012551694,0.00014415222,0.00018517819,0.00022472815,0.0010102306,0.0007282011,0.000006436256],"category_scores_gemma":[0.000021451217,0.00046219095,0.0005651164,0.0002361516,0.0005259858,0.000006560778,0.0009970195,0.000287187,0.000017472958],"study_design_candidate":"not_applicable","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":[0.000010219894,0.000051020175,0.00005016953,0.00055864034,0.00047466057,0.000017287173,0.00005554509,8.199374e-7,0.00024283555,0.00026638812,0.001112793,0.9971596],"study_design_scores_gemma":[0.00013807543,0.000178919,0.0000043960436,0.00075643515,0.00037178563,0.000022114318,0.00002772936,0.0000056543076,0.00033757783,0.00020011733,0.99742174,0.00053548045],"about_ca_topic_score_codex":0.000010530941,"about_ca_topic_score_gemma":0.000031063566,"teacher_disagreement_score":0.9966241,"about_ca_system_score_codex":0.000024918538,"about_ca_system_score_gemma":0.0001632757,"threshold_uncertainty_score":0.999783},"labels":[],"label_agreement":null},{"id":"W2770082463","doi":"10.1016/j.bbrc.2017.11.138","title":"Stochastic simulation of multiscale complex systems with PISKaS: A rule-based approach","year":2017,"lang":"en","type":"article","venue":"Biochemical and Biophysical Research Communications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Air Force Office of Scientific Research; Fondo Nacional de Desarrollo Científico y Tecnológico; Comisión Nacional de Investigación Científica y Tecnológica","keywords":"Computer science; Complex system; Stochastic differential equation; Ordinary differential equation; Stochastic modelling; Stochastic simulation; Population; Causality (physics); Complex network; System dynamics; Stochastic process; Mathematical optimization; Differential equation; Artificial intelligence; Mathematics; Applied mathematics","score_opus":0.1013594906432143,"score_gpt":0.37303779497267747,"score_spread":0.27167830432946316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2770082463","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":[0.9762624,0.00084779185,0.021113485,0.00056617387,0.000009072689,0.00046728077,0.000056897512,0.000013525845,0.0006634015],"genre_scores_gemma":[0.9962921,0.000041481435,0.0031528145,0.000008631831,0.00008641716,0.00007023115,0.0002461296,0.00001573601,0.00008641457],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998678,0.00019145268,0.00019923954,0.00032920786,0.00035018002,0.00025191624],"domain_scores_gemma":[0.99707925,0.000120301636,0.00012766727,0.0020996516,0.0004177478,0.00015538691],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033065732,0.00012985426,0.00021477883,0.000057515907,0.0005524291,0.000083647246,0.00092314417,0.00011876508,0.0000019346016],"category_scores_gemma":[0.00024745587,0.00010174792,0.00007552465,0.00013779207,0.001699433,0.0000063670736,0.00050233747,0.00018338152,0.0000025753918],"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":[0.00015761446,0.00050801877,0.00045269408,0.00007513128,0.0000967429,2.0126541e-7,0.000015086643,0.008710097,0.98829347,0.00036544306,0.00019466567,0.0011308126],"study_design_scores_gemma":[0.0011226468,0.00036971626,0.011463632,0.00009383207,0.00007981395,0.0000024436172,0.000106244035,0.9258326,0.059266116,0.000119635486,0.0012262708,0.00031703938],"about_ca_topic_score_codex":0.00012125716,"about_ca_topic_score_gemma":0.000008166234,"teacher_disagreement_score":0.9290274,"about_ca_system_score_codex":0.000016143264,"about_ca_system_score_gemma":0.00008640391,"threshold_uncertainty_score":0.6261631},"labels":[],"label_agreement":null},{"id":"W2771418007","doi":"10.1186/s12918-017-0481-6","title":"Model checking optimal finite-horizon control for probabilistic gene regulatory networks","year":2017,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"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 Calgary","funders":"National Natural Science Foundation of China","keywords":"Probabilistic logic; Reachability; Computer science; Gene regulatory network; Context (archaeology); Model checking; Biological network; Computation; Optimal control; Theoretical computer science; Mathematical optimization; Algorithm; Artificial intelligence; Bioinformatics; Mathematics; Biology","score_opus":0.027436090344342044,"score_gpt":0.2663482178349386,"score_spread":0.23891212749059657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2771418007","genre_codex":"methods","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":[0.3913958,0.0026732974,0.6041904,0.000023429317,0.0006688825,0.0008177615,0.000059182792,0.0000302706,0.00014098623],"genre_scores_gemma":[0.99354655,0.000041978627,0.0029663588,0.000038583385,0.0019115534,0.00040408518,0.00026792692,0.00006116195,0.00076181954],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977634,0.00019467178,0.0005180044,0.00080932415,0.00009465813,0.0006199664],"domain_scores_gemma":[0.9974666,0.00007642214,0.00054094876,0.0015379034,0.0002312813,0.0001467923],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008446761,0.000334444,0.00055856036,0.000059861355,0.000503348,0.000091834205,0.00066748797,0.0006690389,0.0000027096407],"category_scores_gemma":[0.0003838813,0.00031098962,0.00033350487,0.00003847901,0.00025093605,0.000006550043,0.00017546164,0.00010813496,0.0000048737998],"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":[0.00023833368,0.000037687954,0.0095952945,0.00006491156,0.00025704625,9.812761e-7,0.000008040955,0.8767545,0.110357665,0.0013216113,0.00066574675,0.0006981326],"study_design_scores_gemma":[0.001535877,0.00039157615,0.0014171746,0.000028647397,0.0001844171,0.000015585332,0.000019046498,0.9903704,0.0029935816,0.00012979996,0.002467996,0.0004459308],"about_ca_topic_score_codex":0.000024672156,"about_ca_topic_score_gemma":0.00006381964,"teacher_disagreement_score":0.60215074,"about_ca_system_score_codex":0.00004431784,"about_ca_system_score_gemma":0.00014757378,"threshold_uncertainty_score":0.9999342},"labels":[],"label_agreement":null},{"id":"W2772635314","doi":"10.1049/iet-syb.2017.0048","title":"Effective implicit finite‐difference method for sensitivity analysis of stiff stochastic discrete biochemical systems","year":2017,"lang":"en","type":"article","venue":"IET Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Compute Canada","keywords":"Sensitivity (control systems); Stochastic process; Context (archaeology); Range (aeronautics); Computer science; Stochastic differential equation; Applied mathematics; Stochastic modelling; Probabilistic logic; Mathematical model; Uncertainty quantification; Stochastic simulation; Estimation theory; Statistical physics; Mathematics; Mathematical optimization; Biological system; Algorithm; Machine learning; Statistics; Artificial intelligence; Physics","score_opus":0.012918799018313188,"score_gpt":0.3112214261782073,"score_spread":0.29830262715989414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2772635314","genre_codex":"methods","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":[0.49856716,0.0009368806,0.49894184,0.000020738406,0.000355884,0.00064136705,0.00049584196,0.000012157598,0.000028135411],"genre_scores_gemma":[0.9979705,0.00001378578,0.00057191594,0.0000132689975,0.00041878916,0.000272999,0.00053473306,0.000030187906,0.00017381123],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99727756,0.0006661277,0.0005670131,0.00088695297,0.00012690367,0.00047544413],"domain_scores_gemma":[0.99677664,0.00049139967,0.00076154753,0.0014761837,0.00035105692,0.00014318312],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0011628725,0.0003479728,0.0012120424,0.00020766442,0.00024620467,0.0000679545,0.0004358035,0.0005285511,0.0000019308632],"category_scores_gemma":[0.00071691687,0.0002968655,0.000592348,0.00016830747,0.00027732342,0.0000041576504,0.00025317783,0.00010651408,0.0000023885573],"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":[0.00019425689,0.000045740755,0.0140057355,0.00014034746,0.005259519,0.0000017149077,0.000033731278,0.046536695,0.9324227,0.00059877837,0.00016539716,0.00059540465],"study_design_scores_gemma":[0.002058286,0.0012607168,0.065019295,0.00016166423,0.0078284405,0.00005530474,0.00023264026,0.8353562,0.08501258,0.00015063774,0.0014618969,0.0014023798],"about_ca_topic_score_codex":0.00068473764,"about_ca_topic_score_gemma":0.0001270714,"teacher_disagreement_score":0.8474101,"about_ca_system_score_codex":0.00003904024,"about_ca_system_score_gemma":0.000058555095,"threshold_uncertainty_score":0.9999483},"labels":[],"label_agreement":null},{"id":"W2773561460","doi":"10.1007/978-1-4939-7528-0_3","title":"The MONGOOSE Rational Arithmetic Toolbox","year":2017,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mongoose; Toolbox; Arithmetic; Computer science; Programming language; Mathematics; Zoology; Biology","score_opus":0.01827348212418058,"score_gpt":0.37820757721190135,"score_spread":0.3599340950877208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2773561460","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15648498,0.0039150016,0.83487743,0.0012676717,0.00048053468,0.00024937832,0.0000052113414,0.000011675327,0.0027081142],"genre_scores_gemma":[0.45052424,0.0003015344,0.5464669,0.000522495,0.0003551549,0.00012941773,0.00007097745,0.000046269393,0.0015830237],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.997884,0.00089641527,0.00029640767,0.00046875895,0.000084022715,0.00037041676],"domain_scores_gemma":[0.99823517,0.000073894385,0.00018811385,0.0013613419,0.0000776311,0.00006385313],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016458173,0.00018212874,0.00021303896,0.000054586777,0.0004439767,0.00008304167,0.0008139377,0.0002450749,0.000011970438],"category_scores_gemma":[0.0010491555,0.00014058928,0.00017618624,0.00007436298,0.00043749993,0.000002741275,0.00029480897,0.00015109632,0.0000074713375],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033022607,0.000025458687,0.009475766,0.0000024418703,0.000114613205,0.000008161777,0.000008390535,0.00035706957,0.931921,0.005011338,0.00016839555,0.05287432],"study_design_scores_gemma":[0.0010504903,0.00024728716,0.029299794,0.000009738051,0.00007973996,0.000053945834,0.000044401968,0.002692878,0.7882036,0.023888553,0.15381841,0.0006111558],"about_ca_topic_score_codex":0.00002591501,"about_ca_topic_score_gemma":0.00010581568,"teacher_disagreement_score":0.29403925,"about_ca_system_score_codex":0.000018031325,"about_ca_system_score_gemma":0.00007207389,"threshold_uncertainty_score":0.57330644},"labels":[],"label_agreement":null},{"id":"W2775044045","doi":"10.1063/1.5001760","title":"An efficient hybrid method for stochastic reaction-diffusion biochemical systems with delay","year":2017,"lang":"en","type":"article","venue":"AIP Advances","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Benchmark (surveying); Reaction–diffusion system; Diffusion; Algorithm; Stochastic simulation; Mathematical optimization; Mathematics","score_opus":0.007774730527932551,"score_gpt":0.2880415467638254,"score_spread":0.28026681623589283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2775044045","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":[0.58409446,0.00196516,0.41350347,0.000031250256,0.00014797918,0.00019648872,0.000012520829,0.000011898669,0.000036753692],"genre_scores_gemma":[0.9888213,0.000050723935,0.010393789,0.000024889949,0.00039694388,0.00007813891,0.000106148625,0.000025047146,0.000102985556],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989774,0.000039741448,0.0001531488,0.00046142717,0.00013769722,0.00023056254],"domain_scores_gemma":[0.9987834,0.000021238298,0.00020563218,0.0007600815,0.0001244212,0.00010521033],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020772374,0.0001585517,0.00018609775,0.000029908424,0.00034423056,0.000059902326,0.00028436747,0.000067969144,0.0000013197943],"category_scores_gemma":[0.00005427449,0.00012577393,0.00007924105,0.000029098244,0.00008720435,0.0000079720985,0.00004808607,0.000045843473,0.0000019856109],"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":[0.00029429363,0.00011752859,0.00066498056,0.000038231894,0.00012436602,0.000002946737,0.000012889762,0.120336644,0.8728869,0.000057444082,0.00034156768,0.0051222052],"study_design_scores_gemma":[0.002800564,0.0020163946,0.0022792895,0.00015179414,0.00059337786,0.00023947979,0.0003411583,0.5002044,0.4359932,0.00019920002,0.05388537,0.0012957631],"about_ca_topic_score_codex":0.000021918626,"about_ca_topic_score_gemma":0.000021230166,"teacher_disagreement_score":0.4368937,"about_ca_system_score_codex":0.000017985547,"about_ca_system_score_gemma":0.000037970618,"threshold_uncertainty_score":0.5128912},"labels":[],"label_agreement":null},{"id":"W2780551716","doi":"10.1371/journal.pcbi.1005913","title":"System identification of signaling dependent gene expression with different time-scale data","year":2017,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"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":"Core Research for Evolutional Science and Technology; Institute of Genetics; Japan Science and Technology Agency; Japan Society for the Promotion of Science; Research Organization of Information and Systems","keywords":"Gene expression; Identification (biology); Gene; Biology; Computational biology; Gene expression profiling; Regulation of gene expression; Signal transduction; Cell biology; Computer science; Genetics","score_opus":0.019901362749225375,"score_gpt":0.2530811192296725,"score_spread":0.23317975648044714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2780551716","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":[0.94127136,0.00017350874,0.05817926,0.00003728234,0.000046886817,0.00012287685,0.00011569049,0.0000106239,0.00004253088],"genre_scores_gemma":[0.9936766,0.000007098063,0.0035462177,0.000008917422,0.00015232574,0.000011484429,0.0025191053,0.000013671281,0.000064603875],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988718,0.000097890625,0.0003052316,0.0004466274,0.0001472631,0.000131161],"domain_scores_gemma":[0.9984103,0.000023721885,0.00043493768,0.0009220521,0.00016156689,0.000047444195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016579108,0.00012395356,0.0002033243,0.000041435007,0.00019018527,0.000026230338,0.00060624315,0.00010067637,0.000009542773],"category_scores_gemma":[0.000026436257,0.00009836167,0.000042351432,0.000023252105,0.00011542633,0.0000068327954,0.00035341788,0.000040758925,0.000008643335],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058571844,0.000064263746,0.022825886,0.00002456948,0.00016354102,7.5224017e-7,0.0000072674948,0.016905684,0.9596143,0.000029544035,0.000047198653,0.00025842615],"study_design_scores_gemma":[0.000433525,0.00011201815,0.016542243,0.0000364869,0.000107838205,0.000012015115,0.000024901605,0.05418221,0.92826253,0.00009237244,0.00003056933,0.00016326946],"about_ca_topic_score_codex":0.0000058196915,"about_ca_topic_score_gemma":0.0000067465735,"teacher_disagreement_score":0.054633044,"about_ca_system_score_codex":0.000014293659,"about_ca_system_score_gemma":0.000041882067,"threshold_uncertainty_score":0.40110725},"labels":[],"label_agreement":null},{"id":"W2782908120","doi":"10.1038/s41467-017-02737-0","title":"The Chemical Fluctuation Theorem governing gene expression","year":2018,"lang":"en","type":"article","venue":"Nature Communications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":45,"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":"Ministry of Science, ICT and Future Planning","keywords":"Gene expression; Computational biology; Stochastic process; Gene; Expression (computer science); Regulation of gene expression; Messenger RNA; Biological system; Statistical physics; Biology; Computer science; Physics; Genetics; Mathematics; Statistics","score_opus":0.008658994878327705,"score_gpt":0.2709008586058665,"score_spread":0.26224186372753877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2782908120","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":[0.94993365,0.030049182,0.00478081,0.0040242486,0.00034900353,0.0003108451,0.000018834526,0.00006413196,0.010469324],"genre_scores_gemma":[0.99205303,0.00070200267,0.006067821,0.00020478161,0.00040063832,0.000020292431,0.00024570187,0.000014334817,0.00029137585],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99929905,0.00013105104,0.00013646096,0.00016941866,0.00012720416,0.0001368394],"domain_scores_gemma":[0.9977724,0.000054348555,0.00008889863,0.0018574664,0.00018712209,0.000039746294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026873124,0.0000869577,0.000061197854,0.000014344631,0.00056080933,0.000032559274,0.00089732435,0.0002317861,0.0000091187],"category_scores_gemma":[0.000209267,0.00006355566,0.00007451569,0.00014093462,0.00027541988,0.0000029088123,0.00045929776,0.00024673357,0.000025224128],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014162694,0.000016337743,0.00058482384,5.1647015e-7,0.000034448723,3.223543e-8,0.0000339357,0.00000915815,0.98487085,0.0011771421,0.0106084505,0.0026501194],"study_design_scores_gemma":[0.000110857414,0.0000211024,0.0013880577,0.0000052597247,0.000026750495,0.0000040648515,0.00004393329,0.00089155417,0.66673607,0.00027299722,0.3303955,0.00010385773],"about_ca_topic_score_codex":0.0000013300954,"about_ca_topic_score_gemma":0.0000641047,"teacher_disagreement_score":0.31978706,"about_ca_system_score_codex":0.000018908393,"about_ca_system_score_gemma":0.000037766466,"threshold_uncertainty_score":0.43133488},"labels":[],"label_agreement":null},{"id":"W2784221522","doi":"10.1109/cdc.2017.8263700","title":"Frequency domain properties of buffer-feedback regulation in cellular biology","year":2017,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Feedback regulation; Control theory (sociology); Feedback loop; Frequency domain; Computer science; Controller (irrigation); Feedback control; Positive feedback; Negative feedback; Domain (mathematical analysis); Regulator; Filter (signal processing); Stability (learning theory); Topology (electrical circuits); Control (management); Control engineering; Biology; Mathematics; Engineering; Voltage; Biochemistry","score_opus":0.014055578672574068,"score_gpt":0.23009502060425205,"score_spread":0.21603944193167798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2784221522","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":[0.9943164,0.0009446138,0.0011427385,0.00015204994,0.0000611621,0.00011158045,0.0000017585929,0.0000048130705,0.0032649129],"genre_scores_gemma":[0.99744266,0.00005509627,0.0017051975,0.000018850424,0.00010519308,0.00000921262,0.000030226958,0.000012037526,0.00062154495],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991572,0.00007113745,0.0002526593,0.0002732274,0.00006606399,0.00017975044],"domain_scores_gemma":[0.9989502,0.0000019875247,0.00016870313,0.00077561656,0.000068471665,0.00003501689],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022157954,0.000115346236,0.00018693211,0.000054798733,0.00008004631,0.000014763934,0.00029749668,0.00016955174,0.00004873738],"category_scores_gemma":[0.00004285172,0.0000963644,0.00008986981,0.000042964264,0.00019127491,0.000004497225,0.00011862611,0.000040539384,0.0000071658646],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016034532,0.000025770381,0.0649927,0.000012358419,0.0000351031,5.041687e-7,0.000020532963,0.000065406,0.93332624,0.0010706135,0.000074522985,0.00036023054],"study_design_scores_gemma":[0.00038150948,0.00006840827,0.04181556,0.000016605602,0.000014403933,0.0000013151646,0.000041858082,0.0001302308,0.9536144,0.0031746854,0.0005920628,0.000148917],"about_ca_topic_score_codex":0.00020799816,"about_ca_topic_score_gemma":0.00040921627,"teacher_disagreement_score":0.023177141,"about_ca_system_score_codex":0.00001165933,"about_ca_system_score_gemma":0.000040523533,"threshold_uncertainty_score":0.3929626},"labels":[],"label_agreement":null},{"id":"W2788234033","doi":"10.1007/978-3-319-92402-1_7","title":"A Framework for (De)composing with Boolean Automata Networks","year":2018,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Compute Canada","funders":"Agence Nationale de la Recherche","keywords":"Computer science; Formalism (music); Automaton; Theoretical computer science; Computation; Boolean function; Cellular automaton; Boolean algebra; Algorithm","score_opus":0.009889591011710297,"score_gpt":0.24872030806224427,"score_spread":0.23883071705053396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2788234033","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017666132,0.00078957604,0.9964397,0.00013623152,0.00032597771,0.00029778213,0.000004915844,0.00003115755,0.00020802442],"genre_scores_gemma":[0.3850809,0.00006996228,0.6099807,0.0012104294,0.0031751222,0.000016856977,0.00006179107,0.00009722686,0.0003069797],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977903,0.000020832973,0.00025920375,0.001057959,0.0002886091,0.0005830975],"domain_scores_gemma":[0.9983872,0.000084241365,0.00020584028,0.00100714,0.00018125724,0.00013427985],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004760076,0.0003935054,0.0003567375,0.00017464258,0.00020693729,0.00014793807,0.0008847467,0.0005244597,0.000014970743],"category_scores_gemma":[0.000037949096,0.00034431161,0.00015138311,0.00019055017,0.0007475411,0.000006115633,0.00036317934,0.00030441486,0.000003034668],"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":[0.00020547936,0.00005117418,0.00044722232,0.00008488784,0.00026239938,0.000029150655,0.0002436276,0.7668817,0.002634397,0.001771589,0.0004929465,0.22689539],"study_design_scores_gemma":[0.0006003427,0.0012812462,0.000145468,0.0008187555,0.0001539543,0.00013126431,5.271262e-7,0.89944685,0.00928894,0.07390325,0.012840976,0.0013884441],"about_ca_topic_score_codex":0.0000028936072,"about_ca_topic_score_gemma":0.000065031774,"teacher_disagreement_score":0.386459,"about_ca_system_score_codex":0.00008809017,"about_ca_system_score_gemma":0.00031412992,"threshold_uncertainty_score":0.9999009},"labels":[],"label_agreement":null},{"id":"W2789070738","doi":"10.1101/248682","title":"Antagonistic regulation with a unique setpoint, integral and double integral action","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nortel (Canada)","funders":"","keywords":"Setpoint; Control theory (sociology); Pairwise comparison; Action (physics); Controller (irrigation); Stability (learning theory); Control (management); Biology; Physics; Computer science; Artificial intelligence","score_opus":0.012558578469698978,"score_gpt":0.2296082642959992,"score_spread":0.21704968582630021,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2789070738","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":[0.9869943,0.0006808442,0.011157189,0.00010189032,0.0003685557,0.0005105255,0.000054626184,0.00011491761,0.000017155331],"genre_scores_gemma":[0.9927344,0.00030877063,0.005674587,0.00007896686,0.0009079321,0.00011112552,0.000010022615,0.0001293607,0.000044853085],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9975072,0.00014865784,0.00041083875,0.001204189,0.00026727252,0.00046183003],"domain_scores_gemma":[0.9975068,0.000010588784,0.0004205932,0.0012457212,0.0005712695,0.00024501234],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00043124447,0.00060357864,0.00048577573,0.00021145586,0.00019197071,0.00019605014,0.0003259722,0.000737952,0.000021204914],"category_scores_gemma":[0.000042632466,0.0005659428,0.0001481493,0.00032250697,0.00033231112,0.000015573409,0.00042716443,0.0004677415,0.000011783],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005024881,0.00008258846,0.015748695,0.000221733,0.0005616112,0.000012358818,0.000007163652,0.0003916777,0.9811399,0.00020047846,0.0011212336,0.000010067975],"study_design_scores_gemma":[0.0011953168,0.00040784263,0.055868205,0.00034697008,0.00050913653,4.2137503e-7,0.0000064746864,0.0021587843,0.9298467,0.000010440381,0.008463254,0.0011864334],"about_ca_topic_score_codex":0.000085246174,"about_ca_topic_score_gemma":0.000070355156,"teacher_disagreement_score":0.051293183,"about_ca_system_score_codex":0.00014945968,"about_ca_system_score_gemma":0.00047164538,"threshold_uncertainty_score":0.9996792},"labels":[],"label_agreement":null},{"id":"W2789382863","doi":"10.1007/978-1-4614-1800-9_35","title":"Complex Gene Regulatory Networks – from Structure to Biological Observables: Cell Fate Determination","year":2011,"lang":"en","type":"book-chapter","venue":"Computational Complexity","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Terminology; Glossary; Gene regulatory network; Boolean network; Systems biology; Computer science; Subject (documents); Computational biology; And-inverter graph; Observable; Network dynamics; Biology; Theoretical computer science; Gene; Boolean function; Boolean expression; Mathematics; Genetics; Gene expression; Philosophy; Library science; Linguistics; Algorithm; Physics; Discrete mathematics","score_opus":0.06614006773660074,"score_gpt":0.2506371343267032,"score_spread":0.18449706659010245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2789382863","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":[0.50646377,0.0049132323,0.43683574,0.00019384295,0.0013436753,0.0021599524,0.0041223434,0.00027971057,0.043687727],"genre_scores_gemma":[0.9224965,0.000057157933,0.039562315,0.0009144812,0.0014048987,0.000014624855,0.023879258,0.00012414635,0.011546605],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9972206,0.00012011568,0.00064888585,0.0012058667,0.00040250624,0.00040205286],"domain_scores_gemma":[0.99795955,0.000050765968,0.000457549,0.0008016648,0.00043258918,0.00029790282],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001474317,0.00066784583,0.00066465425,0.00013299267,0.00024814744,0.000054927077,0.00066135515,0.00078841805,0.0009921398],"category_scores_gemma":[0.0000150359,0.0006954699,0.0003959881,0.00007717887,0.00031395728,0.0000061217756,0.0005365458,0.00031031985,0.00007207529],"study_design_candidate":"simulation_or_modeling","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":[0.0012329447,0.00038313598,0.0036060356,0.00013822965,0.002293698,0.000103548984,0.0002699965,0.77535284,0.09428371,0.034462817,0.058129802,0.029743247],"study_design_scores_gemma":[0.0023854868,0.0012210286,0.22580288,0.00020984617,0.00083725376,0.000071531686,0.000017617447,0.10359797,0.007782026,0.4844104,0.16817585,0.005488094],"about_ca_topic_score_codex":0.000024362838,"about_ca_topic_score_gemma":0.000098892015,"teacher_disagreement_score":0.67175484,"about_ca_system_score_codex":0.00009725212,"about_ca_system_score_gemma":0.00011632951,"threshold_uncertainty_score":0.9999211},"labels":[],"label_agreement":null},{"id":"W2791135732","doi":"10.1007/978-1-4939-7710-9_13","title":"Predicting Gene Expression Noise from Gene Expression Variations","year":2018,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; McGill University and Génome Québec Innovation Centre","funders":"","keywords":"Gene expression; Gene; Noise (video); Expression (computer science); Biology; Computational biology; Regulation of gene expression; Genetics; Computer science; Artificial intelligence","score_opus":0.01539258045129562,"score_gpt":0.34034483800372173,"score_spread":0.3249522575524261,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2791135732","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.40215454,0.0010299542,0.59617156,0.0000357577,0.00027131473,0.00013234298,0.000020061141,0.000021336871,0.00016314593],"genre_scores_gemma":[0.31057292,0.00006839544,0.6880409,0.00021650326,0.00060940016,0.000054740263,0.0003350127,0.000040685063,0.00006145078],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9960824,0.0018253259,0.00051476154,0.0009665144,0.00012637129,0.00048459996],"domain_scores_gemma":[0.9984087,0.00008176206,0.00022527551,0.001010125,0.00013930394,0.00013483276],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010234991,0.00030532893,0.00037256491,0.00017010525,0.00015843254,0.000020802441,0.00045400806,0.00062524475,0.0001065486],"category_scores_gemma":[0.000499141,0.0002916848,0.0001887447,0.00032209212,0.00020329552,0.0000051437146,0.000493148,0.00020371724,0.000013701788],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056568213,0.000056481378,0.021063656,0.0000027269004,0.000071075236,0.0000059935014,0.00007517873,0.0003998188,0.9754952,0.00002755227,0.00009352207,0.0026522218],"study_design_scores_gemma":[0.00052604766,0.00016221248,0.0020612567,0.00001910611,0.000052272655,0.0000072063563,0.000025209845,0.0017331201,0.990976,0.0017198254,0.0024159155,0.00030186633],"about_ca_topic_score_codex":0.000059142312,"about_ca_topic_score_gemma":0.000026624064,"teacher_disagreement_score":0.091869354,"about_ca_system_score_codex":0.000035377005,"about_ca_system_score_gemma":0.000072182534,"threshold_uncertainty_score":0.9999535},"labels":[],"label_agreement":null},{"id":"W2791915932","doi":"10.1101/279109","title":"Improvement of the memory function of a mutual repression network in a stochastic environment by negative autoregulation","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Université de Montréal","funders":"Université de Montréal","keywords":"Bistability; Computer science; Autoregulation; Biological network; Function (biology); Gene regulatory network; Stochastic process; Control theory (sociology); Mathematics; Control (management); Physics; Biology; Artificial intelligence","score_opus":0.005353256722086243,"score_gpt":0.18827374970344896,"score_spread":0.1829204929813627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2791915932","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":[0.9900354,0.0010560257,0.0076383096,0.000025018051,0.00043202078,0.000731243,0.0000662745,0.000013080658,0.000002586435],"genre_scores_gemma":[0.99878365,0.00005318289,0.00055890414,0.000029406623,0.00038457068,0.00011895771,0.0000025662562,0.000055366076,0.000013414767],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9976141,0.00020466556,0.00068231474,0.0007989618,0.00038552686,0.00031446933],"domain_scores_gemma":[0.9973001,0.000019520023,0.0009896266,0.0014327634,0.00017955089,0.000078478406],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00060035597,0.0003584823,0.0004416341,0.00008523965,0.000071440896,0.000014171159,0.000385805,0.0004865097,0.000024326364],"category_scores_gemma":[0.00008353445,0.0003204487,0.00022368305,0.0002682499,0.0002479065,0.000006056182,0.00074533775,0.00023686317,0.0000021222804],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001326802,0.00011375217,0.005474454,0.00007382566,0.00022887111,2.8200373e-7,0.000008798603,0.068059705,0.92522264,0.0000066490675,0.000667739,0.000010636571],"study_design_scores_gemma":[0.00060058647,0.00023715208,0.14858127,0.00032300616,0.0002584925,4.477012e-9,0.000005300253,0.005264337,0.84409934,0.000009361641,0.00024084319,0.000380337],"about_ca_topic_score_codex":0.000036160753,"about_ca_topic_score_gemma":0.000006012213,"teacher_disagreement_score":0.1431068,"about_ca_system_score_codex":0.00014261765,"about_ca_system_score_gemma":0.00023515162,"threshold_uncertainty_score":0.9999248},"labels":[],"label_agreement":null},{"id":"W2793737711","doi":"10.1017/s0956792518000116","title":"Zeno breaking, the Contact effect and sensitive behaviour in piecewise-linear systems","year":2018,"lang":"en","type":"article","venue":"European Journal of Applied Mathematics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; University of Cambridge","keywords":"Zeno's paradoxes; Classification of discontinuities; Convergence (economics); Sequence (biology); Limit (mathematics); Multistability; Piecewise; Saddle point; Dynamical systems theory; Applied mathematics; Computer science; Statistical physics; Mathematics; Physics; Nonlinear system; Mathematical analysis; Quantum mechanics","score_opus":0.0066534383180002305,"score_gpt":0.22226312437316403,"score_spread":0.2156096860551638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2793737711","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":[0.99227655,0.00025827903,0.0034587765,0.000022585977,0.000083515064,0.0001574312,0.0000019199829,0.0000037697714,0.0037371817],"genre_scores_gemma":[0.9976037,0.00004044295,0.0016680969,0.000046387904,0.00054668303,9.84083e-7,0.0000022425463,0.000036007106,0.00005543201],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989366,0.0001671531,0.0004298821,0.00013896372,0.00016383194,0.00016354688],"domain_scores_gemma":[0.99911237,0.00004400529,0.0004100316,0.00025607273,0.0001088733,0.0000686619],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016475529,0.000153788,0.00027236142,0.000057489517,0.00006862153,0.000037255108,0.00018746016,0.00003774992,0.000003084064],"category_scores_gemma":[0.000037258134,0.00010075833,0.00008112293,0.00009003125,0.000102893966,0.0000027077024,0.00009527471,0.0001400633,0.00001279992],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00087004394,0.0004476709,0.0046001542,0.00037870125,0.0015366257,0.000487745,0.0061836946,0.0030198593,0.9635868,0.0025828579,0.0060034283,0.0103023965],"study_design_scores_gemma":[0.020412043,0.014432828,0.07680905,0.002459214,0.0045971624,0.009258528,0.01386864,0.026948646,0.77850586,0.00071395515,0.04814721,0.0038468407],"about_ca_topic_score_codex":0.0000011045801,"about_ca_topic_score_gemma":0.0000032815087,"teacher_disagreement_score":0.18508093,"about_ca_system_score_codex":0.000012235191,"about_ca_system_score_gemma":0.000020472566,"threshold_uncertainty_score":0.41088054},"labels":[],"label_agreement":null},{"id":"W2794281399","doi":"10.5539/ijsp.v7n2p50","title":"On a Geometric Extension of the Notion of Exchangeability Referring to Random Events","year":2018,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Extension (predicate logic); Bernoulli's principle; Multilinear map; Mathematics; Scheme (mathematics); Limit (mathematics); Point (geometry); Representation (politics); Meaning (existential); Probability theory; Discrete mathematics; Algebra over a field; Computer science; Pure mathematics; Epistemology; Statistics; Philosophy; Law","score_opus":0.016110250122841164,"score_gpt":0.27781440112832645,"score_spread":0.2617041510054853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2794281399","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":[0.96306926,0.00006628845,0.036300868,0.00011837898,0.00026189172,0.00009254591,0.000056948178,4.3863918e-7,0.00003338822],"genre_scores_gemma":[0.99551076,0.000035695226,0.0042670476,0.00003991512,0.00012273803,9.627022e-7,0.000004158911,0.0000037115492,0.0000150055575],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99902594,0.00009578047,0.0003814157,0.0001208853,0.0003154665,0.000060537386],"domain_scores_gemma":[0.9981984,0.00006329746,0.0003509846,0.00017419165,0.0011714275,0.000041684725],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000759851,0.00006245482,0.00014507264,0.00008099564,0.000024831248,0.0000046043783,0.000179438,0.00003889051,0.000014963449],"category_scores_gemma":[0.0009904442,0.00004331578,0.000075879616,0.00011803686,0.00009140532,0.0000031178015,0.00009861499,0.00004907377,2.9351924e-7],"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":[0.010779355,0.0017564807,0.33626398,0.00029954192,0.0016690382,0.0000051129073,0.0007575179,0.011838551,0.44033885,0.004123911,0.003235033,0.18893261],"study_design_scores_gemma":[0.0017177301,0.00155865,0.86304706,0.00014936518,0.000105712395,0.000023454024,0.000022720822,0.00076165074,0.10444693,0.02716403,0.00086599524,0.00013672546],"about_ca_topic_score_codex":0.0000142268,"about_ca_topic_score_gemma":0.000032143405,"teacher_disagreement_score":0.52678305,"about_ca_system_score_codex":0.0000260475,"about_ca_system_score_gemma":0.00004394259,"threshold_uncertainty_score":0.17663662},"labels":[],"label_agreement":null},{"id":"W2795031011","doi":"10.1101/287565","title":"Tuning gene expression variability and multi-gene regulation by dynamic transcription factor control","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Université de Montréal; Eidgenössische Technische Hochschule Zürich","keywords":"Pulsatile flow; Transcription factor; Gene expression; Gene; Regulation of gene expression; Computational biology; Biology; Gene regulatory network; Promoter; Saccharomyces cerevisiae; Transcription (linguistics); Genetics","score_opus":0.008110122348272924,"score_gpt":0.21150326350918097,"score_spread":0.20339314116090804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795031011","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":[0.8522712,0.001668799,0.14444147,0.000041462197,0.00040512093,0.00059655175,0.00048027583,0.00009446697,6.742e-7],"genre_scores_gemma":[0.983044,0.0004016664,0.015794048,0.000068649795,0.00041086593,0.000116690266,0.000021936265,0.00012925094,0.000012876597],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9965382,0.00045687467,0.00061037816,0.0015738922,0.00031633902,0.00050427753],"domain_scores_gemma":[0.9972775,0.000021202375,0.0004769894,0.0014629717,0.00046775184,0.00029356702],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00073543814,0.0006391995,0.00058442383,0.00013466841,0.00023788073,0.00013134253,0.00036874722,0.0010560033,0.00003190752],"category_scores_gemma":[0.00013219293,0.0006968635,0.00022771381,0.00018668798,0.00020965663,0.000018004208,0.00027157925,0.00034376935,0.0000065901477],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007754833,0.000097285134,0.008099683,0.000105688356,0.000226045,0.0000016060321,0.000005642962,0.0003427461,0.9909002,0.0000015196766,0.00013635494,0.000005648756],"study_design_scores_gemma":[0.0010011184,0.000072769464,0.082799695,0.00008608455,0.00023193106,3.492409e-8,9.672319e-7,0.013404633,0.90094423,0.0000014082112,0.0007405295,0.00071661547],"about_ca_topic_score_codex":0.000013622451,"about_ca_topic_score_gemma":0.000003346994,"teacher_disagreement_score":0.13077284,"about_ca_system_score_codex":0.00015826382,"about_ca_system_score_gemma":0.00020593278,"threshold_uncertainty_score":0.99954826},"labels":[],"label_agreement":null},{"id":"W2796240499","doi":"10.7554/elife.32323","title":"An incoherent feedforward loop facilitates adaptive tuning of gene expression","year":2018,"lang":"en","type":"article","venue":"eLife","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"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":"National Institute of General Medical Sciences; National Cancer Institute; National Institutes of Health; National Science Foundation","keywords":"Feed forward; Loop (graph theory); Gene expression; Feedback loop; Biology; Control theory (sociology); Computer science; Gene; Physics; Computational biology; Genetics; Mathematics; Artificial intelligence; Control (management); Control engineering; Engineering","score_opus":0.013917432920157827,"score_gpt":0.25555192334689175,"score_spread":0.24163449042673393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2796240499","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":[0.9875212,0.00055256224,0.011487952,0.000010886376,0.00006536716,0.0000728766,0.000012399421,0.000010975312,0.00026583782],"genre_scores_gemma":[0.99367064,0.00003650395,0.005522454,0.000051990908,0.00035929756,0.000007445933,0.00007209796,0.000015590656,0.00026394872],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999076,0.00008069861,0.0001994578,0.00029076412,0.00017386526,0.00017919364],"domain_scores_gemma":[0.9991606,0.0000052703663,0.00009980128,0.00043263272,0.0002015734,0.00010012248],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016757261,0.0001245526,0.00015724998,0.000041478594,0.000068182846,0.0000074653153,0.00018386259,0.00009022104,0.000047066762],"category_scores_gemma":[0.000024501307,0.00011200116,0.00008868444,0.0000938669,0.00012455747,0.0000040158448,0.00007847877,0.00003984911,0.000017784103],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000063503125,0.000038880113,0.0069211414,0.0000044452486,0.00006056308,4.76536e-7,0.00012328541,0.0005492356,0.9896238,0.0000036660865,0.0008991995,0.001711805],"study_design_scores_gemma":[0.00018973798,0.00048286509,0.0041287583,0.000012891681,0.00002422244,0.0000014323372,0.0002097665,0.0010594283,0.99140334,0.000011070602,0.002345745,0.0001307257],"about_ca_topic_score_codex":0.000016030186,"about_ca_topic_score_gemma":0.00002425943,"teacher_disagreement_score":0.0061495276,"about_ca_system_score_codex":0.000009899053,"about_ca_system_score_gemma":0.000043024014,"threshold_uncertainty_score":0.45672747},"labels":[],"label_agreement":null},{"id":"W2800979215","doi":"10.1101/315085","title":"Multisite phosphorylation regulates phenotypic variability in antibiotic tolerance","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"National Institutes of Health; Azrieli Foundation","keywords":"Sasa; Biology; Phenotype; Gene; Phosphorylation; Population; Gene expression; Regulation of gene expression; Genetics; Computational biology; Cell biology; Medicine","score_opus":0.0069777231294278555,"score_gpt":0.210250028878987,"score_spread":0.20327230574955915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2800979215","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":[0.9936216,0.002115185,0.0026921774,0.000047819158,0.0007241366,0.0006288528,0.00006385932,0.00009332282,0.000013086133],"genre_scores_gemma":[0.9928456,0.00028449707,0.005674816,0.000090348854,0.0009078817,0.000049921066,0.000004570642,0.00012620003,0.00001615003],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99616414,0.00043304721,0.0007298491,0.0017127964,0.00031464954,0.0006455156],"domain_scores_gemma":[0.9965649,0.000032935754,0.00047369077,0.002242706,0.00048381803,0.00020191437],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0014447924,0.0006435097,0.00066554704,0.00020472502,0.00012702745,0.00011213385,0.0006265776,0.001009059,0.00003498451],"category_scores_gemma":[0.00031222161,0.000745788,0.00026132973,0.0005579423,0.00023356541,0.00001263099,0.0006337559,0.000447157,0.000046985668],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007948114,0.00016683066,0.16486312,0.00020969147,0.0001869156,0.000008606212,0.00000542064,0.0035368693,0.8305844,0.000028685678,0.00032003867,0.000009934073],"study_design_scores_gemma":[0.00039724982,0.0000432844,0.40433064,0.00018275937,0.00009911976,1.1711456e-8,6.9773904e-7,0.004880055,0.5882386,0.0000063200305,0.0011408355,0.0006804068],"about_ca_topic_score_codex":0.0000752316,"about_ca_topic_score_gemma":0.00002951731,"teacher_disagreement_score":0.2423458,"about_ca_system_score_codex":0.000202539,"about_ca_system_score_gemma":0.00033252078,"threshold_uncertainty_score":0.9994993},"labels":[],"label_agreement":null},{"id":"W2801323461","doi":"10.4018/978-1-4666-5202-6.ch033","title":"Bio-Inspired Modelling to Generate Alternatives","year":2014,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"York University","funders":"","keywords":"Computer science; Mathematical optimization; Decision problem; Mathematics; Algorithm","score_opus":0.01664059264691198,"score_gpt":0.23699667430468072,"score_spread":0.22035608165776874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2801323461","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02324784,0.0018126748,0.05974212,0.00006454029,0.0004599317,0.00041260666,0.0001384308,0.000066591536,0.9140553],"genre_scores_gemma":[0.7609923,0.000053459986,0.0031887947,0.001011051,0.002145907,0.000024261668,0.00008776548,0.00013018952,0.23236626],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979978,0.000033533095,0.00039094067,0.0008874803,0.0002889771,0.0004012677],"domain_scores_gemma":[0.9984754,0.00000390374,0.00021214121,0.0008599465,0.00016886149,0.00027978772],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012370694,0.00053726643,0.00048679722,0.00007169082,0.00009922091,0.000059158563,0.00045772683,0.00050359266,0.000017582086],"category_scores_gemma":[0.0000065671834,0.0005558029,0.0004038232,0.000020113219,0.00007634797,9.3704733e-7,0.00028523858,0.00012063019,0.00016224552],"study_design_candidate":"not_applicable","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":[0.00027456996,0.000027328995,0.0001071238,0.000085374304,0.002834372,0.00006571119,0.000058633494,0.1640777,0.038338397,0.7518827,0.01995274,0.02229537],"study_design_scores_gemma":[0.000941888,0.0006456038,0.000016618664,0.00024835585,0.00073112315,0.000050949828,0.000007666542,0.009955669,0.04361368,0.05378328,0.8871643,0.0028408861],"about_ca_topic_score_codex":0.000026184884,"about_ca_topic_score_gemma":0.00007467683,"teacher_disagreement_score":0.8672115,"about_ca_system_score_codex":0.000077199504,"about_ca_system_score_gemma":0.00011203295,"threshold_uncertainty_score":0.99968934},"labels":[],"label_agreement":null},{"id":"W2801981714","doi":"10.1002/ijch.201800003","title":"Mathematical Analysis of Chemical Reaction Systems","year":2018,"lang":"en","type":"preprint","venue":"Israel Journal of Chemistry","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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; University of Wisconsin-Madison; National Science Foundation","keywords":"Orthant; Homogeneous; Nonlinear system; Mathematical model; Action (physics); Chemical reaction; Focus (optics); Computer science; Mathematics; Applied mathematics; Statistical physics; Chemistry; Physics","score_opus":0.010365217462465066,"score_gpt":0.2572917948642931,"score_spread":0.24692657740182802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2801981714","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":[0.9943171,0.0024551568,0.0020192,0.000030323483,0.00021126984,0.0000647592,0.000035371748,0.0000052153446,0.0008615602],"genre_scores_gemma":[0.99717605,0.00018962462,0.00071509817,0.000011606303,0.0014462874,0.000004285157,0.0001755561,0.000034444187,0.0002470276],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9974832,0.00007162843,0.0012673439,0.00038174947,0.00056349643,0.0002325667],"domain_scores_gemma":[0.99603075,0.000027934882,0.0019979896,0.00087665697,0.00088053173,0.00018614458],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00066906784,0.0003222029,0.0011198177,0.00016779148,0.000019973624,0.000034495282,0.0006340799,0.0008257738,0.000052474283],"category_scores_gemma":[0.00018304003,0.00029908025,0.001312315,0.00031613142,0.00019087493,0.000003437813,0.00036902382,0.00043885683,0.0000026253786],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000108720196,0.00013668345,0.001011484,0.0004101512,0.007900477,0.000009159953,0.000019927314,0.0035611582,0.9850616,0.0000038035312,0.0016808788,0.0000959734],"study_design_scores_gemma":[0.00032414534,0.00005659428,0.00022176723,0.00026701426,0.007631916,0.00015907716,0.000109721535,0.0026301225,0.98702866,0.00015492876,0.0010638364,0.00035222445],"about_ca_topic_score_codex":0.0000054277134,"about_ca_topic_score_gemma":4.1540858e-7,"teacher_disagreement_score":0.0028589272,"about_ca_system_score_codex":0.00007568486,"about_ca_system_score_gemma":0.00026034255,"threshold_uncertainty_score":0.9999461},"labels":[],"label_agreement":null},{"id":"W2802396750","doi":"10.25336/csp29385","title":"Information Geometry and Population Genetics: The Mathematical Structure of the Wright - Fisher Model","year":2018,"lang":"en","type":"article","venue":"Canadian Studies in Population","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Wright; Fisher information; Population; Population genetics; Evolutionary biology; Mathematics; Geometry; Demography; Computer science; Statistics; Biology; Sociology","score_opus":0.011517442803460207,"score_gpt":0.2499576975370747,"score_spread":0.2384402547336145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2802396750","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":[0.9987233,0.0006065342,0.00013513019,0.00015392134,0.00009710669,0.00015976763,0.000015647993,0.0000017700523,0.00010679096],"genre_scores_gemma":[0.99932617,0.00004367101,0.00024218981,0.00017595684,0.000102222875,0.000003823211,0.000057447436,0.00000621437,0.000042288455],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99938303,0.00004254747,0.00023657315,0.000095916585,0.00010802676,0.00013391246],"domain_scores_gemma":[0.99948823,0.0000074813274,0.00010116583,0.00027125888,0.000094886134,0.00003697305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011263606,0.00008781677,0.0001082257,0.000078398116,0.000151726,0.000011587457,0.00010505828,0.00009493431,0.0000078790645],"category_scores_gemma":[0.00008890121,0.000056522116,0.00003402048,0.00019738276,0.00014179954,0.000010241862,0.00005956085,0.000047585723,6.7723624e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023052344,0.000009485727,0.94589514,0.0001061413,0.0002522299,1.8592684e-7,0.0021901424,0.032181494,0.0025447367,0.0025938198,0.0035965566,0.010607038],"study_design_scores_gemma":[0.0002287798,0.000034486733,0.9456887,0.00003520536,0.00008257058,0.000006221292,0.0004981459,0.040756766,0.0014591337,0.009997622,0.0010323662,0.00017996837],"about_ca_topic_score_codex":0.0015763514,"about_ca_topic_score_gemma":0.08098849,"teacher_disagreement_score":0.07941213,"about_ca_system_score_codex":0.00005980186,"about_ca_system_score_gemma":0.00003286106,"threshold_uncertainty_score":0.93578106},"labels":[],"label_agreement":null},{"id":"W2803444648","doi":"10.15381/pes.v20i2.13969","title":"Modelamiento Computacional de la Dinamica de Transmisión de la Varicela mediante Automatas Celulares (Cell-DEVS)","year":2018,"lang":"es","type":"article","venue":"Pesquimat","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Carleton University","funders":"","keywords":"Physics; Humanities; Philosophy","score_opus":0.0033033299473583244,"score_gpt":0.2523044425996228,"score_spread":0.2490011126522645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803444648","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":[0.8940843,0.006303328,0.09406149,0.00031730285,0.00012508445,0.0001785914,0.00012866902,0.00007663077,0.004724629],"genre_scores_gemma":[0.98634577,0.0013067656,0.0103589175,0.00029381248,0.000876619,0.000025201807,0.0002530956,0.000098459546,0.00044133342],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9965411,0.00090567704,0.00044549187,0.00075050426,0.00036717628,0.0009900564],"domain_scores_gemma":[0.9983934,0.00017077732,0.00019033604,0.00066204724,0.00015033684,0.0004330644],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008940626,0.00049301854,0.0004442992,0.0001440829,0.00031584696,0.00023175373,0.0006869918,0.0008079849,0.00017870581],"category_scores_gemma":[0.000053860993,0.0005199119,0.00042936113,0.0002989028,0.0008175579,0.000012676514,0.00024991846,0.000324439,0.00006674204],"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":[0.00040514654,0.0011812628,0.017414104,0.00062715623,0.0014575742,0.00027034382,0.0022477673,0.036554515,0.91192687,0.0028296208,0.019542346,0.0055432813],"study_design_scores_gemma":[0.0019988902,0.00043833326,0.015089908,0.00017993418,0.0011116733,0.00060348347,0.00019273833,0.7004796,0.16055231,0.0018497074,0.11621957,0.0012838282],"about_ca_topic_score_codex":0.00009235066,"about_ca_topic_score_gemma":0.000018741755,"teacher_disagreement_score":0.7513746,"about_ca_system_score_codex":0.00020391417,"about_ca_system_score_gemma":0.0005397269,"threshold_uncertainty_score":0.9997252},"labels":[],"label_agreement":null},{"id":"W2804017725","doi":"10.1016/b978-0-12-809633-8.20287-2","title":"Computational Systems Biology","year":2018,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Modelling biological systems; Computational biology; Systems biology; Computer science; Biology; Cognitive science; Psychology","score_opus":0.010634189867947183,"score_gpt":0.23597634799163844,"score_spread":0.22534215812369127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2804017725","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00088911655,0.0055137295,0.00021778984,0.000014040142,0.00053116627,0.00028249042,0.00006823743,0.000025193536,0.9924582],"genre_scores_gemma":[0.014457872,0.000081455226,0.00037867416,0.00015900921,0.0021026207,0.000021283648,0.00084123167,0.000091401875,0.9818665],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99851567,0.00004782667,0.0003919521,0.00062072754,0.00016153647,0.0002622913],"domain_scores_gemma":[0.9987791,0.000011491899,0.0002645622,0.00060949964,0.00022199037,0.00011332534],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018151168,0.00037338765,0.00042525955,0.00009908159,0.00009290464,0.00002835207,0.0002944738,0.00063241855,0.00020523914],"category_scores_gemma":[0.0000075441103,0.0003657763,0.00030581636,0.000009649935,0.00026755987,6.435122e-7,0.00018620987,0.00014393621,0.00031524032],"study_design_candidate":"not_applicable","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":[0.00010282973,0.000032815948,0.00017939939,0.0002322437,0.004379083,0.000028329434,0.00008825694,0.0022924345,0.0050292704,0.017650137,0.028871037,0.9411142],"study_design_scores_gemma":[0.00015828948,0.00012654916,0.000006833537,0.000052578118,0.00014775326,0.000027445849,0.0000024143806,0.00015072634,0.00011204582,0.004361361,0.9944686,0.0003853976],"about_ca_topic_score_codex":2.823545e-7,"about_ca_topic_score_gemma":0.000007725902,"teacher_disagreement_score":0.96559757,"about_ca_system_score_codex":0.000030690902,"about_ca_system_score_gemma":0.00014343936,"threshold_uncertainty_score":0.9998794},"labels":[],"label_agreement":null},{"id":"W2806735107","doi":"10.1016/j.jmaa.2018.10.042","title":"The combined effects of Feller diffusion and transcriptional/translational bursting in simple gene networks","year":2018,"lang":"en","type":"article","venue":"Journal of Mathematical Analysis and Applications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Narodowe Centrum Nauki; Simons Foundation","keywords":"Bursting; Statistical physics; Diffusion process; Mathematics; Diffusion; Stochastic process; Markov process; Markov chain; Physics; Computer science; Biology; Statistics; Neuroscience; Thermodynamics","score_opus":0.004867799079482512,"score_gpt":0.2315875920010977,"score_spread":0.22671979292161518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2806735107","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":[0.699675,0.0015303037,0.29847044,0.00019638869,0.0000053574895,0.00008600665,0.0000014033403,8.7397694e-7,0.000034203462],"genre_scores_gemma":[0.9975135,0.0005142808,0.0017619107,0.000020029018,0.00013664053,0.000008636917,0.000010335499,0.000005053677,0.000029651112],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99918425,0.000050946022,0.00042186736,0.00011020965,0.00013870581,0.00009403752],"domain_scores_gemma":[0.9993307,0.00013300184,0.00020603322,0.00013185978,0.00013903032,0.000059362803],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037841825,0.0000762553,0.00022693882,0.00008127287,0.00012353265,0.000017229291,0.00009013527,0.000056485445,0.000008496388],"category_scores_gemma":[0.000031299034,0.000050747683,0.00014398826,0.00034346266,0.00016352904,0.000003862407,0.000023918627,0.000059600206,2.315594e-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":[0.00045636902,0.0015893066,0.1414573,0.00030503148,0.0074471636,0.0000034044813,0.00070870394,0.015868736,0.71910524,0.05187145,0.0003955929,0.06079168],"study_design_scores_gemma":[0.0035401403,0.00087209675,0.5885685,0.00013719859,0.006438973,0.0000735019,0.00035834158,0.28364596,0.034660358,0.07643756,0.0046322127,0.0006351624],"about_ca_topic_score_codex":0.00000195718,"about_ca_topic_score_gemma":0.00002630829,"teacher_disagreement_score":0.6844449,"about_ca_system_score_codex":0.0000034284778,"about_ca_system_score_gemma":0.00001331987,"threshold_uncertainty_score":0.20694305},"labels":[],"label_agreement":null},{"id":"W2811149315","doi":"10.5539/jmr.v10n4p116","title":"Double Hopf Bifurcation of a Hematopoietic System with State Feedback Control","year":2018,"lang":"en","type":"article","venue":"Journal of Mathematics Research","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Hopf bifurcation; Mathematics; Center manifold; Attractor; Biological applications of bifurcation theory; Control theory (sociology); Bifurcation; Feedback control; Control (management); Mathematical analysis; Nonlinear system; Physics; Computer science; Quantum mechanics; Artificial intelligence","score_opus":0.02910362443825915,"score_gpt":0.3199621066382928,"score_spread":0.29085848220003363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2811149315","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":[0.94420475,0.00040767298,0.054340556,0.00007447593,0.00003939375,0.00018558325,0.0000023700134,0.0000028099087,0.0007424018],"genre_scores_gemma":[0.99392545,0.000040986175,0.005373991,0.00000594709,0.00024386222,0.0000035769608,0.0000015432779,0.000024397674,0.00038026302],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99800515,0.00012636755,0.0005935432,0.0001351672,0.00085346133,0.00028631114],"domain_scores_gemma":[0.9967647,0.00006681427,0.0005098349,0.00041111303,0.0021201556,0.00012738063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003292021,0.000109399865,0.00033060194,0.00027052115,0.00007680981,0.00003087583,0.00033162732,0.00008662821,0.000016789585],"category_scores_gemma":[0.00006751553,0.00007749068,0.000119223805,0.0003729676,0.00026853324,0.000006392317,0.00006208742,0.00016250608,0.0000146413895],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027468447,0.0010027152,0.005587695,0.0022271727,0.0022743205,0.000053784053,0.0022993244,0.0028322674,0.9717673,0.002524159,0.0053422856,0.0013420971],"study_design_scores_gemma":[0.0065457774,0.004621216,0.0011794992,0.0010155982,0.00026795032,0.0008834928,0.0051643387,0.0068699457,0.97021085,0.00090031506,0.001973435,0.00036757646],"about_ca_topic_score_codex":0.000007288081,"about_ca_topic_score_gemma":0.000026175832,"teacher_disagreement_score":0.049720697,"about_ca_system_score_codex":0.000048300353,"about_ca_system_score_gemma":0.0002326055,"threshold_uncertainty_score":0.31599784},"labels":[],"label_agreement":null},{"id":"W2888373391","doi":"10.1038/s41467-018-05882-2","title":"Pulsatile inputs achieve tunable attenuation of gene expression variability and graded multi-gene regulation","year":2018,"lang":"en","type":"article","venue":"Nature Communications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":124,"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":"Université de Montréal; European Research Council; Eidgenössische Technische Hochschule Zürich; European Commission","keywords":"Pulsatile flow; Optogenetics; Gene expression; Gene; Computational biology; Regulation of gene expression; Transcription factor; Gene regulatory network; Biology; Promoter; Synthetic biology; Transcription (linguistics); Systems biology; Saccharomyces cerevisiae; Genetics; Cell biology; Neuroscience","score_opus":0.016265481425113984,"score_gpt":0.2832469737881018,"score_spread":0.26698149236298785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2888373391","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":[0.9902167,0.0022549757,0.006258242,0.000553486,0.000084588966,0.0002996267,0.000038791524,0.000017996084,0.00027559165],"genre_scores_gemma":[0.9620016,0.00021694388,0.0365031,0.00008250146,0.00008229785,0.00003464418,0.0009388643,0.000014846754,0.00012516374],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988417,0.00036516826,0.0002552144,0.00027417898,0.00014140976,0.0001223157],"domain_scores_gemma":[0.99768454,0.000041187297,0.00020696652,0.0017269376,0.0002901176,0.000050244278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049786037,0.000112781476,0.00013910902,0.00006260123,0.00031493633,0.000011055148,0.0004257809,0.0002660582,0.000029619787],"category_scores_gemma":[0.00017667015,0.00011514317,0.00006159207,0.00024486776,0.00021775026,0.000009301647,0.00039594664,0.0001971096,0.0000013335775],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027814545,0.00011228896,0.013878067,0.000005345078,0.000039839393,2.6420011e-8,0.00009627462,0.00015246203,0.98454577,0.00011570242,0.0005025563,0.00052386784],"study_design_scores_gemma":[0.0004764128,0.00011627956,0.10448629,0.000008969917,0.00007748917,0.00000487,0.00003394382,0.0042025247,0.8823,0.00035642573,0.0077487556,0.00018804296],"about_ca_topic_score_codex":0.000009812464,"about_ca_topic_score_gemma":0.00008696084,"teacher_disagreement_score":0.102245755,"about_ca_system_score_codex":0.000025860281,"about_ca_system_score_gemma":0.000047949212,"threshold_uncertainty_score":0.4695402},"labels":[],"label_agreement":null},{"id":"W2890951255","doi":"10.1155/2018/7257083","title":"An <i>r</i>‐Order Finite‐Time State Observer for Reaction‐Diffusion Genetic Regulatory Networks with Time‐Varying Delays","year":2018,"lang":"en","type":"article","venue":"Complexity","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Science North","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Observer (physics); MATLAB; Control theory (sociology); Reaction–diffusion system; Stability (learning theory); Dirichlet boundary condition; Mathematics; State (computer science); Diffusion; Boundary value problem; Computer science; Order (exchange); Applied mathematics; Mathematical optimization; Mathematical analysis; Algorithm; Physics; Control (management)","score_opus":0.01951044707114119,"score_gpt":0.24368631786916564,"score_spread":0.22417587079802445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890951255","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":[0.93210536,0.000282563,0.06675811,0.00004043496,0.00009763268,0.00035726558,0.00002679658,0.000058870224,0.00027296465],"genre_scores_gemma":[0.97668463,0.000029276422,0.019622067,0.0003613956,0.0009740707,0.000039149352,0.0007262369,0.000084355255,0.0014788483],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99816144,0.00013869206,0.00031134585,0.0007038856,0.00019500797,0.00048961525],"domain_scores_gemma":[0.99813884,0.000026684733,0.00019190474,0.0010182046,0.00041904085,0.0002053263],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00026976047,0.0003022915,0.00029699987,0.000057403555,0.00040274335,0.00004904458,0.0003297297,0.00018015724,0.00013090756],"category_scores_gemma":[0.000023796725,0.00028308024,0.00013491961,0.00025813477,0.0003469624,0.000012883149,0.0001283068,0.00009903343,0.00004828744],"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":[0.0013751087,0.0003648918,0.009132801,0.0000422056,0.00057880534,0.0000064816263,0.00013308575,0.08547406,0.8833146,0.000031179683,0.011052933,0.008493839],"study_design_scores_gemma":[0.002733076,0.0030229238,0.08127386,0.000062328,0.00033195456,0.000052317922,0.000025195044,0.8313392,0.042132936,0.0010326552,0.03652409,0.0014694752],"about_ca_topic_score_codex":0.000026422074,"about_ca_topic_score_gemma":0.000117518,"teacher_disagreement_score":0.8411817,"about_ca_system_score_codex":0.00003735873,"about_ca_system_score_gemma":0.000090976566,"threshold_uncertainty_score":0.99996215},"labels":[],"label_agreement":null},{"id":"W2891613640","doi":"10.1103/physrevlett.122.158302","title":"Chebyshev Approximation and the Global Geometry of Model Predictions","year":2019,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"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 Materials Research; Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Smoothness; Universality (dynamical systems); Exponential function; Class (philosophy); Nonlinear system; Chebyshev filter; Applied mathematics; Mathematics; Statistical physics; Computer science; Physics; Mathematical analysis; Artificial intelligence; Quantum mechanics","score_opus":0.007040294138843095,"score_gpt":0.25008252199050546,"score_spread":0.24304222785166235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891613640","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":[0.98250866,0.009013513,0.006254775,0.0017155703,0.000018251714,0.00025734556,0.0000068622244,0.0000041140934,0.00022091689],"genre_scores_gemma":[0.9948596,0.0026184737,0.00019400523,0.002200745,0.00006962796,0.000017981098,0.000023003442,0.000004913745,0.000011650072],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994698,0.00005211909,0.00012537926,0.0001583581,0.000108852015,0.0000854647],"domain_scores_gemma":[0.99958354,0.000009747769,0.00007736498,0.00027753922,0.000025143705,0.00002666688],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001364709,0.000075607364,0.00019121011,0.0000069528696,0.000020207466,0.0000044670373,0.00009541303,0.00001078016,0.0000030809226],"category_scores_gemma":[0.000021413918,0.00005039802,0.00014482586,0.00013290426,0.000094009505,0.0000026176742,0.00005896234,0.00003624348,0.000005415559],"study_design_candidate":"simulation_or_modeling","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":[0.00025267975,0.0004571286,0.02672089,0.004523171,0.0018299208,5.904023e-7,0.00016021637,0.26842353,0.63973254,0.018703394,0.021885587,0.017310333],"study_design_scores_gemma":[0.0028223116,0.00015713535,0.010490149,0.0008275793,0.0016235844,0.000013609543,0.000026111824,0.96242076,0.0104895355,0.0023515897,0.008099451,0.0006781623],"about_ca_topic_score_codex":0.0000022989468,"about_ca_topic_score_gemma":4.4144625e-7,"teacher_disagreement_score":0.69399726,"about_ca_system_score_codex":0.000007480885,"about_ca_system_score_gemma":0.0000101493815,"threshold_uncertainty_score":0.20551716},"labels":[],"label_agreement":null},{"id":"W2891614933","doi":"10.1093/bib/bby088","title":"Control principles for complex biological networks","year":2018,"lang":"en","type":"review","venue":"Briefings in Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":67,"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 Saskatchewan","funders":"National Natural Science Foundation of China","keywords":"Computer science; Control (management); Biological network; Computational biology; Artificial intelligence; Biology","score_opus":0.0715509303580077,"score_gpt":0.3120003368285108,"score_spread":0.2404494064705031,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891614933","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000021562462,0.94506514,0.052963793,0.00002403518,0.0001532146,0.0013112873,0.00012270013,0.000029124096,0.0003091252],"genre_scores_gemma":[0.000070125694,0.98132235,0.014756414,0.0005819373,0.00075199275,0.00023283719,0.0020838827,0.00006316032,0.00013727626],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99727446,0.00009917574,0.0014150422,0.0004418789,0.00014525041,0.00062417745],"domain_scores_gemma":[0.9981318,0.000105758096,0.00081979705,0.00069946575,0.00012397434,0.00011921327],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00072269014,0.00055865024,0.0015076044,0.00015378043,0.00011766141,0.00007169312,0.0006418668,0.00097296864,0.000015760255],"category_scores_gemma":[0.00023589544,0.00045237807,0.00082769163,0.00028151338,0.00024007971,0.0000048321067,0.00025114632,0.00019951357,0.000021216518],"study_design_candidate":"not_applicable","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":[0.00009848008,0.00018485088,0.00013140365,0.011045693,0.001751779,0.00000481228,0.00006189778,0.0023137266,0.000009810467,0.00079193636,0.08098575,0.90261984],"study_design_scores_gemma":[0.00047444418,0.00016943298,0.000015606633,0.0009012093,0.00029367788,0.000030784842,0.0000052119144,0.01703996,0.0000021398819,0.000016594213,0.9805307,0.0005202603],"about_ca_topic_score_codex":0.0000049919827,"about_ca_topic_score_gemma":0.000019392359,"teacher_disagreement_score":0.9020996,"about_ca_system_score_codex":0.00005964949,"about_ca_system_score_gemma":0.00017792333,"threshold_uncertainty_score":0.9997928},"labels":[],"label_agreement":null},{"id":"W2892136592","doi":"10.1016/j.jtbi.2018.09.014","title":"Hybrid models of genetic networks: Mathematical challenges and biological relevance","year":2018,"lang":"en","type":"article","venue":"Journal of Theoretical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria; McGill University","funders":"","keywords":"Ordinary differential equation; Nonlinear system; Biological network; Computer science; Simple (philosophy); Differential equation; Class (philosophy); Gene regulatory network; Relevance (law); Mathematics; Piecewise linear function; Applied mathematics; Biological system; Theoretical computer science; Artificial intelligence; Biology; Mathematical analysis; Physics; Gene","score_opus":0.01578161612112383,"score_gpt":0.2510893192881577,"score_spread":0.23530770316703387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892136592","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":[0.89390236,0.019910958,0.08504714,0.00031739048,0.00012030215,0.000067091234,0.0000031788331,0.0000039060556,0.0006276571],"genre_scores_gemma":[0.9809637,0.01110743,0.007122373,0.00009767076,0.00068210665,0.0000016490053,0.0000026550408,0.000013976115,0.0000084329395],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99847907,0.0002840626,0.00060508895,0.0002572147,0.000097623946,0.0002769408],"domain_scores_gemma":[0.9988366,0.00014156412,0.00031969717,0.00029018853,0.00026378874,0.00014816532],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064668205,0.00016901112,0.00047936014,0.000063465865,0.000034444805,0.0000052935943,0.000292196,0.00023735985,0.000058564878],"category_scores_gemma":[0.0003490484,0.000115558454,0.00018882267,0.000049372746,0.0019916075,0.000003598765,0.00017793462,0.00013780459,0.0000026213552],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013424556,0.00038867258,0.0019593425,0.000065619904,0.0009747195,0.000028862418,0.0001233675,0.0014048519,0.1366536,0.79771405,0.000566634,0.058777817],"study_design_scores_gemma":[0.0010034123,0.0059051537,0.0019495668,0.00008161301,0.00022455321,0.0010633525,0.00007892301,0.017004246,0.03226151,0.93807805,0.0019530462,0.0003966018],"about_ca_topic_score_codex":1.4770113e-7,"about_ca_topic_score_gemma":3.792446e-7,"teacher_disagreement_score":0.14036396,"about_ca_system_score_codex":0.0000072001935,"about_ca_system_score_gemma":0.000030198624,"threshold_uncertainty_score":0.733816},"labels":[],"label_agreement":null},{"id":"W2894552244","doi":"10.1103/physreve.101.022118","title":"Optimal control of protein copy number","year":2020,"lang":"en","type":"article","venue":"Physical review. E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of Waterloo","funders":"Simon Fraser University; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Receptor; Optogenetics; Chemical biology; Cytosol; Cell membrane; Cell; Extracellular; Biophysics; Chemistry; Cell biology; Biology; Biochemistry; Neuroscience","score_opus":0.009202534886924829,"score_gpt":0.2861107750415008,"score_spread":0.27690824015457594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2894552244","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":[0.9808128,0.011410757,0.004981459,0.001420517,0.000012641583,0.00043835078,0.000013119856,0.000010767379,0.0008996241],"genre_scores_gemma":[0.99738455,0.0008063761,0.00037201593,0.0009806342,0.00033851265,0.000032059397,0.000023099024,0.000014164799,0.000048594717],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99924165,0.00007528422,0.00018282911,0.00023253918,0.00013289117,0.00013482572],"domain_scores_gemma":[0.99948275,0.000006169572,0.000099963734,0.0002357661,0.00006957496,0.00010574953],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006846324,0.00011306929,0.0003332213,0.0000033219003,0.000015401041,0.0000033418505,0.00015286208,0.00002943757,0.000060378923],"category_scores_gemma":[0.000084867985,0.00009618356,0.00026546765,0.000121634,0.0000493788,0.0000015014489,0.000053054308,0.00005586031,0.00008313725],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000062918225,0.00011333642,0.0018704789,0.0005202737,0.0002208281,0.0000017267273,0.000013505018,0.0004889402,0.98693585,0.00047510306,0.00615577,0.0031412733],"study_design_scores_gemma":[0.0009720916,0.000452048,0.00048662876,0.000299137,0.0004781463,0.000002953002,0.000006760759,0.004276928,0.8115629,0.00018156046,0.18083829,0.00044254755],"about_ca_topic_score_codex":0.0000012914315,"about_ca_topic_score_gemma":2.2915391e-7,"teacher_disagreement_score":0.17537294,"about_ca_system_score_codex":0.000003168659,"about_ca_system_score_gemma":0.000028976248,"threshold_uncertainty_score":0.39222518},"labels":[],"label_agreement":null},{"id":"W2895157742","doi":"10.1016/j.tcs.2019.08.013","title":"Stochastic chemical reaction networks for robustly approximating arbitrary probability distributions","year":2019,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"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":"Army Research Office; National Science Foundation; European Research Council; Banff International Research Station for Mathematical Innovation and Discovery; European Commission; American Institute of Mathematics","keywords":"Ergodic theory; Mathematics; Limit (mathematics); Probability distribution; Probability mass function; Lattice (music); Applied mathematics; Statistical physics; Discrete mathematics; Pure mathematics; Mathematical analysis; Statistics; Physics","score_opus":0.007422290535116712,"score_gpt":0.2276371222684539,"score_spread":0.2202148317333372,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2895157742","genre_codex":"methods","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":[0.44270277,0.000019031822,0.5567734,0.00005264188,0.00011205196,0.00023371384,0.000002950121,0.000017283443,0.000086131346],"genre_scores_gemma":[0.95568216,7.5287414e-7,0.043836474,0.000065539396,0.00030937087,0.000027523287,0.000060917933,0.000010202482,0.000007057613],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99845827,0.000047518795,0.00024011756,0.0006284653,0.00020889762,0.00041675995],"domain_scores_gemma":[0.9990264,0.000059882204,0.00007396593,0.00052983937,0.00016465399,0.00014524278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008925503,0.00014257879,0.00017025988,0.000031097105,0.00017812823,0.00005926268,0.0004167181,0.00010119202,0.000010017212],"category_scores_gemma":[0.000111887915,0.00012720872,0.00012541171,0.0003219502,0.0009501654,0.000010843079,0.00026107483,0.0001148426,0.0000061567407],"study_design_candidate":"simulation_or_modeling","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":[0.0001833482,0.00025978452,0.0005670811,0.000057602905,0.00006877398,5.036173e-7,0.00004342651,0.11719556,0.40717015,0.46206078,0.00014989723,0.012243088],"study_design_scores_gemma":[0.00023272693,0.00016275668,0.00041103453,0.000015275715,0.000029069828,0.000012595876,0.000004017673,0.95736253,0.021996886,0.019518746,0.00004242229,0.00021193808],"about_ca_topic_score_codex":5.199013e-7,"about_ca_topic_score_gemma":2.2575105e-7,"teacher_disagreement_score":0.840167,"about_ca_system_score_codex":0.00004367533,"about_ca_system_score_gemma":0.00008275278,"threshold_uncertainty_score":0.51874214},"labels":[],"label_agreement":null},{"id":"W2896701276","doi":"10.1007/978-1-4939-8772-6_11","title":"LiveFly: A Toolbox for the Analysis of Transcription Dynamics in Live Drosophila Embryos","year":2018,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Agence Nationale de la Recherche","keywords":"Toolbox; Drosophila (subgenus); Dynamics (music); Embryo; Biology; Cell biology; Computational biology; Genetics; Computer science; Sociology; Gene","score_opus":0.017636783070100144,"score_gpt":0.35410299957860225,"score_spread":0.3364662165085021,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2896701276","genre_codex":"methods","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":[0.32511353,0.0013442903,0.6728963,0.0001373366,0.00010557628,0.00028107633,0.000024564753,0.000003970687,0.0000933297],"genre_scores_gemma":[0.8029955,0.00014426802,0.19616982,0.00022615094,0.00008818876,0.000105615174,0.00018225575,0.000023322287,0.00006489535],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9977401,0.00086143933,0.00048929366,0.0005130331,0.00006866041,0.00032748646],"domain_scores_gemma":[0.9988898,0.00014057456,0.0001670717,0.00062181463,0.00014414988,0.000036608173],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016259588,0.00019441031,0.0004808293,0.0003880475,0.000046875888,0.000007461242,0.00037837724,0.00033419198,0.000019710473],"category_scores_gemma":[0.00027727432,0.00016159311,0.0004311938,0.0010497159,0.0003453688,0.000002094844,0.00006926177,0.000108899556,8.35303e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015002732,0.00006885223,0.0102103455,0.000011960328,0.0010271147,0.0000013662519,0.00013720054,0.0032131055,0.9728951,0.0014690651,0.000011673225,0.010804181],"study_design_scores_gemma":[0.0018808463,0.0012953978,0.03271198,0.00002796415,0.0028249524,0.0000076199567,0.0008122294,0.34179384,0.60792464,0.006538453,0.0034085112,0.0007735821],"about_ca_topic_score_codex":0.00012080833,"about_ca_topic_score_gemma":0.002106253,"teacher_disagreement_score":0.47788197,"about_ca_system_score_codex":0.000055852768,"about_ca_system_score_gemma":0.000051880375,"threshold_uncertainty_score":0.6589576},"labels":[],"label_agreement":null},{"id":"W2896963233","doi":"10.1073/pnas.1810858115","title":"Multiscale effects of heating and cooling on genes and gene networks","year":2018,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":57,"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":"Laufer Center for Physical and Quantitative Biology, Stony Brook University; National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; Government of Canada; National Institutes of Health; National Science Foundation","keywords":"Gene; Gene regulatory network; Gene expression; Biology; TetR; Saccharomyces cerevisiae; Cell biology; Population; Regulation of gene expression; Genetics; Computational biology; Repressor","score_opus":0.013091050120920036,"score_gpt":0.2684895944656512,"score_spread":0.25539854434473114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2896963233","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":[0.99834913,0.0013458782,0.00001293953,0.000085546744,0.0000094057605,0.00006640116,0.0000011248997,0.000001279484,0.00012829866],"genre_scores_gemma":[0.99807,0.00016952805,0.0015166712,0.00006900726,0.00014761821,0.0000020628747,1.13546086e-7,0.0000026456291,0.000022359169],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993511,0.000005632991,0.00014611048,0.00017302069,0.00024156527,0.0000825706],"domain_scores_gemma":[0.9996071,0.000036063357,0.00019349015,0.000007264205,0.00013433947,0.000021778704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042982592,0.00005850028,0.00009885889,0.000045031964,0.00011267908,0.0000065928393,0.00016166312,0.00006432572,5.1660675e-7],"category_scores_gemma":[0.00013900563,0.00004119499,0.00003073095,0.00018334905,0.0007138504,0.0000070888727,0.000115455754,0.00003539262,3.3743063e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013749718,0.000010408837,0.018907942,0.00003574618,0.000021477214,9.542065e-10,0.000028155246,0.0006956158,0.9785304,0.00033304692,0.000042396223,0.0013810329],"study_design_scores_gemma":[0.00010943278,0.0001248092,0.062082328,0.00005169301,0.000015619915,0.0000025841487,0.000019227835,0.011099902,0.92593086,0.00049489527,0.000025726165,0.000042934495],"about_ca_topic_score_codex":0.000002328992,"about_ca_topic_score_gemma":1.1431973e-7,"teacher_disagreement_score":0.052599583,"about_ca_system_score_codex":0.000002830998,"about_ca_system_score_gemma":0.0000070370606,"threshold_uncertainty_score":0.26302114},"labels":[],"label_agreement":null},{"id":"W2898707893","doi":"10.11145/bmc.2018.10.277","title":"The Mackey-Glass models, 40 years later","year":2018,"lang":"en","type":"article","venue":"Biomath Communications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"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 Lethbridge","funders":"","keywords":"Context (archaeology); Perspective (graphical); Citation; Applied mathematics; Computer science; Mathematics; Epistemology; Mathematics education; History; Philosophy; Artificial intelligence; Library science","score_opus":0.023662355002872754,"score_gpt":0.27126990330400647,"score_spread":0.2476075483011337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2898707893","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":[0.97339284,0.008663346,0.0020985794,0.0028401664,0.00022126174,0.00025896015,0.000026555608,0.00006436442,0.012433909],"genre_scores_gemma":[0.9945638,0.0009905698,0.0026462495,0.00014658054,0.00018523005,0.000027124817,0.000098145254,0.000017513925,0.0013247443],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993265,0.00010359178,0.00015560446,0.0001539292,0.00008593859,0.0001744167],"domain_scores_gemma":[0.9974017,0.00001810668,0.00006292976,0.0023586724,0.00010916501,0.00004940988],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001970618,0.000084117666,0.00006685901,0.00002410783,0.00042451458,0.000044540528,0.00097418646,0.000079079866,0.000008630025],"category_scores_gemma":[0.000014916341,0.000067261,0.000085853295,0.00014631143,0.00037917058,0.0000030809017,0.00052483584,0.00004188718,0.000103332335],"study_design_candidate":"not_applicable","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":[0.00020754024,0.0006246868,0.012241643,0.000018602284,0.0020805458,0.000002718524,0.001200041,0.00053214096,0.57600933,0.03415816,0.27811372,0.09481086],"study_design_scores_gemma":[0.00019513081,0.00006179689,0.009580379,0.0000060088632,0.000055930846,0.0000081461185,0.000078058816,0.010983395,0.008915464,0.0014400597,0.9684757,0.00019992559],"about_ca_topic_score_codex":0.000016361726,"about_ca_topic_score_gemma":0.0004696663,"teacher_disagreement_score":0.690362,"about_ca_system_score_codex":0.000011290117,"about_ca_system_score_gemma":0.000040573734,"threshold_uncertainty_score":0.32650658},"labels":[],"label_agreement":null},{"id":"W2899545492","doi":"10.1093/bioinformatics/bty908","title":"BiXGBoost: a scalable, flexible boosting-based method for reconstructing gene regulatory networks","year":2018,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":86,"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 Saskatchewan","funders":"Higher Education Discipline Innovation Project; National Natural Science Foundation of China","keywords":"Computer science; Scalability; Gene regulatory network; Inference; Data mining; Python (programming language); Boosting (machine learning); Machine learning; Artificial intelligence; Gene; Gene expression; Biology; Database","score_opus":0.014920243380440353,"score_gpt":0.2667671860171329,"score_spread":0.25184694263669255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2899545492","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.062402856,0.00044017137,0.934535,0.00005994718,0.00041507804,0.0004380206,0.000027266387,0.00008133576,0.001600288],"genre_scores_gemma":[0.2170135,0.000023444923,0.77932614,0.0009170726,0.0015147248,0.00005595378,0.00032170885,0.00006808423,0.0007593977],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99819195,0.000059933678,0.00064416736,0.000337707,0.00019009366,0.00057617325],"domain_scores_gemma":[0.99824846,0.000059740018,0.00038753625,0.0007724138,0.0003559846,0.00017587095],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00089637906,0.00029183127,0.0003148099,0.00013096977,0.00035368945,0.0000718683,0.00031746092,0.0003194904,0.00003155344],"category_scores_gemma":[0.00017096633,0.00028910986,0.00026430227,0.00033157755,0.00018920223,0.000012780164,0.00012547043,0.00009347967,0.000018928049],"study_design_candidate":"simulation_or_modeling","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":[0.0010403802,0.0002493463,0.012461647,0.0006557096,0.0017253052,0.0000038376984,0.0004567701,0.15329252,0.21344085,0.00082792423,0.099892184,0.51595354],"study_design_scores_gemma":[0.00072437356,0.00028288254,0.00021915307,0.00003913285,0.00011809956,0.000026652904,0.00007724243,0.7385625,0.23836562,0.0000663935,0.021125052,0.00039287287],"about_ca_topic_score_codex":0.000004969989,"about_ca_topic_score_gemma":0.000014789154,"teacher_disagreement_score":0.58527,"about_ca_system_score_codex":0.000038665665,"about_ca_system_score_gemma":0.00018117586,"threshold_uncertainty_score":0.99995613},"labels":[],"label_agreement":null},{"id":"W2900555417","doi":"10.1101/472720","title":"Variability of bacterial behavior in the mammalian gut captured using a growth-linked single-cell synthetic gene oscillator","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Medical Research Council; Harvard University; Hansjörg Wyss Institute for Biologically Inspired Engineering, Harvard University; National Science Foundation; Advanced Research Projects Agency; National Health and Medical Research Council; Menzies Foundation","keywords":"Biology; Escherichia coli; Population; Bacterial growth; Gut flora; Bacteria; Cell biology; Biological system; Genetics; Gene; Immunology","score_opus":0.014921231522403988,"score_gpt":0.21441777533209416,"score_spread":0.19949654380969017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2900555417","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":[0.9962662,0.00065300846,0.00093332026,0.00002773313,0.0008668871,0.0009587121,0.00025697722,0.00003053449,0.000006652332],"genre_scores_gemma":[0.99346566,0.0000565771,0.005013306,0.0000568466,0.0011272879,0.00013707421,0.0000068466725,0.00013368827,0.0000026942841],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99558985,0.00085881056,0.0009810004,0.0014271188,0.0004751132,0.0006681212],"domain_scores_gemma":[0.9957594,0.00004362721,0.0007800749,0.0025570237,0.00067001616,0.00018984408],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0016642904,0.00070540834,0.0008088878,0.00022877414,0.00012757986,0.00011477149,0.0011402483,0.001123484,0.00004997848],"category_scores_gemma":[0.0002897959,0.0006611958,0.00045103647,0.00052208523,0.00040015404,0.000009454101,0.0007056249,0.00044603835,0.0000057293355],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000890076,0.00040378977,0.02286827,0.00018249273,0.00011889295,0.000019910402,0.000013956781,0.00018995012,0.9760408,0.000007209377,0.00006534839,3.8667406e-7],"study_design_scores_gemma":[0.0006844801,0.00016753384,0.059832428,0.000100139056,0.0007197036,2.0447192e-7,0.000005906599,0.0003231995,0.93646234,0.0000026259686,0.0008270684,0.00087437633],"about_ca_topic_score_codex":0.00010014694,"about_ca_topic_score_gemma":0.000017721884,"teacher_disagreement_score":0.039578453,"about_ca_system_score_codex":0.00020210388,"about_ca_system_score_gemma":0.00067252485,"threshold_uncertainty_score":0.9995839},"labels":[],"label_agreement":null},{"id":"W2900880986","doi":"10.1016/j.jmb.2018.11.011","title":"Selection of Protein–Protein Interactions of Desired Affinities with a Bandpass Circuit","year":2018,"lang":"en","type":"article","venue":"Journal of Molecular Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Institute of Mental Health; National Institutes of Health","keywords":"Affinities; Biology; Escherichia coli; Selection (genetic algorithm); Protein–protein interaction; Population; Band-pass filter; Computational biology; Genetics; Gene; Biochemistry; Physics; Computer science; Artificial intelligence","score_opus":0.011840917261579069,"score_gpt":0.24987308465013494,"score_spread":0.23803216738855587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2900880986","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":[0.9416407,0.00039327578,0.057460528,0.000057169662,0.000055304765,0.00012826122,0.000004224498,0.0000025446736,0.00025803552],"genre_scores_gemma":[0.99533504,0.000016912652,0.0042902306,0.000026333786,0.00020045844,0.000006751077,0.000008545941,0.000017953047,0.00009778896],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988394,0.00020878152,0.00048595027,0.0001665393,0.00012736868,0.0001719567],"domain_scores_gemma":[0.9981722,0.000009085291,0.00076781044,0.00021209504,0.0007803247,0.000058439546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027230242,0.00013953597,0.0003357219,0.00018989228,0.00003932032,0.0000054524303,0.00019094809,0.0001404065,0.000045997673],"category_scores_gemma":[0.0000834188,0.000112752874,0.00019970519,0.00022729623,0.0002880943,0.0000056041413,0.00004251024,0.00010978685,9.263437e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034780224,0.00008136888,0.0018123462,0.00001927186,0.0005320295,0.000003473209,0.000029975916,0.00009238627,0.99580157,0.00023003467,0.000044471566,0.0010052708],"study_design_scores_gemma":[0.00055205676,0.0027801846,0.00065557536,0.000065252076,0.00011858589,0.00014552355,0.000052184863,0.000024525943,0.9936124,0.0005383455,0.0013442663,0.00011106357],"about_ca_topic_score_codex":0.000010946299,"about_ca_topic_score_gemma":0.00003926986,"teacher_disagreement_score":0.05369437,"about_ca_system_score_codex":0.000018559564,"about_ca_system_score_gemma":0.00018947935,"threshold_uncertainty_score":0.45979285},"labels":[],"label_agreement":null},{"id":"W2904703945","doi":"10.3233/isb-180470","title":"Modeling cell population dynamics","year":2018,"lang":"en","type":"article","venue":"In Silico Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":93,"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 Alberta","funders":"National Institute of General Medical Sciences; National Institutes of Health; Nvidia","keywords":"Population; Mathematical model; Population model; Computer science; Computational model; Systems biology; Simple (philosophy); Dynamics (music); Competition (biology); Artificial intelligence; Ecology; Biology; Computational biology; Mathematics; Statistics; Physics","score_opus":0.00794999312983975,"score_gpt":0.25188861294896825,"score_spread":0.2439386198191285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2904703945","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":[0.99290174,0.000341611,0.0055324496,0.000048461705,0.00014161416,0.000062651656,0.0000041900475,0.000010159371,0.0009571143],"genre_scores_gemma":[0.9984844,0.0000417328,0.0005330251,0.00011579901,0.00036049623,0.000006899517,0.00029364973,0.000013753947,0.00015025445],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991467,0.00007515396,0.00019779145,0.00031804992,0.000035324065,0.00022696846],"domain_scores_gemma":[0.99957293,0.0000044616786,0.000038722435,0.0002974085,0.00004985423,0.000036598838],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001456265,0.00010525621,0.00012853253,0.00007118512,0.000041686188,0.0000054202005,0.00013968095,0.00022357047,0.000018909714],"category_scores_gemma":[0.000021259058,0.000104833234,0.00005942179,0.00013359897,0.000062874205,0.0000015014268,0.000080461425,0.00005380066,0.000021138017],"study_design_candidate":"simulation_or_modeling","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":[0.000082986495,0.000090258385,0.5040627,0.000009988156,0.000044473913,0.0000015164751,0.00004868981,0.03578565,0.45015272,0.0007200079,0.00018219539,0.008818826],"study_design_scores_gemma":[0.0006841947,0.00042555542,0.01605878,0.000007600883,0.000029858858,0.000009498503,0.00007897287,0.9433449,0.03427022,0.0019995584,0.002634955,0.00045592574],"about_ca_topic_score_codex":0.00020155284,"about_ca_topic_score_gemma":0.0021430554,"teacher_disagreement_score":0.9075592,"about_ca_system_score_codex":0.000029600033,"about_ca_system_score_gemma":0.000018562167,"threshold_uncertainty_score":0.4274975},"labels":[],"label_agreement":null},{"id":"W2905233582","doi":"10.4230/lipics.opodis.2018.21","title":"Output-Oblivious Stochastic Chemical Reaction Networks","year":2018,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Function (biology); Combinatorics; Uniqueness; Congruence (geometry); Affine transformation; Order (exchange); Grid; Mathematics; Discrete mathematics; Pure mathematics; Mathematical analysis","score_opus":0.031046018344752433,"score_gpt":0.18053173057150532,"score_spread":0.1494857122267529,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2905233582","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":[0.82089245,0.0002660821,0.17758285,0.000015377864,0.00048565643,0.00018973088,0.000010376887,0.00005627188,0.000501208],"genre_scores_gemma":[0.99581033,0.00018960712,0.00011349126,0.0000612909,0.0012512902,0.0000018434642,0.00042635069,0.00005405033,0.0020917256],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99793065,0.00011060123,0.00021993137,0.0012359341,0.0000778529,0.00042505268],"domain_scores_gemma":[0.99809015,0.000015707305,0.00027194302,0.0011986953,0.00021432269,0.00020917688],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018523092,0.00039631725,0.0003526828,0.00012658021,0.00010829057,0.000034660472,0.00059064664,0.00086653454,0.000029054965],"category_scores_gemma":[0.000039472674,0.0004833327,0.00040810756,0.0002661208,0.00022130339,0.0000047526714,0.001052487,0.00041403325,0.000055937322],"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":[0.0002536899,0.00014010062,0.0015303026,0.000037538357,0.0008219839,0.000048021357,0.000019910545,0.97785306,0.011517813,0.00022907318,0.0069493563,0.0005991239],"study_design_scores_gemma":[0.001978375,0.00042540857,0.002881701,0.0002175976,0.0024616122,0.00005613227,0.0001264973,0.9686201,0.009852464,0.0046107103,0.005743422,0.0030259418],"about_ca_topic_score_codex":0.00003485159,"about_ca_topic_score_gemma":0.00003550401,"teacher_disagreement_score":0.17746936,"about_ca_system_score_codex":0.00012172959,"about_ca_system_score_gemma":0.00012961078,"threshold_uncertainty_score":0.9997618},"labels":[],"label_agreement":null},{"id":"W2908917219","doi":"10.3390/pr7010052","title":"Component Characterization in a Growth-Dependent Physiological Context: Optimal Experimental Design","year":2019,"lang":"en","type":"article","venue":"Processes","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Component (thermodynamics); Context (archaeology); Computer science; Biological system; Optimal design; Genetic algorithm; Schedule; Range (aeronautics); Mathematical optimization; Mathematics; Machine learning; Engineering; Biology","score_opus":0.015172347364217034,"score_gpt":0.23714530476359683,"score_spread":0.22197295739937978,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2908917219","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":[0.99482167,0.0014847975,0.0033415223,0.00003177522,0.000046639085,0.00021947302,0.000004302908,0.000012211496,0.000037581867],"genre_scores_gemma":[0.9989472,0.00017534732,0.0002647629,0.00012278391,0.00008150106,0.00005295251,0.000193009,0.00001366424,0.0001487795],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991626,0.00006046869,0.00016169144,0.0003285293,0.000108998895,0.00017769895],"domain_scores_gemma":[0.9996739,0.0000070823326,0.000068593996,0.00014039093,0.00006985311,0.000040164363],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000868501,0.00012920832,0.00015845343,0.000036045287,0.000026517637,0.000019168861,0.00014071805,0.00008726191,0.00006472257],"category_scores_gemma":[0.000022423263,0.00011629908,0.000040061415,0.00011416999,0.000028685912,0.00000645412,0.00007853219,0.000044786688,0.000034744888],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010637,0.00015460681,0.0074805305,0.00004625954,0.000024798393,0.0000017170522,0.000057075053,0.001333471,0.990588,0.000006992278,0.000035100373,0.00016507083],"study_design_scores_gemma":[0.00051757914,0.00025338295,0.009302056,0.000015702992,0.000008558868,0.0000055050236,0.0001303996,0.00090150756,0.988141,0.000009423522,0.0005253269,0.00018952902],"about_ca_topic_score_codex":0.0000041544836,"about_ca_topic_score_gemma":0.00000288198,"teacher_disagreement_score":0.004125503,"about_ca_system_score_codex":0.000017801527,"about_ca_system_score_gemma":0.00005062772,"threshold_uncertainty_score":0.4742539},"labels":[],"label_agreement":null},{"id":"W2912029926","doi":"10.1007/s12551-019-00499-1","title":"Bayesian statistical learning for big data biology","year":2019,"lang":"en","type":"review","venue":"Biophysical Reviews","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":26,"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; BC Cancer Agency","funders":"Engineering and Physical Sciences Research Council; Medical Research Council; University of Birmingham; Alan Turing Institute","keywords":"Bayesian probability; Bayesian statistics; Statistical inference; Computer science; Bayesian inference; Variable-order Bayesian network; Inference; Probabilistic logic; Machine learning; Statistical model; Molecular cell biology; Artificial intelligence; Mathematics; Statistics; Biology","score_opus":0.1422026910481684,"score_gpt":0.3917441366108956,"score_spread":0.24954144556272717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912029926","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[7.1196206e-7,0.9567231,0.040797897,0.000009486726,0.00051059516,0.0014612378,0.00037959416,0.0000143491125,0.00010305124],"genre_scores_gemma":[0.000011189266,0.97191256,0.001827065,0.000053336058,0.0042271484,0.00024233985,0.020323154,0.00011070378,0.0012924866],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99614537,0.0007009443,0.0009590743,0.0015320056,0.000120372984,0.0005422509],"domain_scores_gemma":[0.9967328,0.00016306003,0.0006015058,0.0022584144,0.000057451376,0.00018680507],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00064797734,0.00064788084,0.0029153966,0.00007457835,0.000092179565,0.000039262562,0.001228118,0.0005855028,0.000026570779],"category_scores_gemma":[0.00067864184,0.0004821918,0.0010630172,0.00026168497,0.00013354023,0.0000027624606,0.00075576344,0.0003232113,0.0003960373],"study_design_candidate":"not_applicable","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":[0.0000055637315,0.000042225096,0.0000017452579,0.00669394,0.0002752583,5.9076586e-7,5.9830666e-7,0.0000014460103,0.00018533795,0.00012380735,0.016130589,0.9765389],"study_design_scores_gemma":[0.00011652064,0.00021493225,4.6317152e-7,0.0011300801,0.0019692236,0.0000050174212,5.9940265e-7,0.00017755498,0.0000062231534,0.000029718127,0.9958213,0.0005283559],"about_ca_topic_score_codex":0.000003431908,"about_ca_topic_score_gemma":0.0000044027324,"teacher_disagreement_score":0.97969073,"about_ca_system_score_codex":0.000030736595,"about_ca_system_score_gemma":0.00029238084,"threshold_uncertainty_score":0.99976295},"labels":[],"label_agreement":null},{"id":"W2912050044","doi":"10.1162/artl_a_00267","title":"Artificial Gene Regulatory Networks—A Review","year":2019,"lang":"en","type":"review","venue":"Artificial Life","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":43,"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; College of Engineering, Michigan State University; Office of Experimental Program to Stimulate Competitive Research; Michigan State University; National Science Foundation","keywords":"Gene regulatory network; Computer science; Key (lock); Mechanism (biology); Biology; Computational biology; Gene; Artificial intelligence; Gene expression; Ecology; Genetics","score_opus":0.04980137574125841,"score_gpt":0.30935252086906745,"score_spread":0.259551145127809,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912050044","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000040127652,0.9966985,0.00054158794,0.00006290437,0.0010522862,0.0011638622,0.00004572207,0.000049201448,0.00034579358],"genre_scores_gemma":[0.00012780652,0.99028337,0.00011832463,0.00084586535,0.0051997267,0.00014093007,0.0019722371,0.00020264726,0.0011090998],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.995216,0.00056683813,0.0016570203,0.0013423264,0.0004514505,0.00076637126],"domain_scores_gemma":[0.99642175,0.000045844838,0.00085571513,0.0021520911,0.0001554671,0.00036914833],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009212465,0.0008521159,0.0025535855,0.00015256353,0.00017655484,0.00006675042,0.00077064184,0.00092668814,0.00020822664],"category_scores_gemma":[0.00020770165,0.00079170335,0.0018995013,0.0006563378,0.00014336221,0.0000054845996,0.00037262434,0.00040872602,0.0009805927],"study_design_candidate":"not_applicable","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":[0.000014754446,0.00007578047,0.0000026029363,0.0072167106,0.000735639,0.000008722807,0.0000018699416,0.00028282046,0.00013878122,0.00018876286,0.04747995,0.9438536],"study_design_scores_gemma":[0.000030902367,0.000070940994,0.0000022608535,0.005340382,0.0028468657,0.000022101713,0.0000019463691,0.00007908278,0.00014738341,0.000025503801,0.9905946,0.0008380028],"about_ca_topic_score_codex":0.00000485353,"about_ca_topic_score_gemma":0.000019864408,"teacher_disagreement_score":0.9431147,"about_ca_system_score_codex":0.000062126426,"about_ca_system_score_gemma":0.0007287222,"threshold_uncertainty_score":0.9997973},"labels":[],"label_agreement":null},{"id":"W2912349718","doi":"10.1007/s11390-019-1896-x","title":"Controllability and Its Applications to Biological Networks","year":2019,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Controllability; Biological network; Computer science; Complex network; Biological data; Network controllability; Systems biology; Complex system; Distributed computing; Artificial intelligence; Bioinformatics; Centrality; Mathematics; Biology","score_opus":0.005921843677497686,"score_gpt":0.23383058211120905,"score_spread":0.22790873843371137,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912349718","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":[0.9510153,0.0014381099,0.04637929,0.00097005646,0.000063835,0.00011348162,2.7823157e-7,0.0000044759645,0.000015198833],"genre_scores_gemma":[0.9965735,0.00015725422,0.0029263454,0.00021676147,0.000113391856,0.0000027730357,2.2267345e-7,0.0000020391556,0.0000076746155],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993679,0.000015019296,0.00016690095,0.00021048594,0.00009403357,0.0001456419],"domain_scores_gemma":[0.99927664,0.000012012765,0.000093042945,0.00017183763,0.0003604116,0.00008607246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049812964,0.00006237493,0.0001553049,0.00015686452,0.000061574014,0.000022052582,0.00026183427,0.00009677305,0.0000017621811],"category_scores_gemma":[0.00003575058,0.00004651352,0.000023681798,0.00047529265,0.0002044756,0.0000058686323,0.00023648038,0.000074710406,0.0000016328488],"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":[0.000068949135,0.00009520128,0.10973082,0.000010531081,0.00010390596,0.00000413458,0.000025969826,0.0040424867,0.6372048,0.0036750005,0.00039452474,0.24464367],"study_design_scores_gemma":[0.0069543864,0.017408721,0.21117178,0.00012533151,0.0002498421,0.0036446052,0.0003519734,0.23098086,0.2190553,0.012113917,0.29582682,0.0021164739],"about_ca_topic_score_codex":1.409993e-7,"about_ca_topic_score_gemma":6.442914e-7,"teacher_disagreement_score":0.4181495,"about_ca_system_score_codex":0.000008289051,"about_ca_system_score_gemma":0.00005953099,"threshold_uncertainty_score":0.18967663},"labels":[],"label_agreement":null},{"id":"W2913074838","doi":"10.1109/cdc.2018.8619098","title":"Dynamic Networks: Representations, Abstractions, and Well-Posedness","year":2018,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"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 Calgary","funders":"","keywords":"Abstraction; Computer science; Realization (probability); Theoretical computer science; Resolution (logic); Nonlinear system; Dynamic network analysis; Distributed computing; Artificial intelligence; Mathematics","score_opus":0.0052343234685975435,"score_gpt":0.25687058797192686,"score_spread":0.2516362645033293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913074838","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":[0.96687454,0.0012757307,0.022600377,0.00023942794,0.00021708463,0.000113016285,0.0000015104687,0.000029529509,0.00864878],"genre_scores_gemma":[0.9919489,0.00038608126,0.0014901343,0.00017043935,0.00026940485,0.0000082905235,0.00006944454,0.000014413285,0.0056428635],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99928886,0.000034174187,0.00014411318,0.00030529252,0.00006811694,0.00015942767],"domain_scores_gemma":[0.99944925,0.0000076048595,0.000048997445,0.00034533313,0.000077319986,0.00007150086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001082553,0.00009734813,0.000082928746,0.000036134836,0.00014075026,0.000029374482,0.00007407775,0.00009344512,0.00018045805],"category_scores_gemma":[0.000011560236,0.000093224866,0.000049000584,0.000095731804,0.00013028446,0.0000034099664,0.00006827458,0.00003992135,0.000046079505],"study_design_candidate":"not_applicable","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":[0.00031495278,0.00049376365,0.1902462,0.00005906871,0.00203222,0.000020266489,0.00023429848,0.027701115,0.48471957,0.0024520266,0.22516555,0.06656097],"study_design_scores_gemma":[0.0021647324,0.0007744515,0.3639824,0.00003006575,0.00053470855,0.00026674534,0.001606872,0.17720276,0.08899653,0.0012241637,0.36141932,0.0017972254],"about_ca_topic_score_codex":0.000023185965,"about_ca_topic_score_gemma":0.00022558702,"teacher_disagreement_score":0.39572304,"about_ca_system_score_codex":0.000007088722,"about_ca_system_score_gemma":0.00001883115,"threshold_uncertainty_score":0.38015997},"labels":[],"label_agreement":null},{"id":"W2914058822","doi":"10.1101/530584","title":"Short-range interactions govern cellular dynamics in microbial multi-genotype systems","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"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":"Eidgenössische Technische Hochschule Zürich; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Interaction network; Spatial ecology; Systems biology; Process (computing); Temporal scales; Scale (ratio); Dynamics (music)","score_opus":0.010885998133917864,"score_gpt":0.21583835615841204,"score_spread":0.20495235802449419,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2914058822","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":[0.9830921,0.0041660722,0.008753662,0.000036344583,0.002548312,0.00087077345,0.00043984025,0.000076803066,0.000016042295],"genre_scores_gemma":[0.9971402,0.00037386033,0.0011868356,0.000050601888,0.00080219,0.00012649615,0.000017216078,0.0001988203,0.000103724014],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99666685,0.00024844418,0.0007383913,0.0013962503,0.0002928783,0.00065719674],"domain_scores_gemma":[0.99704677,0.000017769189,0.00037207126,0.0019843746,0.00037028434,0.00020871866],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00046339838,0.0006872795,0.0007326177,0.00027943964,0.000095462965,0.00017693367,0.00075330323,0.00092799304,0.000014220066],"category_scores_gemma":[0.000067801906,0.0008146775,0.00036840927,0.00039055638,0.000091802176,0.000011691738,0.000789276,0.0007439593,0.00009293395],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004562546,0.00019590161,0.06907271,0.00028163663,0.00041913672,0.00003250084,0.000004138713,0.012801933,0.9167094,0.000032268483,0.00040309035,0.0000016345867],"study_design_scores_gemma":[0.0027542172,0.00021742721,0.17099808,0.0013042463,0.0012302581,3.257693e-7,0.000059568803,0.15941678,0.6247495,5.6839735e-7,0.033768393,0.0055006486],"about_ca_topic_score_codex":0.00021087442,"about_ca_topic_score_gemma":0.00028506224,"teacher_disagreement_score":0.29195994,"about_ca_system_score_codex":0.00073642674,"about_ca_system_score_gemma":0.00042605287,"threshold_uncertainty_score":0.9994304},"labels":[],"label_agreement":null},{"id":"W2914184348","doi":"10.1093/bioinformatics/btz080","title":"ChimeraUGEM: unsupervised gene expression modeling in any given organism","year":2019,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"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":"Azrieli Foundation; Tel Aviv University; Ministry of Science, Technology and Space","keywords":"Organism; Chlamydomonas reinhardtii; Model organism; Gene; Computational biology; Source code; Computer science; Biology; Gene expression; Coding (social sciences); Software; Coding region; Genetics; Programming language","score_opus":0.010676590549476008,"score_gpt":0.21166432740557284,"score_spread":0.20098773685609683,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2914184348","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":[0.9906202,0.00034200915,0.007649002,0.000034643566,0.00009756563,0.00019211369,0.000005625429,0.000016341548,0.0010425055],"genre_scores_gemma":[0.98470396,0.00014352362,0.014338056,0.00015373043,0.000090942405,0.0000059571985,0.00016792223,0.00002314385,0.00037274245],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989831,0.000027471067,0.00036466657,0.0001836592,0.00016634582,0.00027476647],"domain_scores_gemma":[0.9992847,0.000003963618,0.00008238291,0.00050001574,0.000051215313,0.00007775164],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017109924,0.00016460888,0.00018908817,0.00008901865,0.000041124415,0.000025200457,0.000225631,0.00017173306,0.000062348976],"category_scores_gemma":[0.000014287799,0.00015271844,0.00008875956,0.00016756936,0.000015805339,0.000011480537,0.00015546694,0.00008052021,0.00012855645],"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":[0.000040327584,0.00006714364,0.010320871,0.00008007565,0.000064168096,0.0000015835247,0.00044923802,0.08117989,0.90531033,0.000014008495,0.0009358963,0.0015364734],"study_design_scores_gemma":[0.0010578398,0.000115306844,0.0008103151,0.000045999273,0.000026379741,0.000009341361,0.00036975642,0.70990616,0.28435373,0.000050978517,0.0028457623,0.0004084435],"about_ca_topic_score_codex":0.0000065309537,"about_ca_topic_score_gemma":0.0000072320818,"teacher_disagreement_score":0.62872624,"about_ca_system_score_codex":0.000022515072,"about_ca_system_score_gemma":0.000059940445,"threshold_uncertainty_score":0.6227677},"labels":[],"label_agreement":null},{"id":"W2916377258","doi":"10.1515/jib-2018-0013","title":"Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2017","year":2018,"lang":"en","type":"article","venue":"Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"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":"Biotechnology and Biological Sciences Research Council; National Institute of General Medical Sciences; Directorate for Biological Sciences; Bundesministerium für Bildung und Forschung; Klaus Tschira Stiftung; Bundesministerium für Wirtschaft und Energie; National Science Foundation","keywords":"Computer science; Dissemination; Synthetic biology; Data science; Engineering management; Biology; Telecommunications; Computational biology; Engineering","score_opus":0.02016615640410648,"score_gpt":0.29376194636233943,"score_spread":0.27359578995823297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916377258","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":[0.97206134,0.006015703,0.011288055,0.00007718684,0.00043184185,0.0006948323,0.00019632952,0.000011344722,0.00922338],"genre_scores_gemma":[0.9729317,0.003679691,0.023060754,0.00009834007,0.00008106862,0.000013979912,0.00008386079,0.000017320035,0.000033293363],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9959959,0.0000979812,0.0027238624,0.0001505765,0.00051624456,0.000515467],"domain_scores_gemma":[0.9961765,0.000094201234,0.0018741529,0.00036582982,0.0012343351,0.00025499612],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0016543646,0.0004240438,0.0008190899,0.0009349197,0.000093736504,0.00010064972,0.00039026092,0.00029958002,0.000009559591],"category_scores_gemma":[0.00059050875,0.00030659031,0.00010108691,0.00074428436,0.0007933525,0.00026715492,0.00024051263,0.00032359772,0.000005520253],"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":[0.0037106439,0.0010499972,0.49936172,0.004514353,0.007491821,0.000033248187,0.23759395,0.0017361753,0.016898468,0.017821385,0.013383722,0.19640452],"study_design_scores_gemma":[0.021995705,0.011345899,0.21345595,0.006088656,0.0012869927,0.0018742295,0.19816361,0.07683627,0.06708687,0.00084873114,0.39598298,0.0050341175],"about_ca_topic_score_codex":0.00003249812,"about_ca_topic_score_gemma":0.00011807174,"teacher_disagreement_score":0.38259926,"about_ca_system_score_codex":0.00013040342,"about_ca_system_score_gemma":0.000756199,"threshold_uncertainty_score":0.9999386},"labels":[],"label_agreement":null},{"id":"W2916962794","doi":"10.1021/acs.jpcb.8b10974","title":"<i>In Silico</i> Evolution of Biochemical Log-Response","year":2019,"lang":"en","type":"article","venue":"The Journal of Physical Chemistry B","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Canada Foundation for Innovation; Simons Foundation","keywords":"In silico; Computational biology; Biology; Computer science; Genetics; Gene","score_opus":0.003182215958352463,"score_gpt":0.21947727230015204,"score_spread":0.21629505634179957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916962794","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":[0.9989376,0.0005985626,0.00008416285,0.00015948174,0.000025493722,0.000040526378,0.0000025586983,0.000001166491,0.00015046659],"genre_scores_gemma":[0.99927115,0.00001602421,0.000023505158,0.00002553168,0.0003489653,5.6790066e-7,0.0000022458057,0.000010629369,0.0003013503],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99912125,0.00010657175,0.00029203686,0.000112413574,0.000215351,0.00015239495],"domain_scores_gemma":[0.99916506,0.000065816224,0.00026931055,0.00032753308,0.00011446357,0.00005780556],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046524915,0.00011284006,0.00024125939,0.000019760617,0.00001278194,0.0000031937252,0.0003262365,0.00008875731,0.000027274122],"category_scores_gemma":[0.00008005253,0.000080427635,0.00023192792,0.0001629732,0.000103963415,0.0000044485155,0.00007763654,0.0001644147,0.0000062750864],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008645001,0.00012025294,0.0007109821,0.00002231529,0.00005979994,0.0000011630916,0.000032686694,0.0032945883,0.99412173,0.0000047059493,0.0007400632,0.000027241647],"study_design_scores_gemma":[0.00047246247,0.0001522986,0.0012581738,0.000022475067,0.000055294724,0.000035653757,0.0000822801,0.00052749104,0.996492,0.00013130397,0.00068483007,0.00008570339],"about_ca_topic_score_codex":0.0000028300005,"about_ca_topic_score_gemma":2.746777e-7,"teacher_disagreement_score":0.0027670972,"about_ca_system_score_codex":0.000041180614,"about_ca_system_score_gemma":0.000103496415,"threshold_uncertainty_score":0.32797438},"labels":[],"label_agreement":null},{"id":"W2920436315","doi":"10.1101/564419","title":"Metabolic Cost of Rapid Adaptation of Single Yeast Cells","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"York University; National Science Foundation","keywords":"Adaptation (eye); Metabolic adaptation; Metabolic network; Coupling (piping); Metabolic pathway; Cellular adaptation; Saccharomyces cerevisiae; Yeast","score_opus":0.01361184613585883,"score_gpt":0.2057099550565301,"score_spread":0.19209810892067128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2920436315","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":[0.9866586,0.005858119,0.005851063,0.000015740794,0.00058637076,0.0005839181,0.00040271005,0.000027681685,0.000015838514],"genre_scores_gemma":[0.9960557,0.00077653787,0.0026801003,0.00003072426,0.00029387462,0.00004272299,0.0000037840614,0.00009870544,0.00001785348],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9977611,0.0001703431,0.00065348257,0.00074669614,0.00033376776,0.00033464626],"domain_scores_gemma":[0.99672735,0.000013669859,0.0009015658,0.0015463104,0.0006800499,0.00013105974],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00039761869,0.00041240553,0.00073218986,0.00018279065,0.000040627852,0.00003137207,0.00050085,0.0005701054,0.000031183674],"category_scores_gemma":[0.00006518668,0.0004641641,0.00037525175,0.0003399002,0.00014105343,0.000004978551,0.0004112395,0.00020167606,0.000010713687],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034925324,0.00014985388,0.0015897125,0.00024330785,0.0004664371,0.0000012425671,0.000004838948,0.014551996,0.98271024,0.000026298789,0.00020811032,0.00001305137],"study_design_scores_gemma":[0.00037435748,0.00009728254,0.007169776,0.0001054044,0.00034217685,6.105967e-9,0.0000055853498,0.0009159296,0.9842032,3.7234366e-7,0.0063832956,0.00040261776],"about_ca_topic_score_codex":0.000044753473,"about_ca_topic_score_gemma":0.0000059537933,"teacher_disagreement_score":0.013636067,"about_ca_system_score_codex":0.00003690438,"about_ca_system_score_gemma":0.00043916513,"threshold_uncertainty_score":0.999781},"labels":[],"label_agreement":null},{"id":"W2922426772","doi":"10.1101/580563","title":"Metabolic activity affects response of single cells to a nutrient switch in structured populations","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"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":"","keywords":"Nutrient; Phenotype; Biology; Cell biology; Metabolism; Biochemistry; Ecology; Gene","score_opus":0.012676261403544472,"score_gpt":0.23026725001050566,"score_spread":0.2175909886069612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2922426772","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":[0.9945943,0.0011681879,0.0023387177,0.00007008578,0.000645412,0.00097323186,0.00017359958,0.00003475393,0.0000017136526],"genre_scores_gemma":[0.99625,0.000060846523,0.003203868,0.00005828475,0.00020896306,0.00009919863,0.0000014429104,0.000105884115,0.000011550021],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9970578,0.0005003348,0.00046339113,0.0011172036,0.00035229675,0.000508982],"domain_scores_gemma":[0.99701405,0.000033502296,0.00046516376,0.0019496022,0.00030113416,0.00023653886],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007304187,0.0005183017,0.00079266744,0.0004859996,0.000054141867,0.000053783453,0.00052794017,0.00067314896,0.000011597559],"category_scores_gemma":[0.00022152814,0.00058704725,0.00029712464,0.0008081504,0.00005940282,0.0000077027125,0.00069247157,0.00032307568,0.000011898651],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041231516,0.00018954462,0.012245133,0.00010946073,0.00016807318,0.0000054507414,0.000007989085,0.013955258,0.97272587,0.0000297173,0.00014936525,0.000001846337],"study_design_scores_gemma":[0.00035714675,0.00009644128,0.23909414,0.000087121574,0.00011189371,7.75156e-9,0.0000013761593,0.00019599953,0.75839555,9.885731e-7,0.001234793,0.00042455108],"about_ca_topic_score_codex":0.000052401178,"about_ca_topic_score_gemma":0.000039510425,"teacher_disagreement_score":0.226849,"about_ca_system_score_codex":0.00014692053,"about_ca_system_score_gemma":0.0005326719,"threshold_uncertainty_score":0.9996581},"labels":[],"label_agreement":null},{"id":"W2927621939","doi":"10.1063/1.5079941","title":"Chaos in a ring circuit","year":2019,"lang":"en","type":"article","venue":"Chaos An Interdisciplinary Journal of Nonlinear Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Randomness; Attractor; Chaotic; Computer science; Invariant (physics); Ring (chemistry); Noise (video); State space; Generator (circuit theory); Physical system; Transfer function; Topology (electrical circuits); Theoretical computer science; Mathematics; Physics; Mathematical analysis; Artificial intelligence; Power (physics); Engineering","score_opus":0.013440266906708605,"score_gpt":0.30092696732686164,"score_spread":0.287486700420153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2927621939","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":[0.99789286,0.0003041959,0.0005863028,0.00011065769,0.00038158428,0.000082638835,0.00000188738,0.0000031107365,0.0006367892],"genre_scores_gemma":[0.9981047,0.00003346381,0.0011303963,0.000049844286,0.00045979786,0.00000117883,0.0000032849891,0.000015236094,0.00020209413],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984374,0.000048485643,0.00045552143,0.00035455762,0.00037010724,0.00033391215],"domain_scores_gemma":[0.998844,0.000008123296,0.0002776958,0.00044600805,0.00023611619,0.00018802582],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011476127,0.00014483239,0.00024857646,0.00035256735,0.000116658004,0.000054730546,0.0008680856,0.00007347394,0.00005745902],"category_scores_gemma":[0.00003202003,0.0001253919,0.00015366326,0.0005296241,0.00022537129,0.00004887383,0.00057596545,0.0001944083,0.000023718987],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012619986,0.00023471203,0.034519523,0.000020375768,0.000038507773,0.00005369425,0.00095823425,0.007797749,0.9503364,0.00004738209,0.00005270602,0.005814532],"study_design_scores_gemma":[0.006546397,0.010676549,0.29630283,0.0011734817,0.00016471026,0.0039237477,0.0115343155,0.17480257,0.48449528,0.002250251,0.005617628,0.0025122326],"about_ca_topic_score_codex":0.0000016481044,"about_ca_topic_score_gemma":0.000020401361,"teacher_disagreement_score":0.46584108,"about_ca_system_score_codex":0.00006278207,"about_ca_system_score_gemma":0.000265997,"threshold_uncertainty_score":0.51133335},"labels":[],"label_agreement":null},{"id":"W2937533000","doi":"","title":"Towards a Boolean dynamical system representation in a nonmonotonic modal logic","year":2018,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Compute Canada","funders":"","keywords":"Rotation formalisms in three dimensions; Representation (politics); Dynamical systems theory; Boolean function; Modal logic; And-inverter graph; Computer science; Context (archaeology); Theoretical computer science; Mathematics; Boolean circuit; Modal; Discrete mathematics; Physics","score_opus":0.011548488812132784,"score_gpt":0.2431593640870352,"score_spread":0.23161087527490243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2937533000","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":[0.87892026,0.0011526435,0.10311807,0.0014748764,0.00019191254,0.00054045825,0.000038358838,0.00008914244,0.014474284],"genre_scores_gemma":[0.98262894,0.00027120608,0.013832785,0.000042073923,0.000084721396,0.00011476059,0.001260948,0.00005131316,0.0017132782],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99378574,0.0037602081,0.00060002744,0.0011270246,0.00034090795,0.00038609802],"domain_scores_gemma":[0.9959363,0.00008861153,0.00043506938,0.0023792952,0.0010078053,0.00015295352],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0029593173,0.00034917626,0.00042812814,0.00019528932,0.00014080225,0.00016022875,0.0009840528,0.0005577117,0.000034227778],"category_scores_gemma":[0.0004546042,0.00038386896,0.00032846592,0.0003365231,0.00022568386,0.000007405306,0.0015622681,0.00038296505,0.000027624106],"study_design_candidate":"simulation_or_modeling","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":[0.0011272125,0.007158878,0.1729409,0.0041325497,0.0046281684,0.00022397138,0.019402837,0.05984473,0.4248203,0.12100719,0.013407463,0.17130582],"study_design_scores_gemma":[0.0026037223,0.0000066196335,0.05143139,0.0032931839,0.0004031057,0.00008351597,0.0006617577,0.65442973,0.27399114,0.005121434,0.0056835962,0.0022908389],"about_ca_topic_score_codex":0.00087900314,"about_ca_topic_score_gemma":0.0030385864,"teacher_disagreement_score":0.594585,"about_ca_system_score_codex":0.00020793937,"about_ca_system_score_gemma":0.00034334895,"threshold_uncertainty_score":0.9998613},"labels":[],"label_agreement":null},{"id":"W2941073901","doi":"10.1038/s41467-019-09521-2","title":"Bacterial chemotaxis in a microfluidic T-maze reveals strong phenotypic heterogeneity in chemotactic sensitivity","year":2019,"lang":"en","type":"article","venue":"Nature Communications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":103,"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 Chemical, Bioengineering, Environmental, and Transport Systems; Natural Sciences and Engineering Research Council of Canada; Gordon and Betty Moore Foundation; Simons Foundation; National Science Foundation","keywords":"Chemotaxis; Context (archaeology); Biology; Microscale chemistry; Population; Sensitivity (control systems); Microfluidics; Microorganism; Biological system; Ecology; Evolutionary biology; Bacteria; Genetics; Nanotechnology; Mathematics","score_opus":0.010542942969462303,"score_gpt":0.26806660332644017,"score_spread":0.2575236603569779,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2941073901","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":[0.9917989,0.0068023945,0.000026305543,0.0005389716,0.00010453174,0.00030524662,0.000016508604,0.000011459716,0.0003957114],"genre_scores_gemma":[0.9977948,0.0006077989,0.0008107239,0.00019995144,0.0000802243,0.00002068287,0.00037200417,0.000024917115,0.00008891522],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.998474,0.00042893057,0.00031044535,0.0003933473,0.00011468505,0.00027857046],"domain_scores_gemma":[0.99763405,0.00006017453,0.00012484322,0.0020399475,0.00008052395,0.00006044591],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005459019,0.00018741257,0.00028218562,0.000116464915,0.000048927486,0.000023018038,0.0005368833,0.00046266828,0.000020303649],"category_scores_gemma":[0.00012993236,0.00020921795,0.00012832228,0.00039205587,0.00007429368,0.000009398529,0.0004676747,0.000572443,0.000027219647],"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":[0.00004276904,0.00013753431,0.14019294,0.000012093789,0.000048988317,0.0000010830862,0.000035542143,0.000061752005,0.8585708,0.000068040514,0.00039512684,0.0004333223],"study_design_scores_gemma":[0.0019331566,0.00008471539,0.6890908,0.000081214224,0.000067134155,0.000028085693,0.000101148646,0.0011280505,0.27684435,0.00007902843,0.029883347,0.00067897665],"about_ca_topic_score_codex":0.00006942725,"about_ca_topic_score_gemma":0.0026360953,"teacher_disagreement_score":0.5817265,"about_ca_system_score_codex":0.00009591302,"about_ca_system_score_gemma":0.000088734625,"threshold_uncertainty_score":0.85316604},"labels":[],"label_agreement":null},{"id":"W2943032484","doi":"","title":"On the fate of perturbations in critical random Boolean networks","year":2009,"lang":"en","type":"article","venue":"IRIS UNIMORE (University of Modena and Reggio Emilia)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Boolean network; Boolean function; Algorithm","score_opus":0.011310904342289369,"score_gpt":0.22277884469592213,"score_spread":0.21146794035363276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2943032484","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":[0.9883527,0.0008298926,0.007954787,0.0018475208,0.000016554413,0.000084249565,0.0000047130034,0.0000038625903,0.00090569805],"genre_scores_gemma":[0.99864775,0.0005902422,0.00017131801,0.00010569748,0.000023767137,1.316663e-7,0.000014753169,0.000004319717,0.00044202124],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993848,0.000087049615,0.000100716396,0.00019407528,0.00009928394,0.0001340838],"domain_scores_gemma":[0.9995007,0.000055941404,0.00005528841,0.00026972374,0.00006724785,0.00005110933],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001512989,0.0000900714,0.00017930666,0.000066584,0.00009301193,0.0000037387522,0.000167113,0.00012049648,0.00001420012],"category_scores_gemma":[0.000041891435,0.00007920679,0.00011294552,0.00014694018,0.000252591,0.0000044649646,0.000046635363,0.000088031724,3.8209936e-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":[0.0069194655,0.0018918822,0.023279678,0.00019800558,0.0013158357,0.00014277957,0.005215135,0.4021251,0.3362854,0.0626064,0.10129317,0.05872714],"study_design_scores_gemma":[0.0134764165,0.0030397559,0.16962615,0.000662469,0.0011292087,0.00004838813,0.00918268,0.7575414,0.014496382,0.017556492,0.011429448,0.0018111952],"about_ca_topic_score_codex":0.000031786814,"about_ca_topic_score_gemma":0.000074569536,"teacher_disagreement_score":0.35541633,"about_ca_system_score_codex":0.000008270678,"about_ca_system_score_gemma":0.000022361566,"threshold_uncertainty_score":0.3229959},"labels":[],"label_agreement":null},{"id":"W2946183952","doi":"","title":"Noisy random boolean networks and cell differentiation","year":2010,"lang":"en","type":"article","venue":"Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Calgary","funders":"","keywords":"Computer science; Boolean network; Boolean function; And-inverter graph; Boolean circuit; Theoretical computer science; Algorithm","score_opus":0.005188307607250975,"score_gpt":0.18992525234804045,"score_spread":0.18473694474078947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2946183952","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":[0.9739727,0.00047867597,0.010635331,0.00023939997,0.00037321865,0.00025394844,0.000033153527,0.00004009543,0.013973508],"genre_scores_gemma":[0.98336023,0.0005460127,0.00053156976,0.00013817623,0.00033960864,0.000009107459,0.00035879566,0.000036802834,0.014679683],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99821335,0.00012738135,0.0002471676,0.00069556537,0.00021902924,0.0004975141],"domain_scores_gemma":[0.99900216,0.00004401892,0.00015473196,0.0005013624,0.00009907772,0.00019863332],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018854026,0.0003426197,0.00033777967,0.00014337765,0.00041667803,0.000049893402,0.00034731807,0.00020859038,0.00006363722],"category_scores_gemma":[0.000013107175,0.00034076627,0.00018878123,0.00015421676,0.00028712492,0.00001571483,0.0005492231,0.0002654964,0.000024677545],"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":[0.001167497,0.00060084806,0.21759164,0.000114886476,0.0012655437,0.00012165437,0.00034382215,0.010957564,0.7449303,0.007980363,0.011752297,0.003173528],"study_design_scores_gemma":[0.015229341,0.0009564367,0.6493102,0.00007580281,0.0021914826,0.00029698943,0.00082526874,0.032498553,0.069847226,0.0005666313,0.22452587,0.0036762655],"about_ca_topic_score_codex":0.000011372671,"about_ca_topic_score_gemma":0.00022897517,"teacher_disagreement_score":0.6750831,"about_ca_system_score_codex":0.000020957103,"about_ca_system_score_gemma":0.000049503207,"threshold_uncertainty_score":0.99990445},"labels":[],"label_agreement":null},{"id":"W2946233355","doi":"10.1504/ijdmb.2019.099714","title":"Effective induction of gene regulatory networks using a novel recommendation method","year":2019,"lang":"en","type":"article","venue":"International Journal of Data Mining and Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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 Calgary","funders":"Türkiye Bilimsel ve Teknolojik Araştırma Kurumu","keywords":"Computer science; Data mining; Inference; Set (abstract data type); Receiver operating characteristic; Gene regulatory network; Data set; In silico; Precision and recall; Measure (data warehouse); Collaborative filtering; Machine learning; Artificial intelligence; Gene; Recommender system; Biology; Genetics","score_opus":0.028468735948894958,"score_gpt":0.31662038653124835,"score_spread":0.28815165058235337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2946233355","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":[0.6224362,0.00013963596,0.376903,0.000031983574,0.00035522095,0.0000512203,0.000035051933,0.0000012529908,0.000046438297],"genre_scores_gemma":[0.6140057,0.00009005385,0.3852705,0.000043998247,0.00029685145,2.6142382e-7,0.00027514427,0.0000066045623,0.000010890534],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991135,0.000041260733,0.00047741082,0.00009971457,0.00019007707,0.00007805401],"domain_scores_gemma":[0.99865323,0.00003561185,0.0007470602,0.00020788358,0.00031769133,0.000038536513],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008579244,0.000086521475,0.00016521056,0.00013400204,0.000021484682,0.00002604345,0.0002876139,0.00008798116,0.000008809964],"category_scores_gemma":[0.000064975335,0.00007626042,0.000056076162,0.00007597454,0.000027909844,0.00006313335,0.00018008378,0.00006892771,2.6094605e-7],"study_design_candidate":"simulation_or_modeling","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":[0.00026333125,0.00008176952,0.007243915,0.000034873534,0.0013270802,8.622097e-7,0.00029009406,0.012942271,0.2691423,0.000011327391,0.0006061386,0.70805603],"study_design_scores_gemma":[0.001768387,0.0004048743,0.005710371,0.00020607485,0.0002577341,0.0007011971,0.0010182237,0.9406303,0.046549667,0.000009522332,0.0024950823,0.00024853478],"about_ca_topic_score_codex":0.0000036935685,"about_ca_topic_score_gemma":0.0000017546212,"teacher_disagreement_score":0.92768806,"about_ca_system_score_codex":0.0000214617,"about_ca_system_score_gemma":0.000050390183,"threshold_uncertainty_score":0.31098098},"labels":[],"label_agreement":null},{"id":"W2948932325","doi":"","title":"Timing of molecular processes in a synchronous Boolean model of genetic regulatory network","year":2009,"lang":"en","type":"article","venue":"IRIS UNIMORE (University of Modena and Reggio Emilia)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Calgary","funders":"","keywords":"Computer science; Gene regulatory network; Boolean network; Theoretical computer science; Computational biology; Boolean function; Gene; Biology; Genetics; Algorithm; Gene expression","score_opus":0.008769799058166912,"score_gpt":0.19561286466719813,"score_spread":0.18684306560903122,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2948932325","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":[0.98359734,0.00483833,0.011090685,0.00006855298,0.000008361403,0.00011870819,0.00000643101,0.0000058140413,0.00026576396],"genre_scores_gemma":[0.99284285,0.0010872254,0.0058258027,0.000022170849,0.000019067893,1.8954736e-7,0.000015321222,0.000011506472,0.00017587368],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99901646,0.000042343745,0.0002238675,0.0003275064,0.00017164597,0.00021816246],"domain_scores_gemma":[0.9991473,0.000007352823,0.00022944306,0.00039520775,0.00014325866,0.00007746532],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012833193,0.00015511534,0.00036906355,0.0001298895,0.000049040835,0.0000023315292,0.0002499658,0.00018903289,0.0000028254601],"category_scores_gemma":[0.000011146934,0.00018622841,0.00012699548,0.00029219722,0.0002534365,0.000008499636,0.00010108496,0.00007001207,1.2738533e-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":[0.00022804711,0.00013955435,0.008188518,0.00025508256,0.00015837754,0.000017003063,0.0005872109,0.63486964,0.34909016,0.00008586119,0.00051199953,0.0058685844],"study_design_scores_gemma":[0.005548021,0.0020230499,0.10004639,0.0012448684,0.001268858,0.000054453743,0.0028209514,0.68906254,0.19061679,0.0049815737,0.0005299085,0.001802617],"about_ca_topic_score_codex":0.000047150814,"about_ca_topic_score_gemma":0.00009539479,"teacher_disagreement_score":0.15847337,"about_ca_system_score_codex":0.000016647557,"about_ca_system_score_gemma":0.000151409,"threshold_uncertainty_score":0.7594174},"labels":[],"label_agreement":null},{"id":"W2950018839","doi":"10.26717/bjstr.2019.16.002891","title":"Oscillations in Biological Systems: Psychopathological Associations","year":2019,"lang":"en","type":"article","venue":"Biomedical Journal of Scientific & Technical Research","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Flor; Medicine; Psychiatry; Gerontology; Psychology; History; Archaeology","score_opus":0.06828218677290747,"score_gpt":0.38216517183838555,"score_spread":0.31388298506547807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950018839","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":[0.99600554,0.0010817358,0.00072694506,0.00071066787,0.0006014537,0.00024288254,0.000014934826,0.000008721988,0.00060711993],"genre_scores_gemma":[0.99802303,0.00014254969,0.0008378652,0.000021814001,0.00031159513,0.000008858258,0.000041927466,0.000009521339,0.00060283433],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99598354,0.00068582525,0.0008095259,0.00046549604,0.0015028479,0.00055274775],"domain_scores_gemma":[0.9980364,0.00021861342,0.00020520305,0.00048725834,0.0007216161,0.00033094513],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009897834,0.00011892501,0.00033555797,0.0006892529,0.00015880066,0.00013226323,0.0008372734,0.00045196095,0.00011207021],"category_scores_gemma":[0.002204789,0.00008519398,0.0002269804,0.0019579008,0.0009670595,0.00000992245,0.0002989826,0.00067018764,0.00008719975],"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":[0.000081574646,0.00058341085,0.056825217,0.000010560433,0.000042013373,0.000040414867,0.000013888245,0.00021182855,0.9190753,0.0006653771,0.020424165,0.0020262208],"study_design_scores_gemma":[0.0035088672,0.004419948,0.51597816,0.00036090595,0.000052735664,0.00057034584,0.00061539834,0.0018610117,0.004511675,0.002899793,0.46440265,0.00081853877],"about_ca_topic_score_codex":0.0000041460858,"about_ca_topic_score_gemma":0.0000072316543,"teacher_disagreement_score":0.91456366,"about_ca_system_score_codex":0.00013564604,"about_ca_system_score_gemma":0.00038227375,"threshold_uncertainty_score":0.3563171},"labels":[],"label_agreement":null},{"id":"W2950530125","doi":"10.48550/arxiv.1101.1663","title":"Linear Conjugacy of Chemical Reaction Networks","year":2011,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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 Waterloo","funders":"","keywords":"Ordinary differential equation; Conjugacy class; Action (physics); Network dynamics; Work (physics); Mathematics; Chemical Dynamics; Computer science; Dynamics (music); Phenomenon; Differential equation; Statistical physics; Pure mathematics; Discrete mathematics; Physics; Mathematical analysis; Chemical physics; Thermodynamics","score_opus":0.038274438684545754,"score_gpt":0.1809810443852758,"score_spread":0.14270660570073004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950530125","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":[0.9770241,0.00030164176,0.02082001,0.000005471014,0.00020955445,0.00013492024,0.000009392724,0.000022186592,0.0014727731],"genre_scores_gemma":[0.9978581,0.00053543074,0.0001744972,0.000022294837,0.0003287731,6.519969e-7,0.00026023682,0.000029785346,0.0007902125],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99870163,0.00008378652,0.00021690513,0.000721919,0.000045001558,0.0002307807],"domain_scores_gemma":[0.9984598,0.000009360611,0.0003224686,0.0009133439,0.00017976006,0.00011523156],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013810777,0.000251511,0.00033119664,0.000082804436,0.000030740193,0.000005339726,0.0004376527,0.000643923,0.00003997814],"category_scores_gemma":[0.000020499092,0.0003030594,0.00037607976,0.00017864368,0.0001606936,0.000003409452,0.0006762618,0.00029227164,0.000009987832],"study_design_candidate":"simulation_or_modeling","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":[0.00094149855,0.00047817317,0.018940406,0.00021703343,0.002454068,0.00007817434,0.00006621966,0.64605224,0.32283676,0.0038543562,0.0031946597,0.00088638597],"study_design_scores_gemma":[0.003120245,0.00053849345,0.0045283404,0.0003177536,0.003478616,0.000032098847,0.00018639877,0.36721408,0.60148627,0.00833668,0.007578112,0.0031829257],"about_ca_topic_score_codex":0.00007392721,"about_ca_topic_score_gemma":0.000014317661,"teacher_disagreement_score":0.2788382,"about_ca_system_score_codex":0.00003822354,"about_ca_system_score_gemma":0.00009634308,"threshold_uncertainty_score":0.9999421},"labels":[],"label_agreement":null},{"id":"W2950801430","doi":"10.1101/142521","title":"A multi-stage representation of cell proliferation as a Markov process","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Markov chain; Exponential growth; Process (computing); Exponential function; Computer science; Markov process; Representation (politics); Variance (accounting); Algorithm; Biological system; Exponential distribution; Property (philosophy); Applied mathematics; Mathematics; Biology; Statistics; Machine learning","score_opus":0.01893077394042962,"score_gpt":0.2720433374160669,"score_spread":0.25311256347563726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950801430","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":[0.99432194,0.0010096176,0.003313346,0.00004276403,0.0003112764,0.00081319455,0.00010900329,0.000051560866,0.0000273035],"genre_scores_gemma":[0.99293447,0.00032295554,0.0057519916,0.00004220041,0.0004458001,0.00023881893,0.00000676406,0.00010846379,0.00014854666],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99735636,0.00017245716,0.00057302666,0.0011407889,0.0003866534,0.0003707401],"domain_scores_gemma":[0.9956287,0.000009189475,0.001130885,0.0021961816,0.0008580544,0.00017695327],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004438942,0.00046662174,0.00054301886,0.00018337795,0.00017509745,0.00014074107,0.00070371706,0.0006950931,0.000023771552],"category_scores_gemma":[0.00028398546,0.00052397646,0.0002862262,0.00020819275,0.0001407032,0.000014869102,0.00046810877,0.00030312783,0.000015030198],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007547964,0.00017483893,0.021903729,0.0004992134,0.0002242058,0.00000958101,0.0000109485245,0.0012491571,0.97570384,0.00000564296,0.00014107072,0.0000023172095],"study_design_scores_gemma":[0.0005916293,0.00007279815,0.023142764,0.00011506617,0.00019957744,1.45123655e-8,0.000005794966,0.002468909,0.9723917,9.024337e-7,0.00050055416,0.00051026855],"about_ca_topic_score_codex":0.00004761798,"about_ca_topic_score_gemma":0.000012005384,"teacher_disagreement_score":0.0033120958,"about_ca_system_score_codex":0.000056427114,"about_ca_system_score_gemma":0.0007730184,"threshold_uncertainty_score":0.99972117},"labels":[],"label_agreement":null},{"id":"W2950851734","doi":"10.1021/sb400206c","title":"Rapidly Characterizing the Fast Dynamics of RNA Genetic Circuitry with Cell-Free Transcription–Translation (TX-TL) Systems","year":2014,"lang":"en","type":"article","venue":"ACS Synthetic Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":181,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Institute for Research in Immunology and Cancer","funders":"Defense Advanced Research Projects Agency; Office of Naval Research; Alfred P. Sloan Foundation; Howard Hughes Medical Institute","keywords":"Synthetic biology; RNA; Computational biology; Transcription (linguistics); Biology; Cascade; Bottleneck; Translation (biology); Systems biology; Computer science; Genetics; Messenger RNA; Gene; Chemistry","score_opus":0.006809401474155928,"score_gpt":0.19076041003429103,"score_spread":0.1839510085601351,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950851734","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":[0.9204074,0.0020937994,0.07567432,0.0005185368,0.00024580536,0.00027662024,0.000038138336,0.000018115375,0.0007272395],"genre_scores_gemma":[0.9985791,0.00022533725,0.00046565305,0.000084508814,0.00023691122,0.000036883193,0.00021530519,0.000038810416,0.00011747649],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99828035,0.00037832864,0.0004127693,0.0004594778,0.00013219363,0.00033688964],"domain_scores_gemma":[0.99847126,0.000055331162,0.000263333,0.0010317239,0.00011321136,0.00006514174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038448515,0.00024544523,0.00033619153,0.00007058838,0.00012051521,0.000019660078,0.00053098483,0.00029599672,0.000011554867],"category_scores_gemma":[0.000024491246,0.0001753987,0.00013986687,0.00016060789,0.00033087726,0.000004006274,0.00005142828,0.00012450034,0.000005187785],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046138128,0.00004471158,0.0022641283,0.000058546564,0.00016512642,0.0000011086623,0.000081405386,0.0012220754,0.9870439,0.00042369874,0.00003429166,0.00861486],"study_design_scores_gemma":[0.0053146114,0.0032122084,0.02071538,0.00029040012,0.0021710568,0.00091749395,0.001462559,0.053907767,0.86534226,0.0014884976,0.04262269,0.0025551047],"about_ca_topic_score_codex":0.000039833638,"about_ca_topic_score_gemma":0.000084873114,"teacher_disagreement_score":0.12170168,"about_ca_system_score_codex":0.000017914035,"about_ca_system_score_gemma":0.00004856202,"threshold_uncertainty_score":0.71525514},"labels":[],"label_agreement":null},{"id":"W2950920865","doi":"10.1162/artl_a_00303","title":"Measuring Time with Minimal Clocks","year":2019,"lang":"en","type":"preprint","venue":"Artificial Life","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Waterloo","funders":"","keywords":"Measure (data warehouse); Molecular clock; Biological clock; Computer science; Scale (ratio); Circadian clock; Real-time computing; Dynamics (music); Vector clock; Atomic clock; Clock synchronization; Biological system; Statistical physics; Physics; Biology; Synchronization (alternating current); Neuroscience; Circadian rhythm; Acoustics; Quantum mechanics","score_opus":0.021930369675214077,"score_gpt":0.22231153062161338,"score_spread":0.2003811609463993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950920865","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":[0.9946998,0.0006890062,0.0009159142,0.00018034512,0.00025094813,0.00026153063,0.000022322745,0.000029915513,0.0029502283],"genre_scores_gemma":[0.99587387,0.000021179676,0.00044641527,0.00018193114,0.0014769288,0.000024078363,0.00031080018,0.00005944102,0.0016053382],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99826753,0.00008224414,0.00031333606,0.0007224424,0.0002814781,0.00033299558],"domain_scores_gemma":[0.99860615,0.000008671903,0.00019714114,0.00090123026,0.0001320197,0.00015479278],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022870932,0.00030552116,0.00036486128,0.00006531408,0.000072320676,0.00006228458,0.0003273814,0.00040232702,0.000099342156],"category_scores_gemma":[0.000048286412,0.00028610832,0.00022530514,0.000082805156,0.00007191435,0.0000014747415,0.00050796155,0.00023110473,0.00028011555],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011565256,0.00035462115,0.030290712,0.00022943446,0.0031562895,0.00003302492,0.00018657063,0.28141952,0.6451804,0.00013662591,0.03202084,0.0058354153],"study_design_scores_gemma":[0.001402788,0.0014195842,0.015545309,0.00043935096,0.0020660071,0.00004118135,0.00023401775,0.029096646,0.79871136,0.00097120175,0.14502126,0.005051296],"about_ca_topic_score_codex":0.000017963135,"about_ca_topic_score_gemma":0.000048063815,"teacher_disagreement_score":0.25232288,"about_ca_system_score_codex":0.000020764177,"about_ca_system_score_gemma":0.00036350277,"threshold_uncertainty_score":0.9999591},"labels":[],"label_agreement":null},{"id":"W2951527048","doi":"10.1038/s41467-019-10330-w","title":"Role of network-mediated stochasticity in mammalian drug resistance","year":2019,"lang":"en","type":"article","venue":"Nature Communications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":100,"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 Alberta","funders":"National Cancer Institute; National Institutes of Health; National Institute of General Medical Sciences; Ministry of Education and Science of the Russian Federation","keywords":"Drug resistance; Drug; Resistance (ecology); Computational biology; Biology; Computer science; Genetics; Pharmacology; Ecology","score_opus":0.004774386301108912,"score_gpt":0.23846144823438167,"score_spread":0.23368706193327277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951527048","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":[0.9591745,0.033325594,0.00012610426,0.000998653,0.000070000846,0.00030205288,0.000023216471,0.000013494335,0.005966379],"genre_scores_gemma":[0.9958076,0.000297525,0.0025965627,0.00009029667,0.000040997817,0.00001509507,0.0002927207,0.000013565518,0.000845648],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99918354,0.00014353116,0.00022006739,0.00018420741,0.000102981045,0.00016565669],"domain_scores_gemma":[0.9980209,0.000051451938,0.00012330529,0.0016548864,0.00011065164,0.00003882032],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020109715,0.00009458533,0.00015734977,0.00004962947,0.000045779005,0.0000054668435,0.0007361874,0.00021911823,0.000016059936],"category_scores_gemma":[0.00006441307,0.0001003902,0.000076084776,0.00036447603,0.00007497949,0.0000027105793,0.00027094167,0.00031218524,0.0000113590895],"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":[0.00021007883,0.00043443727,0.42388347,0.000050641363,0.00029946343,8.449664e-7,0.00030639762,0.023975015,0.5177199,0.008974171,0.023406131,0.00073940546],"study_design_scores_gemma":[0.001927083,0.000092450835,0.3866629,0.00017656104,0.00015063377,0.000004966322,0.0005013735,0.011470161,0.0312907,0.0012562955,0.56548464,0.0009822109],"about_ca_topic_score_codex":0.00001398606,"about_ca_topic_score_gemma":0.0053318236,"teacher_disagreement_score":0.54207855,"about_ca_system_score_codex":0.000017437591,"about_ca_system_score_gemma":0.000055045213,"threshold_uncertainty_score":0.40937933},"labels":[],"label_agreement":null},{"id":"W2951650699","doi":"10.48550/arxiv.0804.2267","title":"Dynamics and density evolution in piecewise deterministic growth processes","year":2008,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Dynamics (music); Statistical physics; Piecewise; Mathematics; Computer science; Physics; Mathematical analysis","score_opus":0.01185196231823098,"score_gpt":0.22846584940043504,"score_spread":0.21661388708220405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951650699","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":[0.9954732,0.0021979315,0.0018365683,0.00007138903,0.00010698969,0.00018920355,0.000015156152,0.000017968423,0.0000915676],"genre_scores_gemma":[0.99644583,0.0025413684,0.00020788472,0.000048073467,0.00020734851,0.000031762575,0.0003054513,0.0000336643,0.0001786059],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984984,0.00007653101,0.00029912754,0.0007206052,0.00012696684,0.00027841126],"domain_scores_gemma":[0.99903244,0.000013841345,0.00017842978,0.00049435714,0.00018672393,0.00009418636],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012270789,0.00029521424,0.00033148305,0.00010411433,0.000080202444,0.000018095467,0.0002196193,0.0004558495,0.0000020714008],"category_scores_gemma":[0.00019779515,0.00032122564,0.00009521053,0.00016257384,0.0001528366,0.000003083093,0.0005799537,0.00024738343,0.0000060284847],"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":[0.000028956894,0.000052592783,0.9946877,0.0002257179,0.00007548516,0.000024807283,0.00003068856,0.0007241004,0.003901934,0.000008862522,0.000059768543,0.00017940454],"study_design_scores_gemma":[0.0002724503,0.000064343796,0.98919004,0.00008137251,0.00012889846,0.00004966152,0.000023868297,0.0038518482,0.0054825363,0.00035765817,0.000042128584,0.00045517602],"about_ca_topic_score_codex":0.000117582975,"about_ca_topic_score_gemma":0.0016284382,"teacher_disagreement_score":0.0054976237,"about_ca_system_score_codex":0.00009651514,"about_ca_system_score_gemma":0.00029493263,"threshold_uncertainty_score":0.999924},"labels":[],"label_agreement":null},{"id":"W2952800844","doi":"10.1101/019273","title":"The case for absolute ligand discrimination : modeling information processing and decision by immune T cells","year":2015,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Context (archaeology); Sorting; Population; Computer science; Artificial intelligence; Algorithm; Biology","score_opus":0.010301256336736854,"score_gpt":0.22458510240214377,"score_spread":0.21428384606540693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952800844","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":[0.86267585,0.009689826,0.12658496,0.000074567215,0.0002745466,0.0005571005,0.00010928241,0.00003264588,0.0000012209896],"genre_scores_gemma":[0.99381095,0.00089437334,0.004810666,0.00003338235,0.0002299033,0.00015580084,0.000005862773,0.0000546054,0.000004456745],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984069,0.000046357953,0.0005272432,0.00048781108,0.00019615942,0.0003355415],"domain_scores_gemma":[0.99791986,0.000023014774,0.00040311663,0.0006838558,0.00082007225,0.0001500743],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009677375,0.00034012648,0.00027236424,0.000086121414,0.00043151111,0.00041668356,0.00026741906,0.00042267266,3.3315453e-7],"category_scores_gemma":[0.00013496698,0.00029635153,0.0001139695,0.0001376676,0.00007304984,0.000033698514,0.00039709377,0.00019040721,0.0000018206448],"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":[0.00014249026,0.000042152187,0.000049397662,0.00037619568,0.0002047371,0.000007532987,0.000028121316,0.02357476,0.97258794,0.000024351863,0.002372538,0.00058978004],"study_design_scores_gemma":[0.00086356176,0.00009590527,0.00012345717,0.00021486111,0.00038933186,3.6785215e-7,0.000042641892,0.559729,0.42964375,0.000030186253,0.0080553945,0.0008115713],"about_ca_topic_score_codex":0.000024668789,"about_ca_topic_score_gemma":0.000010252751,"teacher_disagreement_score":0.5429442,"about_ca_system_score_codex":0.0000782007,"about_ca_system_score_gemma":0.00028626755,"threshold_uncertainty_score":0.99994886},"labels":[],"label_agreement":null},{"id":"W2958731503","doi":"10.1098/rsif.2019.0182","title":"Metabolic activity affects the response of single cells to a nutrient switch in structured populations","year":2019,"lang":"en","type":"article","venue":"Journal of The Royal Society Interface","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":49,"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":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Nutrient; Phenotype; Biology; Cell biology; Metabolism; Biochemistry; Ecology; Gene","score_opus":0.008499513287531424,"score_gpt":0.24802086832518735,"score_spread":0.23952135503765593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2958731503","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":[0.99491304,0.0006334367,0.003244556,0.0007226574,0.00029942676,0.00016973766,0.0000042159872,0.0000010359847,0.000011909412],"genre_scores_gemma":[0.99886936,0.000009481866,0.00041476105,0.0000911681,0.000076798045,0.0000012152608,2.6014283e-7,0.000010424982,0.0005265376],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990094,0.00029351015,0.00022639983,0.00011734292,0.00020814221,0.00014520768],"domain_scores_gemma":[0.99913603,0.00003748889,0.00032734603,0.00035857596,0.000094735144,0.00004581835],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062791986,0.00010528996,0.00021878384,0.000021773387,0.00004317748,0.000014631873,0.00037909317,0.00008913258,0.000014381276],"category_scores_gemma":[0.00006577891,0.00006162638,0.00045107194,0.00021913537,0.000035681336,0.0000033248466,0.00017098636,0.0001650843,0.0000016350857],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003048624,0.000050331113,0.0025896474,0.000004816884,0.000116444455,1.11886294e-7,0.00034703888,0.2190155,0.7757134,0.0000023226762,0.0017585349,0.000097032476],"study_design_scores_gemma":[0.00034636384,0.00020542454,0.04377186,0.000030463814,0.00007107587,0.0000039379966,0.0002653642,0.001910054,0.95084727,0.000025801644,0.0024482186,0.00007414122],"about_ca_topic_score_codex":0.000014966565,"about_ca_topic_score_gemma":0.000029836903,"teacher_disagreement_score":0.21710543,"about_ca_system_score_codex":0.000052322062,"about_ca_system_score_gemma":0.00006635054,"threshold_uncertainty_score":0.25130507},"labels":[],"label_agreement":null},{"id":"W2961644112","doi":"10.1515/jib-2019-0035","title":"Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2019","year":2019,"lang":"en","type":"review","venue":"Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"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":"National Institute of General Medical Sciences; National Human Genome Research Institute","keywords":"SBML; Computer science; Software engineering; Programming language; Process (computing); Markup language; World Wide Web; XML","score_opus":0.034406021553025114,"score_gpt":0.32573692615158356,"score_spread":0.2913309045985584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2961644112","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027175955,0.9910201,0.0016662497,0.000011734139,0.00043460913,0.0013105405,0.0005610542,0.0000079922565,0.002270142],"genre_scores_gemma":[0.0032793537,0.9865667,0.009362306,0.00003770663,0.00006462081,0.00003570829,0.00053732615,0.000044590714,0.0000716687],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9926527,0.00022248174,0.005464261,0.00024970263,0.00071791053,0.00069293944],"domain_scores_gemma":[0.9930152,0.0002431097,0.0048800246,0.0006007332,0.00095659227,0.00030432965],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0021147716,0.0009250601,0.0030656466,0.0018415184,0.000065638866,0.00014701538,0.00067275326,0.0008060138,0.000008556275],"category_scores_gemma":[0.0005890223,0.00063375855,0.00036228582,0.0011569482,0.0004907236,0.00026141567,0.00041991452,0.00079767103,0.000012039473],"study_design_candidate":"not_applicable","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":[0.00030382097,0.00026338332,0.004333276,0.036188394,0.0051952708,0.000010544283,0.017064402,0.0003786147,0.000036872443,0.0019870733,0.0028613622,0.931377],"study_design_scores_gemma":[0.0018168747,0.00081265776,0.00041963154,0.011645976,0.0010410076,0.00033697925,0.0073236497,0.0013764853,0.000080921396,0.000020536492,0.9740875,0.0010378321],"about_ca_topic_score_codex":0.00002682742,"about_ca_topic_score_gemma":0.00003661609,"teacher_disagreement_score":0.9712261,"about_ca_system_score_codex":0.0003022759,"about_ca_system_score_gemma":0.0023500868,"threshold_uncertainty_score":0.9996114},"labels":[],"label_agreement":null},{"id":"W2962697832","doi":"10.1002/cpa.21651","title":"Systematic Measures of Biological Networks II: Degeneracy, Complexity, and Robustness","year":2016,"lang":"en","type":"article","venue":"Communications on Pure and Applied Mathematics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"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 Alberta","funders":"","keywords":"Robustness (evolution); Degeneracy (biology); Mathematics; Attractor; Ordinary differential equation; Statistical physics; Entropy (arrow of time); Applied mathematics; Theoretical computer science; Computer science; Differential equation; Mathematical analysis","score_opus":0.060824224736321875,"score_gpt":0.26842250996105055,"score_spread":0.20759828522472867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2962697832","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":[0.90079087,0.008283149,0.08857149,0.00053257536,0.000019528052,0.00061569863,0.000015468742,0.000027642454,0.0011435647],"genre_scores_gemma":[0.9803736,0.002932683,0.016464619,0.000036303773,0.000026462552,0.00006550994,0.000022601162,0.000014255682,0.00006392882],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99917424,0.00006705587,0.00035033954,0.00018622902,0.00009253161,0.00012960314],"domain_scores_gemma":[0.99833745,0.00012079972,0.0002018008,0.0012091852,0.00006945481,0.00006130483],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033691892,0.00014758359,0.0003336596,0.000040164185,0.00019303584,0.000013449382,0.0003947858,0.00013228685,0.0000033814592],"category_scores_gemma":[0.00005258279,0.0000936496,0.000055419674,0.000088763576,0.0003973422,0.000002081604,0.00050711585,0.000054448785,9.271768e-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":[0.000116535826,0.0018250259,0.0015718975,0.005240467,0.0017896281,7.900384e-7,0.0005578556,0.0036277554,0.4538207,0.5133284,0.0023524885,0.015768457],"study_design_scores_gemma":[0.018323854,0.0054444326,0.01096009,0.028746715,0.0073814252,0.00066594087,0.00894347,0.18138888,0.55007625,0.16358326,0.013580763,0.010904918],"about_ca_topic_score_codex":3.6250685e-7,"about_ca_topic_score_gemma":0.000011675313,"teacher_disagreement_score":0.34974512,"about_ca_system_score_codex":0.0000058540736,"about_ca_system_score_gemma":0.000012352546,"threshold_uncertainty_score":0.381892},"labels":[],"label_agreement":null},{"id":"W2963138844","doi":"10.25088/complexsystems.20.4.325","title":"Period-Halving Bifurcation of a Neuronal Recurrence Equation","year":2011,"lang":"en","type":"article","venue":"Complex Systems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"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":"Abdus Salam International Centre for Theoretical Physics; University of Alberta","keywords":"Bifurcation; Period (music); Mathematics; Exponential function; Convergence (economics); Combinatorics; Mathematical analysis; Physics; Nonlinear system","score_opus":0.07523020377044722,"score_gpt":0.25611653690964786,"score_spread":0.18088633313920066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963138844","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":[0.980868,0.0009931405,0.0159406,0.000008466598,0.00022270306,0.00015222463,0.0000060359052,0.000010834631,0.0017980362],"genre_scores_gemma":[0.99915594,0.000014859127,0.00043974485,0.000008372888,0.00014462485,0.000014930807,0.000075725424,0.0000104973615,0.00013532086],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99920976,0.00010018248,0.0002448365,0.00020876688,0.00011923028,0.00011721941],"domain_scores_gemma":[0.9993408,0.0000045885963,0.00017370682,0.0003145633,0.00012745136,0.00003893109],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001740207,0.00008586646,0.00012954464,0.000046630157,0.00004450567,0.000009276568,0.00014990014,0.000054519332,0.000034180048],"category_scores_gemma":[0.00003070436,0.0000870846,0.000069931375,0.00011736868,0.000045748515,0.0000028731217,0.000048923437,0.000027129601,0.000010081254],"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":[0.00004614399,0.00008823597,0.043924354,0.00012526909,0.0001220391,9.556964e-7,0.0004695628,0.001995909,0.9474747,0.0017292514,0.0010989907,0.0029245843],"study_design_scores_gemma":[0.0015272966,0.0012540111,0.6108838,0.0002726572,0.00031533747,0.00012214892,0.0014145896,0.17706157,0.16243185,0.00036213946,0.042969257,0.0013853462],"about_ca_topic_score_codex":0.000035582554,"about_ca_topic_score_gemma":0.000008627162,"teacher_disagreement_score":0.7850429,"about_ca_system_score_codex":0.000009549592,"about_ca_system_score_gemma":0.00003445039,"threshold_uncertainty_score":0.3551207},"labels":[],"label_agreement":null},{"id":"W2963250704","doi":"10.1002/cpa.21647","title":"Systematic Measures of Biological Networks I: Invariant Measures and Entropy","year":2016,"lang":"en","type":"article","venue":"Communications on Pure and Applied Mathematics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"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 Alberta","funders":"","keywords":"Attractor; Mathematics; Ordinary differential equation; Dissipative system; Applied mathematics; Statistical physics; Entropy (arrow of time); White noise; Differential equation; Mathematical analysis; Statistics; Physics","score_opus":0.03704488370634303,"score_gpt":0.24725800253924082,"score_spread":0.21021311883289778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963250704","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":[0.74097806,0.031006237,0.22003052,0.0016321968,0.00005612401,0.0020433958,0.00003612051,0.000079533405,0.004137813],"genre_scores_gemma":[0.987776,0.0050688814,0.0069340845,0.000053800137,0.000025443007,0.00007136564,0.000011762638,0.000013556738,0.000045150136],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991464,0.00008419475,0.00035081178,0.00018212544,0.00010785213,0.0001286206],"domain_scores_gemma":[0.9983318,0.0001596317,0.0001994903,0.0011797136,0.000065654465,0.00006371894],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042762366,0.00014383536,0.0003192463,0.000041601495,0.00010823582,0.000016434236,0.00035493632,0.00013667891,0.000002743641],"category_scores_gemma":[0.000111513466,0.000087459695,0.00005691452,0.00007908553,0.00025945564,0.0000019445088,0.00025887534,0.000056033823,0.000002148741],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007504855,0.0005984904,0.0008315577,0.0015885917,0.0011055532,5.3821435e-7,0.00035196138,0.000213585,0.6853816,0.300467,0.0010151683,0.008370889],"study_design_scores_gemma":[0.015402807,0.003968078,0.008559594,0.021421287,0.006976722,0.00045727912,0.008955954,0.02576205,0.6850553,0.19204421,0.023565795,0.007830889],"about_ca_topic_score_codex":4.4282854e-7,"about_ca_topic_score_gemma":0.0000067276937,"teacher_disagreement_score":0.24679789,"about_ca_system_score_codex":0.000006234462,"about_ca_system_score_gemma":0.000014632473,"threshold_uncertainty_score":0.3566503},"labels":[],"label_agreement":null},{"id":"W2965152924","doi":"10.1007/978-3-030-26807-7_11","title":"Error-Free Stable Computation with Polymer-Supplemented Chemical Reaction Networks","year":2019,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Bottleneck; Computer science; Computation; Turing; Polymer; Turing machine; Theoretical computer science; Algorithm; Chemistry","score_opus":0.007435960383910231,"score_gpt":0.22323302100800888,"score_spread":0.21579706062409865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965152924","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":[0.007772451,0.00075589895,0.9899961,0.00013856898,0.00036257555,0.00029159072,0.000010835741,0.000024634415,0.00064736244],"genre_scores_gemma":[0.9768493,0.000054332904,0.020130914,0.00047376545,0.0009277416,0.000007106767,0.000636099,0.00007279976,0.0008479389],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977148,0.000026228801,0.00030858832,0.0010333867,0.00047562143,0.00044133666],"domain_scores_gemma":[0.99855393,0.000036704994,0.00025065808,0.00089311396,0.00016487656,0.000100715144],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00027892686,0.00038180672,0.00034787253,0.0001949919,0.00009684855,0.000078191464,0.00066928676,0.00039470074,0.000020852867],"category_scores_gemma":[0.000013183589,0.00034449704,0.00009591262,0.0002469377,0.00032022395,0.000012028692,0.00043848154,0.00036602828,0.0000066647513],"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":[0.00016508644,0.00005362791,0.0005683112,0.00004484122,0.00019040216,0.000017345263,0.00005626575,0.8462945,0.06937153,0.00021235416,0.0006414315,0.082384266],"study_design_scores_gemma":[0.0019703172,0.0009210001,0.00034109646,0.0003714827,0.0002117408,0.00014453694,0.0000013978439,0.86424357,0.12108985,0.002699685,0.0060806843,0.0019246185],"about_ca_topic_score_codex":0.000021807731,"about_ca_topic_score_gemma":0.0001406269,"teacher_disagreement_score":0.96986514,"about_ca_system_score_codex":0.00011722617,"about_ca_system_score_gemma":0.0003013322,"threshold_uncertainty_score":0.9999007},"labels":[],"label_agreement":null},{"id":"W2968569765","doi":"10.1007/s11047-019-09756-4","title":"Approximate majority analyses using tri-molecular chemical reaction networks","year":2019,"lang":"en","type":"article","venue":"Natural Computing","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Correctness; Simple (philosophy); Protocol (science); Population; Context (archaeology); Theory of computation; Binary logarithm; Computer science; Combinatorics; Discrete mathematics; Mathematics; Theoretical computer science; Algorithm; Biology","score_opus":0.015566931183915866,"score_gpt":0.2939392384567327,"score_spread":0.2783723072728168,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2968569765","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":[0.9858694,0.0020810694,0.011340002,0.000016905273,0.00034002372,0.00013632483,6.6134265e-7,0.000034724206,0.00018089988],"genre_scores_gemma":[0.99577415,0.000010276207,0.003397369,0.00011249555,0.0005041376,7.389824e-7,0.000115647024,0.000027668077,0.000057512003],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99855095,0.00009983595,0.00027249765,0.00050697895,0.00019988912,0.0003698593],"domain_scores_gemma":[0.9992291,0.000015660764,0.00017334239,0.0003950915,0.00011283295,0.00007397822],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002519807,0.00021344896,0.00026621833,0.000061860774,0.00008882262,0.00004092622,0.00020338834,0.00022545252,0.0000065851777],"category_scores_gemma":[0.000033940585,0.00020754249,0.00025509714,0.00032299195,0.00003484183,0.0000059190293,0.00020325123,0.0002705642,0.00000607005],"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":[0.00003159438,0.000014704623,0.002147699,0.000011748527,0.00013225466,0.0000027566252,0.000004773129,0.05092305,0.94451374,0.000013802453,0.000051079747,0.0021528206],"study_design_scores_gemma":[0.00041496762,0.000030624615,0.0011286559,0.000023118559,0.00011395553,0.000040116913,0.0000251795,0.69750947,0.30006042,0.000021624573,0.00030157343,0.00033027967],"about_ca_topic_score_codex":0.00002057628,"about_ca_topic_score_gemma":0.0000016098278,"teacher_disagreement_score":0.6465864,"about_ca_system_score_codex":0.000051310988,"about_ca_system_score_gemma":0.000029872015,"threshold_uncertainty_score":0.8463337},"labels":[],"label_agreement":null},{"id":"W2970388638","doi":"10.1016/j.cherd.2019.08.015","title":"Complex system decomposition for distributed state estimation based on weighted graph","year":2019,"lang":"en","type":"article","venue":"Process Safety and Environmental Protection","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Fundamental Research Funds for the Central Universities; Natural Science Foundation of Guangdong Province; National Natural Science Foundation of China","keywords":"Graph; Nonlinear system; Directed graph; Computer science; Node (physics); Algorithm; Modular decomposition; State (computer science); Process (computing); Decomposition; Connection (principal bundle); Graph theory; Mathematics; Theoretical computer science; Mathematical optimization; Line graph; Combinatorics; Pathwidth; Engineering","score_opus":0.005100130028781583,"score_gpt":0.20796133693694574,"score_spread":0.20286120690816417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2970388638","genre_codex":"methods","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":[0.4187452,0.000035557925,0.5803525,0.00004307119,0.00002888572,0.0006529125,0.00009467012,0.0000182019,0.000029006964],"genre_scores_gemma":[0.99687827,0.000013355828,0.00041266935,0.000029735393,0.000025191996,0.00011199029,0.0024902206,0.00001547737,0.000023091554],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992684,0.000038332546,0.00015881911,0.00030126877,0.00010457428,0.00012861204],"domain_scores_gemma":[0.99970937,0.000004900331,0.00010161796,0.00013155711,0.000009773421,0.000042770174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000109947265,0.00012683826,0.00011147364,0.000037876893,0.00016340661,0.000014771548,0.000041008665,0.000078425015,0.000010112445],"category_scores_gemma":[0.0000021875612,0.000125298,0.00005696055,0.000060470746,0.000030461442,0.000007883047,0.000013717343,0.000042704687,0.000006245488],"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":[0.0019171553,0.0001243235,0.0013098348,0.00038075467,0.000078949946,2.4523257e-7,0.000018308532,0.8184846,0.16759166,0.000013391591,0.00001223951,0.010068533],"study_design_scores_gemma":[0.0010216399,0.00047658663,0.0057151765,0.000033068576,0.000038118003,0.000005422118,0.0000562258,0.94150287,0.050389554,0.00010370924,0.00047675334,0.00018089938],"about_ca_topic_score_codex":0.0000034161428,"about_ca_topic_score_gemma":0.0000018282363,"teacher_disagreement_score":0.57993984,"about_ca_system_score_codex":0.00005804119,"about_ca_system_score_gemma":0.000006599459,"threshold_uncertainty_score":0.5109504},"labels":[],"label_agreement":null},{"id":"W2971404151","doi":"10.1103/physrevlett.123.108101","title":"Kinetic Uncertainty Relations for the Control of Stochastic Reaction Networks","year":2019,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":29,"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":"Defense Advanced Research Projects Agency; National Science Foundation","keywords":"Component (thermodynamics); Dissipation; Statistical physics; Non-equilibrium thermodynamics; Network topology; Conjecture; Kinetic energy; Physics; Control (management); Connected component; Master equation; Computer science; Biological system; Topology (electrical circuits); Control theory (sociology); Mathematics; Thermodynamics; Quantum mechanics; Pure mathematics","score_opus":0.007037721946738691,"score_gpt":0.2510956934257773,"score_spread":0.24405797147903863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2971404151","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":[0.53219277,0.031018393,0.42742315,0.0069938116,0.0002442087,0.0020475113,0.000014979709,0.0000134510165,0.000051744104],"genre_scores_gemma":[0.9963925,0.0005275989,0.000032472944,0.0025853328,0.00028448243,0.00008216089,0.000047753398,0.000012933806,0.00003478511],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99933773,0.000061165636,0.00017620513,0.00018902839,0.00009610329,0.0001397884],"domain_scores_gemma":[0.9992654,0.00013322043,0.00014018425,0.0003736211,0.000058166595,0.000029415842],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001597345,0.00010056854,0.00022706357,0.0000099498275,0.00003687879,0.000003931258,0.00012907607,0.000015904392,0.0000076107185],"category_scores_gemma":[0.000055933386,0.00006958765,0.00028742952,0.000108993525,0.000048894475,0.0000020187333,0.000019147257,0.00006309135,0.000010009102],"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":[0.0000392148,0.000037119844,0.00019080997,0.00014170908,0.00026507667,5.2517365e-8,0.000006014595,0.7435759,0.24764292,0.0002019623,0.005431904,0.0024673387],"study_design_scores_gemma":[0.0015111207,0.0003532046,0.005794358,0.0006411604,0.0023198603,0.0000043462487,0.000013237196,0.9344386,0.0009222891,0.00015183022,0.053343594,0.0005064165],"about_ca_topic_score_codex":0.000005007336,"about_ca_topic_score_gemma":0.0000020545713,"teacher_disagreement_score":0.46419972,"about_ca_system_score_codex":0.000011310596,"about_ca_system_score_gemma":0.00001306096,"threshold_uncertainty_score":0.2837702},"labels":[],"label_agreement":null},{"id":"W2974263843","doi":"10.1016/j.media.2019.101560","title":"Special issue on MICCAI 2018","year":2019,"lang":"en","type":"editorial","venue":"Medical Image Analysis","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Engineering and Physical Sciences Research Council","keywords":"Systems biology; Computer science; Gene regulatory network; Synthetic biology; Modelling biological systems; Computational biology; Key (lock); Data science; Artificial intelligence; Biology; Gene","score_opus":0.0033260884908028147,"score_gpt":0.2558565078153947,"score_spread":0.2525304193245919,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2974263843","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011749457,0.0011609093,0.0014607945,0.0007431767,0.97145045,0.000309077,0.0003530948,0.00004991274,0.023297658],"genre_scores_gemma":[0.00017374492,0.0011181541,0.00017966943,0.00038398313,0.94157755,0.00001786877,0.007244802,0.00008944594,0.04921476],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9944219,0.00030990856,0.00071495445,0.0014497914,0.0024598637,0.0006435831],"domain_scores_gemma":[0.99681866,0.00016824917,0.00036928218,0.001816734,0.0003500834,0.00047697415],"candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008538217,0.0006320604,0.0013090724,0.00050270616,0.000108731576,0.00010149257,0.0011598244,0.0023455399,0.009870115],"category_scores_gemma":[0.0017213589,0.00057165936,0.0017555869,0.0010262459,0.0002739292,0.00000417517,0.00039356083,0.00088690856,0.0021168469],"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":[0.000057780726,0.00011595225,0.00007624775,0.00003203447,0.006032575,0.00005579478,0.000008438195,0.00011829671,0.00043475206,5.276659e-7,0.9899284,0.0031391713],"study_design_scores_gemma":[0.00045157745,0.0001823609,0.000028045884,0.000029974542,0.00488435,9.704954e-7,0.000012219999,0.00039634373,0.0010407763,0.0000041726735,0.9923919,0.00057731906],"about_ca_topic_score_codex":0.00008663189,"about_ca_topic_score_gemma":0.00038001157,"teacher_disagreement_score":0.029872863,"about_ca_system_score_codex":0.00009330911,"about_ca_system_score_gemma":0.0005878274,"threshold_uncertainty_score":0.9996735},"labels":[],"label_agreement":null},{"id":"W2974932406","doi":"10.1016/j.euroneuro.2019.08.013","title":"S12EXAMINATION OF STARTLE-ASSOCIATED GENES AND THE CHANGE IN ANXIETY SYMPTOM SEVERITY FOLLOWING PHARMACOLOGICAL TREATMENT","year":2019,"lang":"en","type":"article","venue":"European Neuropsychopharmacology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Ergodicity; Metastability; Sampling (signal processing); Stability (learning theory); Statistical physics; Mathematics; Computer science; Psychology; Statistics; Machine learning; Physics","score_opus":0.013777207011314355,"score_gpt":0.27226486655146076,"score_spread":0.2584876595401464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2974932406","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":[0.9963451,0.0014838561,0.0000050510394,0.00023650394,0.0004493944,0.00058397895,0.0000065773943,0.000021431044,0.0008681323],"genre_scores_gemma":[0.9963162,0.0024630707,0.000019744151,0.00071075454,0.00015642671,0.00003187981,0.000028171764,0.000041239975,0.00023249978],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99733,0.001525632,0.0003134885,0.00045214244,0.00011299225,0.00026574152],"domain_scores_gemma":[0.99944746,0.000058611866,0.0001713374,0.0002205942,0.000040590177,0.000061388964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060405827,0.00020296266,0.00030382103,0.0000696676,0.00004494909,0.0000102822505,0.00020277245,0.00007152254,0.000052935284],"category_scores_gemma":[0.000021954635,0.00015234236,0.00016811957,0.0002180209,0.00013343894,0.0000070296046,0.00013880717,0.00010981329,0.000009939731],"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":[0.00053862884,0.00023631491,0.10873028,0.000008184113,0.0003165438,0.000024099701,0.00020600363,0.00027483414,0.87463576,0.000009722619,0.00016009917,0.014859559],"study_design_scores_gemma":[0.017282972,0.0009437414,0.93870246,0.000012903561,0.00042279073,0.0000224396,0.000050304014,0.0042862073,0.020012517,0.000011012923,0.01785833,0.000394337],"about_ca_topic_score_codex":0.000017687667,"about_ca_topic_score_gemma":0.000016109814,"teacher_disagreement_score":0.8546232,"about_ca_system_score_codex":0.000027566379,"about_ca_system_score_gemma":0.000017230663,"threshold_uncertainty_score":0.6212341},"labels":[],"label_agreement":null},{"id":"W2979694653","doi":"10.1049/enb.2019.0009","title":"Engineered gene networks enable non‐genetic drug resistance and enhanced cellular robustness","year":2019,"lang":"en","type":"article","venue":"Engineering Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biology; Gene; Gene regulatory network; Gene expression; Drug resistance; Robustness (evolution); Computational biology; Regulation of gene expression; Biological network; Genetics; Multiple drug resistance; Systems biology","score_opus":0.0017988048337665241,"score_gpt":0.16403145621598428,"score_spread":0.16223265138221776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2979694653","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":[0.82065254,0.006293471,0.17239255,0.00002610997,0.000347111,0.00016821538,0.0000032851583,0.00003437675,0.000082327635],"genre_scores_gemma":[0.99018866,0.00038634654,0.0064327237,0.00003208311,0.0003923345,0.000030278057,0.00012131486,0.000053780495,0.0023624888],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99859095,0.000038665752,0.000252328,0.0005728436,0.00006363153,0.0004815869],"domain_scores_gemma":[0.99919105,0.000021096941,0.00006675692,0.0005501436,0.000053170254,0.00011776311],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00015753988,0.00027889802,0.00032060803,0.00008205863,0.000045165947,0.000018244997,0.00022282498,0.00025350568,0.000029571644],"category_scores_gemma":[0.000020566802,0.0002898593,0.00009620322,0.00018787687,0.000043207987,0.0000035811931,0.00012820124,0.00013437375,0.000009995315],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013633181,0.0000069671087,0.0005092137,0.00002244274,0.00007757321,0.0000016588667,0.000009423626,0.3994919,0.59955066,0.000019965713,0.00018328267,0.00011326351],"study_design_scores_gemma":[0.0009374407,0.00010681762,0.002554404,0.000035179535,0.00007717824,0.000012337781,0.000015402333,0.15506129,0.8230471,0.000017249435,0.017322538,0.0008130426],"about_ca_topic_score_codex":0.0000043078535,"about_ca_topic_score_gemma":0.000009279665,"teacher_disagreement_score":0.24443062,"about_ca_system_score_codex":0.000019532665,"about_ca_system_score_gemma":0.000025950247,"threshold_uncertainty_score":0.99995536},"labels":[],"label_agreement":null},{"id":"W2984929238","doi":"10.1101/845792","title":"Genetic buffering and potentiation in metabolism","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Ministerio de Economía y Competitividad; York University","keywords":"Pleiotropy; Biology; Reprogramming; Context (archaeology); Potentiator; Mutant; In silico; Mutation; Saccharomyces cerevisiae; Epistasis; Gene; Enzyme; Genetics; Metabolism; Cell biology; Phenotype; Biochemistry","score_opus":0.005891138634371316,"score_gpt":0.19380734577731987,"score_spread":0.18791620714294854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2984929238","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":[0.98602396,0.010638688,0.0023174593,0.000055363522,0.0004853865,0.00040584386,0.000029132441,0.000039424594,0.000004724127],"genre_scores_gemma":[0.994938,0.0015386636,0.0027425487,0.00009742197,0.00049435825,0.00007264772,0.0000011740798,0.00010374384,0.000011410519],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99768555,0.00014342331,0.00043962352,0.0010677278,0.00022599057,0.0004376611],"domain_scores_gemma":[0.998261,0.000008621715,0.0002708981,0.001140411,0.00016966037,0.00014941636],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00035038695,0.00044586358,0.0004900601,0.0002489264,0.00005822252,0.00010968232,0.00033623195,0.00062069565,0.00001007668],"category_scores_gemma":[0.0000588618,0.0005195644,0.0001515659,0.00024949582,0.000063017425,0.000007113545,0.0006736864,0.00032752307,0.000015430121],"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":[0.000018770133,0.000038853923,0.06943857,0.00015285489,0.00019540994,0.000010096746,0.0000030577369,0.0060999193,0.92392594,0.00002551207,0.000084758685,0.0000062606177],"study_design_scores_gemma":[0.00051210594,0.000025227348,0.805677,0.00009440775,0.0001840042,2.9230039e-8,0.000001544234,0.0026582757,0.18728688,0.0000021015267,0.0028824052,0.0006760493],"about_ca_topic_score_codex":0.00004736138,"about_ca_topic_score_gemma":0.000012584985,"teacher_disagreement_score":0.7366391,"about_ca_system_score_codex":0.000069053625,"about_ca_system_score_gemma":0.00022529098,"threshold_uncertainty_score":0.9997256},"labels":[],"label_agreement":null},{"id":"W2984946828","doi":"10.1093/insilicoplants/diz009","title":"Gillespie-Lindenmayer systems for stochastic simulation of morphogenesis","year":2019,"lang":"en","type":"article","venue":"in silico Plants","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Stochastic simulation; Stochastic process; Computer science; Stochastic differential equation; Formalism (music); Parametric statistics; Stochastic modelling; Statistical physics; Morphogenesis; Extension (predicate logic); Applied mathematics; Mathematical optimization; Mathematics; Physics; Chemistry","score_opus":0.013247966075805508,"score_gpt":0.256353507206002,"score_spread":0.24310554113019647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2984946828","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":[0.9925468,0.0012390466,0.005570569,0.000004066566,0.00016511898,0.00038226263,0.000049757193,0.0000042237357,0.000038130158],"genre_scores_gemma":[0.9993251,0.000021549624,0.000041989202,0.000013707582,0.000092907976,0.000026530397,0.00011061892,0.000017535556,0.00035005325],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99916553,0.000034249268,0.0002575277,0.00025440208,0.000116001975,0.00017228335],"domain_scores_gemma":[0.9994485,0.00005151156,0.00011243638,0.00029319347,0.000060035305,0.000034352262],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001717139,0.000107862594,0.00021097566,0.00007784002,0.000015188425,0.00000615104,0.00011913257,0.00014124863,0.000010368665],"category_scores_gemma":[0.00003087022,0.000107451575,0.000083930376,0.00007950451,0.00002051874,0.000002143165,0.000031615586,0.000025514424,0.000012378767],"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":[0.00008152228,0.000027527783,0.017918224,0.000034738525,0.000049667124,3.1229578e-7,0.000014149617,0.78626436,0.19525105,0.0000069608327,0.00007421351,0.00027725296],"study_design_scores_gemma":[0.0032206096,0.00040123283,0.03525845,0.000156978,0.00011239607,0.00001282434,0.00028178314,0.8367855,0.118740305,0.000053961106,0.004307719,0.00066824036],"about_ca_topic_score_codex":0.000018324889,"about_ca_topic_score_gemma":0.000020165395,"teacher_disagreement_score":0.076510735,"about_ca_system_score_codex":0.000013581176,"about_ca_system_score_gemma":0.0000311437,"threshold_uncertainty_score":0.4381748},"labels":[],"label_agreement":null},{"id":"W2989375860","doi":"10.1162/artl_a_00303","title":"Measuring Time with Minimal Clocks","year":2019,"lang":"en","type":"article","venue":"University of Hertfordshire Research Archive (University of Hertfordshire)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Waterloo","funders":"","keywords":"Measure (data warehouse); Molecular clock; Biological clock; Circadian clock; Computer science; Atomic clock; Scale (ratio); Dynamics (music); Clock drift; Real-time computing; Biological system; Clock synchronization; Statistical physics; Physics; Biology; Synchronization (alternating current); Neuroscience; Circadian rhythm; Quantum mechanics; Acoustics","score_opus":0.015754856245991024,"score_gpt":0.20856150413269414,"score_spread":0.19280664788670313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2989375860","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":[0.9777044,0.00025185864,0.0030635612,0.00014504972,0.000029756875,0.00046917182,0.00006490812,0.000025805319,0.018245492],"genre_scores_gemma":[0.9843411,0.00029786932,0.005136292,0.000009311182,0.000052674462,1.12197945e-7,0.00012935988,0.000035757348,0.009997516],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9970606,0.00037216578,0.00017997631,0.0007523247,0.0009017484,0.0007331951],"domain_scores_gemma":[0.997781,0.000114647504,0.0002265444,0.0009281415,0.0006380167,0.0003116959],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00082069874,0.00027382848,0.0005372897,0.00048428922,0.00041194144,0.000013009512,0.0011832487,0.00021401052,0.0008530557],"category_scores_gemma":[0.00004406341,0.00032669678,0.00037074325,0.00062491227,0.0010231403,0.00004664902,0.00079004845,0.0003709341,0.00012823463],"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":[0.011983049,0.0011466508,0.1647219,0.0007374788,0.00370666,0.00033701197,0.0042934995,0.0033748425,0.76017374,0.000920799,0.026092302,0.022512082],"study_design_scores_gemma":[0.023801882,0.016491259,0.19656712,0.0018040881,0.0012450849,0.00017836652,0.084549665,0.03026136,0.053113107,0.0023215702,0.5849361,0.004730434],"about_ca_topic_score_codex":0.00073250855,"about_ca_topic_score_gemma":0.0013995565,"teacher_disagreement_score":0.70706064,"about_ca_system_score_codex":0.00008899909,"about_ca_system_score_gemma":0.00048766995,"threshold_uncertainty_score":0.9999185},"labels":[],"label_agreement":null},{"id":"W2991687158","doi":"10.3233/jid-2007-11305","title":"DESIGN AND IMPLEMENTATION OF A GENE NETWORK REVERSE ENGINEERING METHOD BASED ON MUTUAL INFORMATION","year":2007,"lang":"en","type":"article","venue":"Journal of Integrated Design and Process Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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 Calgary","funders":"","keywords":"Reverse engineering; Computer science; Systems engineering; Engineering; Programming language","score_opus":0.009852663611013486,"score_gpt":0.284954313781639,"score_spread":0.2751016501706255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991687158","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":[0.18965897,0.00016133829,0.8100443,0.000014424917,0.00003361201,0.00007921896,5.497558e-7,0.0000015699777,0.0000060605375],"genre_scores_gemma":[0.7682577,0.00003900759,0.23158312,0.00007643456,0.000035347908,0.0000010185812,0.0000023775822,0.0000031396037,0.0000018755572],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99915653,0.00005249492,0.00032305907,0.00009726721,0.00022126346,0.00014935905],"domain_scores_gemma":[0.99906635,0.000047328653,0.00030060776,0.00006730982,0.0004322295,0.000086144246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003293596,0.00008609146,0.00012294382,0.00018851523,0.00006208694,0.00003158587,0.00010954153,0.000049214923,0.0000034211384],"category_scores_gemma":[0.0001015016,0.00006658071,0.000026082034,0.0004821667,0.00006368506,0.000037775557,0.000009300986,0.00007153642,1.0758775e-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":[0.0003283375,0.00001133488,0.00055127137,0.000020660496,0.000027876056,0.0000018650134,0.00021868343,0.6052423,0.37413695,0.000013656039,0.00012096496,0.019326093],"study_design_scores_gemma":[0.00042152594,0.0006769359,0.0008074888,0.000042527605,0.000038131002,0.000046016965,0.00037314428,0.24921098,0.7481121,0.000030927622,0.00014962361,0.000090591755],"about_ca_topic_score_codex":0.0000030214787,"about_ca_topic_score_gemma":7.3308325e-7,"teacher_disagreement_score":0.57859874,"about_ca_system_score_codex":0.000019682375,"about_ca_system_score_gemma":0.00028890747,"threshold_uncertainty_score":0.27150825},"labels":[],"label_agreement":null},{"id":"W2993023536","doi":"10.1109/cdc40024.2019.9029988","title":"Coupling and synchronization of piecewise linear genetic regulatory systems","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"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":"Agence Nationale de la Recherche","keywords":"Synchronization (alternating current); Formalism (music); Piecewise linear function; Coupling (piping); Nonlinear system; Dynamical systems theory; Nonlinear dynamical systems; Differential equation; Control theory (sociology); Topology (electrical circuits); Computer science; Mathematics; Statistical physics; Biological system; Physics; Mathematical analysis; Quantum mechanics; Biology; Artificial intelligence; Engineering; Combinatorics","score_opus":0.007575576519835042,"score_gpt":0.22248761172044018,"score_spread":0.21491203520060514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2993023536","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":[0.94411176,0.02147609,0.03341508,0.000010362744,0.00034915813,0.00038628234,0.000016017622,0.000016120448,0.00021913576],"genre_scores_gemma":[0.99512416,0.0015554817,0.0014223299,0.000011852361,0.00038855436,0.000015922466,0.0002699085,0.000050659393,0.0011611293],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99849564,0.000046003122,0.00044929856,0.0006152103,0.00020325732,0.00019057008],"domain_scores_gemma":[0.99840397,0.000009134989,0.00034115685,0.0009380322,0.00022941626,0.00007831678],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00021259187,0.00026662284,0.00042608622,0.00009305987,0.000033111915,0.000024492178,0.00021206515,0.00053838245,0.000012934126],"category_scores_gemma":[0.000021463678,0.00026804153,0.00013856024,0.00007539966,0.00008771888,0.0000012643923,0.00058126973,0.00012636141,0.0000047035173],"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":[0.000014038816,0.000022036136,0.018661577,0.00060385454,0.00032976895,7.923159e-7,0.000012693194,0.94934756,0.030201996,0.000037241687,0.00047104713,0.00029736932],"study_design_scores_gemma":[0.0004719106,0.00013720914,0.011699194,0.0002613057,0.0004725062,0.00001542004,0.00007268617,0.96184844,0.022785235,0.00003956705,0.0015288169,0.00066771224],"about_ca_topic_score_codex":0.00004192045,"about_ca_topic_score_gemma":0.000010034675,"teacher_disagreement_score":0.051012408,"about_ca_system_score_codex":0.000025388292,"about_ca_system_score_gemma":0.00018751998,"threshold_uncertainty_score":0.9999772},"labels":[],"label_agreement":null},{"id":"W2995864181","doi":"10.1007/s11569-019-00361-4","title":"From Buzz to Burst—Critical Remarks on the Term ‘Life’ and Its Ethical Implications in Synthetic Biology","year":2019,"lang":"en","type":"article","venue":"NanoEthics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Universität Wien","keywords":"Epistemology; Philosophy of science; Context (archaeology); Constructive; Term (time); Function (biology); Discipline; Philosophy of technology; Artificial life; Sociology; Philosophy of biology; Cognitive science; Computer science; Psychology; Biology; Artificial intelligence; Philosophy; Social science","score_opus":0.01891728363628784,"score_gpt":0.3118904799789924,"score_spread":0.2929731963427045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995864181","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":[0.9571032,0.00052587246,0.00025985815,0.041275676,0.000109657,0.00021459487,0.000031053714,0.000008159703,0.00047195403],"genre_scores_gemma":[0.99377346,0.00012128768,0.0001706557,0.005539887,0.00017399543,0.000035118366,0.000041846542,0.0000181739,0.0001255455],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99862254,0.00029876485,0.00021388169,0.00049427163,0.00011133885,0.00025919708],"domain_scores_gemma":[0.99866796,0.00047850318,0.000034755118,0.0005976467,0.00009085023,0.00013030179],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005649039,0.00014386002,0.0001916648,0.000051981213,0.00007891361,0.00002051377,0.00025837764,0.0007488166,0.000058094676],"category_scores_gemma":[0.0012749307,0.00011060722,0.000067218345,0.00015482849,0.00013864897,0.0000013519206,0.00017237001,0.0005618046,0.00007556211],"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":[0.000095114876,0.00008629042,0.0210757,0.00002140877,0.00010011459,0.0000017388326,0.00024925757,0.00019212975,0.911714,0.064159825,0.0011583342,0.0011460854],"study_design_scores_gemma":[0.0034160684,0.0030632957,0.4008874,0.00063299114,0.0005603382,0.00007341253,0.0010808189,0.0054686894,0.34958613,0.0661801,0.16538242,0.0036683255],"about_ca_topic_score_codex":0.000019751134,"about_ca_topic_score_gemma":0.00007077292,"teacher_disagreement_score":0.5621279,"about_ca_system_score_codex":0.00001732213,"about_ca_system_score_gemma":0.00009504718,"threshold_uncertainty_score":0.57755595},"labels":[],"label_agreement":null},{"id":"W2996597124","doi":"10.1038/s41557-019-0403-x","title":"Interfacing electronic and genetic circuits","year":2019,"lang":"en","type":"letter","venue":"Nature Chemistry","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"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; Canadian Cancer Society Research Institute; Canadian Institutes of Health Research; Genome Canada","keywords":"Interfacing; Electronic circuit; Leverage (statistics); Interface (matter); Computation; Synthetic biology; Computer science; Chemistry; Computer hardware; Electrical engineering; Artificial intelligence; Computational biology; Algorithm; Engineering","score_opus":0.0027430372494944744,"score_gpt":0.20258104370368318,"score_spread":0.1998380064541887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2996597124","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":[0.8469724,0.09334895,0.00012950116,0.05317012,0.00056263036,0.00043522072,0.0000749211,0.00007301075,0.005233237],"genre_scores_gemma":[0.84999776,0.00074734486,0.000054496155,0.1277436,0.006863342,0.000019752842,0.0012250851,0.00014253081,0.013206115],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978594,0.00003786511,0.00025075,0.0009770127,0.0002553562,0.00061959616],"domain_scores_gemma":[0.99874425,0.000017348219,0.00018580539,0.0008994816,0.000096768796,0.00005634738],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.00007037764,0.00047318288,0.00039673777,0.000039028524,0.00005394899,0.000048581212,0.00041831602,0.0038923481,0.00008148264],"category_scores_gemma":[0.000047816306,0.000493936,0.00022608381,0.00010742774,0.00008039934,0.0000011780952,0.00031965438,0.0032128314,0.000018245188],"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":[0.000004485509,0.000005169486,0.00024167051,0.00031647075,0.00030966385,0.000034339235,0.000004297476,0.000024530173,0.40976927,2.6523404e-7,0.5883898,0.00090003305],"study_design_scores_gemma":[0.0002301851,0.00003050227,0.00006580116,0.00005604315,0.00018161694,0.00022459262,0.0000030376902,0.000030137033,0.22443227,0.0000804353,0.7741162,0.0005491392],"about_ca_topic_score_codex":0.0000015109532,"about_ca_topic_score_gemma":0.0000018051256,"teacher_disagreement_score":0.1857264,"about_ca_system_score_codex":0.00006921967,"about_ca_system_score_gemma":0.00021614734,"threshold_uncertainty_score":0.9997512},"labels":[],"label_agreement":null},{"id":"W2997053614","doi":"10.1186/s12859-019-3315-2","title":"Improvement of the memory function of a mutual repression network in a stochastic environment by negative autoregulation","year":2019,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Bistability; Biological network; Computer science; Gene regulatory network; Autoregulation; Function (biology); Stochastic process; Robustness (evolution); Mathematics; Biology; Physics; Bioinformatics; Genetics","score_opus":0.004249827032259076,"score_gpt":0.1854823751677977,"score_spread":0.18123254813553863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2997053614","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":[0.9545335,0.00015397416,0.044596933,0.000007990142,0.000107815285,0.00044029133,0.000009100033,0.000002803011,0.00014755595],"genre_scores_gemma":[0.9972555,0.000008432969,0.002312772,0.000024822308,0.00003534506,0.000011977857,0.000051810326,0.000008203169,0.0002911319],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990291,0.000040190087,0.00045459115,0.00012573514,0.00021151369,0.00013889009],"domain_scores_gemma":[0.9990517,0.000017186463,0.0004253566,0.00045340142,0.000028122644,0.000024216262],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002406128,0.000108717824,0.00016303362,0.000030134886,0.000023929038,0.000003677545,0.0001262181,0.00010710266,0.000023250766],"category_scores_gemma":[0.000021426145,0.000081337006,0.0001021811,0.0001253125,0.000060285325,0.0000070541064,0.0001406182,0.000051390158,0.0000040856585],"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":[0.00014275526,0.000057359153,0.012967882,0.00008066083,0.00006455838,1.1173786e-8,0.00023086485,0.8972833,0.084952824,0.00001894186,0.00083169807,0.0033691393],"study_design_scores_gemma":[0.0016358668,0.000622247,0.0713605,0.00013863265,0.00012674251,0.0000010595328,0.0007739938,0.8283441,0.09614475,0.00018039995,0.0003982468,0.00027342842],"about_ca_topic_score_codex":0.0000080637365,"about_ca_topic_score_gemma":0.000011943812,"teacher_disagreement_score":0.06893917,"about_ca_system_score_codex":0.000031014344,"about_ca_system_score_gemma":0.00004734723,"threshold_uncertainty_score":0.33168268},"labels":[],"label_agreement":null},{"id":"W2997403971","doi":"10.1186/s12864-019-6298-5","title":"D3GRN: a data driven dynamic network construction method to infer gene regulatory networks","year":2019,"lang":"en","type":"article","venue":"BMC Genomics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"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 Saskatchewan","funders":"Higher Education Discipline Innovation Project; National Natural Science Foundation of China","keywords":"Gene regulatory network; Biology; Computational biology; DNA microarray; Gene; Genetics; Gene expression","score_opus":0.012209240042838701,"score_gpt":0.25702316077981013,"score_spread":0.24481392073697145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2997403971","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":[0.59331256,0.0009245839,0.40472722,0.000034842662,0.00045762002,0.0003633449,0.000026917305,0.000025455689,0.00012746047],"genre_scores_gemma":[0.64648724,0.00015583169,0.34946534,0.0004277845,0.0011462509,0.000019684434,0.0013043877,0.00009293979,0.0009005198],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99762064,0.00021502307,0.0004266799,0.0010122346,0.00017504675,0.00055035675],"domain_scores_gemma":[0.9970174,0.000027363958,0.00019470385,0.0024436046,0.00010067757,0.00021627959],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006321444,0.0003103527,0.00037534515,0.0000750292,0.00011344257,0.00005442955,0.00081032625,0.00033198047,0.000058774614],"category_scores_gemma":[0.000021973627,0.00034371798,0.00016594224,0.0002988793,0.000058095706,0.000009184412,0.0009990877,0.00014691507,0.00010726439],"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":[0.00009808173,0.000020144102,0.01773393,0.000011827856,0.00023364605,0.0000011635801,0.000016660006,0.7871173,0.18338342,0.000080144135,0.0030849956,0.008218652],"study_design_scores_gemma":[0.0015080271,0.00030290624,0.035677105,0.000042139367,0.00049812987,0.00013478778,0.00014527116,0.82692856,0.020756077,0.00031584105,0.112077504,0.0016136889],"about_ca_topic_score_codex":0.00001119027,"about_ca_topic_score_gemma":0.00024770905,"teacher_disagreement_score":0.16262735,"about_ca_system_score_codex":0.00008990028,"about_ca_system_score_gemma":0.00020325463,"threshold_uncertainty_score":0.9999015},"labels":[],"label_agreement":null},{"id":"W2999309601","doi":"10.1016/j.cels.2019.12.001","title":"Cellular Dialogues: Cell-Cell Communication through Diffusible Molecules Yields Dynamic Spatial Patterns","year":2020,"lang":"en","type":"article","venue":"Cell Systems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":32,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Institute for Advanced Research","funders":"European Research Council; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Canadian Institute for Advanced Research; EMBO; European Molecular Biology Organization","keywords":"Cell; Cell signaling; Biology; Cell biology; Computer science; Computational biology; Biological system; Signal transduction; Genetics","score_opus":0.012479838163256422,"score_gpt":0.20614827379176268,"score_spread":0.19366843562850625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2999309601","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":[0.90159994,0.012847011,0.08084377,0.00013340627,0.00027500122,0.000432905,0.00004612286,0.000051243584,0.0037705791],"genre_scores_gemma":[0.9962537,0.0007625637,0.00024946604,0.00021848081,0.00037876642,0.000038854534,0.0011063184,0.000070262045,0.0009215562],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998069,0.00029943758,0.00045357613,0.0005821095,0.00024154045,0.00035433273],"domain_scores_gemma":[0.99844515,0.000018418368,0.00027416303,0.0010053865,0.00008760984,0.00016928582],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013701574,0.0003128974,0.00035467092,0.00003113709,0.00014344805,0.00007928565,0.00060267746,0.00031515685,0.00002985171],"category_scores_gemma":[0.000009083672,0.0003205205,0.00023685332,0.00014697642,0.00006106695,0.0000071160916,0.0002869803,0.00017113783,0.00012594783],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002933894,0.00015212147,0.004045886,0.00037299102,0.00007383048,0.000009235148,0.00040967064,0.009602375,0.9826985,0.000011023997,0.0025144026,0.000080598074],"study_design_scores_gemma":[0.0015872219,0.00041233568,0.00045065966,0.00006313437,0.00030606496,0.0000049208925,0.0012836787,0.05051758,0.9130312,0.000025525633,0.03132089,0.0009967698],"about_ca_topic_score_codex":0.00068224757,"about_ca_topic_score_gemma":0.00013879346,"teacher_disagreement_score":0.09465377,"about_ca_system_score_codex":0.000032611904,"about_ca_system_score_gemma":0.00005671497,"threshold_uncertainty_score":0.99992466},"labels":[],"label_agreement":null},{"id":"W3000355524","doi":"10.1016/j.idm.2019.12.010","title":"A primer on model selection using the Akaike Information Criterion","year":2020,"lang":"en","type":"article","venue":"Infectious Disease Modelling","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":487,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Akaike information criterion; Selection (genetic algorithm); Bayesian information criterion; Model selection; Workflow; Minimum description length; Computer science; Calibration; Computation; Data collection; Mathematical model; Information Criteria; Data mining; Statistics; Machine learning; Mathematics; Artificial intelligence; Algorithm","score_opus":0.02207519264189321,"score_gpt":0.24227967193965982,"score_spread":0.22020447929776663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3000355524","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":[0.50264156,0.000088356515,0.49692413,0.00009894432,0.000028158309,0.000105921485,0.000003658587,0.000025567511,0.00008370355],"genre_scores_gemma":[0.9975952,0.000043792603,0.0005570901,0.00142072,0.00027827616,0.00001567324,0.00005645807,0.000019315905,0.000013476297],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999205,0.000053163785,0.00018727955,0.00021648311,0.00016250105,0.00017560567],"domain_scores_gemma":[0.99947053,0.0000045703723,0.00008839043,0.0001930503,0.000103275706,0.00014018625],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008355145,0.00014606264,0.00009229527,0.00004340381,0.00023254083,0.000064347936,0.00008896763,0.00006983159,0.0000061077462],"category_scores_gemma":[0.000021433465,0.00012451848,0.00013708965,0.000177361,0.000025063748,0.000018440891,0.000043302673,0.00009428976,0.0000126412015],"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":[0.000087273096,0.000019268866,0.0007630851,0.000013123369,0.000047831385,2.3766968e-7,0.000090318346,0.98838526,0.009959781,0.000056299657,0.0001622308,0.00041528838],"study_design_scores_gemma":[0.00017151263,0.000052996147,0.000039051458,0.000007662635,0.00008219457,0.0000016412599,0.000011006702,0.9946501,0.0034280634,0.00015850249,0.001250911,0.00014632192],"about_ca_topic_score_codex":0.000015764826,"about_ca_topic_score_gemma":0.0000025097768,"teacher_disagreement_score":0.49636704,"about_ca_system_score_codex":0.00003365802,"about_ca_system_score_gemma":0.000092585695,"threshold_uncertainty_score":0.5077717},"labels":[],"label_agreement":null},{"id":"W3001250673","doi":"10.1101/2020.01.21.914598","title":"Geometric models for robust encoding of dynamical information into embryonic patterns","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft","keywords":"Bifurcation; Function (biology); Segmentation; Encoding (memory); Dynamics (music); Dynamical systems theory; Computer science; Biology; Topology (electrical circuits); Evolutionary biology; Statistical physics; Biological system; Physics; Mathematics; Artificial intelligence; Combinatorics","score_opus":0.014625933345012259,"score_gpt":0.21524225098838154,"score_spread":0.2006163176433693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3001250673","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":[0.64384604,0.0008023324,0.35403824,0.00011065573,0.0003088554,0.0005699607,0.000265365,0.00005445741,0.0000041065014],"genre_scores_gemma":[0.9846404,0.00037964655,0.014206084,0.000106363914,0.00039105085,0.00017410723,0.000019026189,0.000081489816,0.0000018301287],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9977434,0.00007962028,0.0007002588,0.00072331517,0.00032982876,0.00042355346],"domain_scores_gemma":[0.99741596,0.000026194368,0.0006646584,0.0010369053,0.00063053623,0.0002257405],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000418132,0.00046291313,0.00060677825,0.0003996298,0.000096982425,0.00008934829,0.0006428373,0.0006966658,0.000007043174],"category_scores_gemma":[0.00022156918,0.0005288941,0.00042197166,0.00057832035,0.00006880409,0.000025198955,0.0007055861,0.00031052923,0.000006018716],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000113521935,0.00010124174,0.00545662,0.0018876375,0.00091689185,0.0000028024851,0.000015827263,0.12248038,0.8681215,0.00038487912,0.0004957963,0.000022878026],"study_design_scores_gemma":[0.0013806332,0.00033458826,0.012246261,0.00035529566,0.00079745904,3.1374068e-8,0.000015278625,0.27746958,0.7035114,0.000031072057,0.002126513,0.0017318808],"about_ca_topic_score_codex":0.000026764064,"about_ca_topic_score_gemma":0.000004588181,"teacher_disagreement_score":0.34079438,"about_ca_system_score_codex":0.00013943212,"about_ca_system_score_gemma":0.00045163863,"threshold_uncertainty_score":0.9997163},"labels":[],"label_agreement":null},{"id":"W3004418897","doi":"10.1063/1.5143259","title":"Robust oscillations in multi-cyclic Markov state models of biochemical clocks","year":2020,"lang":"en","type":"article","venue":"The Journal of Chemical Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"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; Alfred P. Sloan Foundation; National Science Foundation","keywords":"Randomness; Coherence (philosophical gambling strategy); Markov chain; Markov process; Degenerate energy levels; Basis (linear algebra); Energy (signal processing); Stochastic process","score_opus":0.03339461253648154,"score_gpt":0.24360344811682513,"score_spread":0.2102088355803436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3004418897","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":[0.98337436,0.00065023365,0.01538195,0.00045924733,0.00001961905,0.00005385943,0.0000073769966,0.0000021695928,0.00005120071],"genre_scores_gemma":[0.99776477,0.00015401331,0.0016329498,0.00016049115,0.00024590705,6.515173e-7,0.000009776496,0.000016519873,0.000014949986],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990008,0.000068785936,0.0004460784,0.00012032773,0.00020407587,0.00015991677],"domain_scores_gemma":[0.9992139,0.00003139006,0.00030274494,0.0002035112,0.00014115509,0.00010731734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017661451,0.00012370519,0.0002640043,0.000018192633,0.000015825433,0.0000051918873,0.00032202507,0.000080727805,0.000004920476],"category_scores_gemma":[0.00004672884,0.00009310222,0.00019721861,0.00024341507,0.000119730204,0.0000066876773,0.00011569594,0.000210746,8.6060317e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011131797,0.00007067909,0.00035726267,0.000011405437,0.00008440769,7.3982477e-7,0.00009793277,0.1200749,0.87803364,0.000007634675,0.00090066815,0.00024942314],"study_design_scores_gemma":[0.00070400833,0.00006754232,0.0001545107,0.000019626681,0.000095700656,0.000007630572,0.000033149656,0.03631931,0.9613686,0.0009759887,0.00012636253,0.00012757539],"about_ca_topic_score_codex":0.0000027261938,"about_ca_topic_score_gemma":6.161637e-7,"teacher_disagreement_score":0.08375559,"about_ca_system_score_codex":0.00001664802,"about_ca_system_score_gemma":0.0000619175,"threshold_uncertainty_score":0.37965983},"labels":[],"label_agreement":null},{"id":"W3012535847","doi":"10.1016/j.mbs.2020.108387","title":"Delay stability of reaction systems","year":2020,"lang":"en","type":"preprint","venue":"Mathematical Biosciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"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; National Science Foundation","keywords":"Stability (learning theory); Exponential stability; Work (physics); Delay differential equation; Mathematics; Action (physics); Applied mathematics; Control theory (sociology); Differential equation; Computer science; Physics; Mathematical analysis; Thermodynamics; Nonlinear system; Control (management)","score_opus":0.0328610087079921,"score_gpt":0.27149579641530797,"score_spread":0.23863478770731586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3012535847","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":[0.98853016,0.0006568344,0.008419879,0.00019873821,0.00026642648,0.00027577596,0.000029665505,0.000018499968,0.0016039972],"genre_scores_gemma":[0.9980986,0.000053570006,0.0015560378,0.000017526976,0.0001495046,0.000022336859,0.000035670266,0.000010074846,0.000056645757],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99830955,0.000115107745,0.00045794775,0.0005682365,0.00036767017,0.00018150112],"domain_scores_gemma":[0.9988691,0.000026352318,0.00029296367,0.0005882461,0.000110729416,0.000112570466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005402992,0.00018559486,0.00039003912,0.000040165487,0.000044679284,0.000039110524,0.00045127407,0.00026088324,0.00001714055],"category_scores_gemma":[0.0002516797,0.00014746316,0.00021287131,0.00016942053,0.00032951243,0.0000020625118,0.000519814,0.00012935663,0.000012459296],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022229218,0.00016429256,0.0009830267,0.0010205002,0.00014643228,0.0000016498129,0.00014849968,0.0005477042,0.99452984,0.0015289141,0.0004407191,0.0004662074],"study_design_scores_gemma":[0.00037376245,0.0007529242,0.0025604013,0.0004911901,0.0006544959,0.000035379533,0.0015969658,0.060930252,0.8992758,0.027131025,0.004730196,0.0014676003],"about_ca_topic_score_codex":0.0000215848,"about_ca_topic_score_gemma":0.000006347223,"teacher_disagreement_score":0.09525402,"about_ca_system_score_codex":0.000016808337,"about_ca_system_score_gemma":0.0001349124,"threshold_uncertainty_score":0.6013373},"labels":[],"label_agreement":null},{"id":"W3018611246","doi":"10.1096/fasebj.2020.34.s1.00347","title":"Spatiotemporal control of gene expression boundaries using a feedforward loop","year":2020,"lang":"en","type":"article","venue":"The FASEB Journal","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Morphogen; Feed forward; Dorsum; Transcription factor; Biological system; Multiplicative function; Computer science; Biology; Physics; Computational biology; Gene; Mathematics; Genetics; Anatomy; Engineering","score_opus":0.01639282071250673,"score_gpt":0.2371295556615304,"score_spread":0.22073673494902368,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3018611246","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":[0.9151528,0.0015830225,0.08265043,0.00044199752,0.00007564005,0.000058329893,0.000009161848,0.0000032154412,0.00002541976],"genre_scores_gemma":[0.9973785,0.000036356483,0.0016088826,0.00028521166,0.0006328503,7.387837e-7,0.000009177018,0.000014261805,0.000033980643],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991323,0.00013461534,0.00025659933,0.00012624897,0.00018881432,0.00016146176],"domain_scores_gemma":[0.9993357,0.0000066138155,0.00025453704,0.00018547756,0.000107836684,0.00010982721],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024563842,0.00010695682,0.00017548466,0.000021504904,0.00025656505,0.000060504175,0.0002185846,0.00006660504,0.000041231157],"category_scores_gemma":[0.000046303325,0.00007330126,0.00017808497,0.00008921015,0.00016362933,0.000004488323,0.000050895636,0.00011747431,0.0000022040717],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015074204,0.000010377841,0.005323951,0.000005568561,0.00013160307,0.000003771018,0.000105511244,0.008223776,0.9852131,0.0000038289236,0.0005153824,0.00031236192],"study_design_scores_gemma":[0.00058865146,0.0001261069,0.00033360324,0.000011165354,0.00011502793,0.00006165345,0.00012035406,0.0055101905,0.99154574,0.000031298594,0.0014640107,0.00009219573],"about_ca_topic_score_codex":0.0000060912694,"about_ca_topic_score_gemma":0.0000022752458,"teacher_disagreement_score":0.08222576,"about_ca_system_score_codex":0.0000102507565,"about_ca_system_score_gemma":0.00017245537,"threshold_uncertainty_score":0.29891384},"labels":[],"label_agreement":null},{"id":"W3023576658","doi":"10.5206/mase/10267","title":"Viewpoints on modelling: Comments on \"Achilles and the tortoise: Some caveats to mathematical modelling in biology\"","year":2020,"lang":"en","type":"article","venue":"Mathematics in Applied Sciences and Engineering","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Viewpoints; Confusion; Management science; Epistemology; Computer science; Engineering ethics; Data science; Psychology; Philosophy; Engineering; Physics","score_opus":0.027587956462409236,"score_gpt":0.24838181554680308,"score_spread":0.22079385908439383,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3023576658","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":[0.9190904,0.00031245395,0.07909815,0.00071090995,0.00001704222,0.00025910945,0.0000015085293,0.000008456688,0.0005019954],"genre_scores_gemma":[0.9854661,0.00016050594,0.01386455,0.00042110583,0.000041437946,0.000029601704,0.0000015576092,0.000011096781,0.000004030094],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991218,0.000013924919,0.00024309923,0.00029781237,0.00011461305,0.00020878675],"domain_scores_gemma":[0.9996786,0.00006381813,0.00003500541,0.00013965218,0.0000046567247,0.0000782542],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050287374,0.00014569827,0.00023450566,0.00006853843,0.00006175599,0.000034756977,0.00016721716,0.000062584855,0.0000013891115],"category_scores_gemma":[0.00002453239,0.00010214274,0.000027383307,0.00017149728,0.0000886019,0.0000026302405,0.00010838822,0.00010054823,0.0000026284001],"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":[0.000015860773,0.000022332642,0.000032662963,0.000040972325,0.000009681914,4.034922e-7,0.0005112348,0.9441152,0.0024776824,0.05256706,0.0000070035903,0.00019987761],"study_design_scores_gemma":[0.0003390654,0.000057908746,0.00000889444,0.000054992004,0.0000066760686,0.0000010060089,0.00014492235,0.9904277,0.0012958514,0.0074457675,0.000089692156,0.00012754773],"about_ca_topic_score_codex":0.0000018519806,"about_ca_topic_score_gemma":0.0000013986645,"teacher_disagreement_score":0.06637574,"about_ca_system_score_codex":0.0000098534265,"about_ca_system_score_gemma":0.0000063439934,"threshold_uncertainty_score":0.41652602},"labels":[],"label_agreement":null},{"id":"W3025634535","doi":"10.1016/j.mbs.2020.108376","title":"Small binding-site clearance delays are not negligible in gene expression modeling","year":2020,"lang":"en","type":"article","venue":"Mathematical Biosciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Binding site; Ribosome; Transcription (linguistics); Gene expression; Gene; RNA; Bistability; Messenger RNA; RNA polymerase; Biology; Ribosomal binding site; Biophysics; Computational biology; Physics; Cell biology; Genetics; Quantum mechanics","score_opus":0.040328251121417406,"score_gpt":0.246433141676213,"score_spread":0.20610489055479558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3025634535","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":[0.97259754,0.0002805563,0.026146866,0.00058955577,0.000029057925,0.00010222227,0.0000062548575,0.000018096576,0.0002298398],"genre_scores_gemma":[0.98920465,0.00006382664,0.0101678725,0.0003751113,0.00010060494,0.000010312951,0.000008297354,0.000011893257,0.000057417365],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9986299,0.000049361817,0.00028742146,0.00049801305,0.00022529288,0.00030999334],"domain_scores_gemma":[0.9994759,0.00001301391,0.00008333362,0.00023807255,0.000033282173,0.00015638521],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024955583,0.00014950898,0.00021780563,0.000053047283,0.000094057126,0.0000530009,0.0003418537,0.00011120091,0.000021221775],"category_scores_gemma":[0.0001381586,0.00012107549,0.00009581164,0.00038967552,0.000099585,0.000007297622,0.00018376853,0.00008151524,0.00008208978],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026764608,0.00004609734,0.0015645613,0.00003545155,0.00000617726,0.000004581473,0.000118857926,0.016098889,0.981805,0.00004438963,0.00007796073,0.00017125452],"study_design_scores_gemma":[0.00021986307,0.00009573829,0.00021265204,0.000067954796,0.000014894334,0.0000047049293,0.00018040412,0.3541624,0.64422786,0.000352545,0.00019725924,0.00026372334],"about_ca_topic_score_codex":0.0000031980546,"about_ca_topic_score_gemma":0.000009943481,"teacher_disagreement_score":0.3380635,"about_ca_system_score_codex":0.000009166401,"about_ca_system_score_gemma":0.00002986726,"threshold_uncertainty_score":0.49373153},"labels":[],"label_agreement":null},{"id":"W3036300597","doi":"10.1111/1751-7915.13612","title":"Are synthetic biology standards applicable in everyday research practice?","year":2020,"lang":"en","type":"article","venue":"Microbial Biotechnology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Horizon 2020 Framework Programme; Fondation Bettencourt Schueller; European Commission","keywords":"Standardization; Synthetic biology; Caucus; Engineering ethics; Management science; Computer science; Data science; Biology; Political science; Computational biology; Engineering","score_opus":0.023400471422729267,"score_gpt":0.3104564543360659,"score_spread":0.2870559829133366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3036300597","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":[0.96186656,0.0034026217,0.0031082074,0.030081267,0.00011944737,0.0005217717,0.00010915692,0.000099007724,0.000691959],"genre_scores_gemma":[0.9967822,0.00048287094,0.0011576809,0.0011400068,0.00022145572,0.000035736884,0.00004808736,0.000038036775,0.00009393461],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99753207,0.00037337813,0.0003429566,0.0008955833,0.00016875417,0.00068728003],"domain_scores_gemma":[0.9987905,0.00004198555,0.00016635134,0.00064842677,0.00024479153,0.000107918095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009768922,0.00021473515,0.00036311251,0.0002442261,0.00011684191,0.000023022852,0.00060018356,0.0009655187,0.000065265325],"category_scores_gemma":[0.0011818582,0.00022245361,0.00010709327,0.00096244446,0.0005223741,0.000004511754,0.00058888603,0.000580055,0.00009836997],"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":[0.00018544243,0.0000731696,0.000990303,0.000016682256,0.000070910646,0.000026521184,0.000025518875,0.00015130662,0.98331827,0.00036789567,0.01207603,0.0026979279],"study_design_scores_gemma":[0.0003820989,0.00022113956,0.00007198923,0.000008872236,0.00001564614,0.000027142478,0.00018037665,0.000052649764,0.44992968,0.00010829319,0.5488247,0.00017739538],"about_ca_topic_score_codex":0.000051911353,"about_ca_topic_score_gemma":0.00018436818,"teacher_disagreement_score":0.5367487,"about_ca_system_score_codex":0.00009693821,"about_ca_system_score_gemma":0.00017326046,"threshold_uncertainty_score":0.90713954},"labels":[],"label_agreement":null},{"id":"W3039123993","doi":"10.4018/ijhiot.2020070105","title":"Alternative Generation in Complex Decision Modelling Using a Firefly Algorithm Metaheuristic Approach","year":2020,"lang":"en","type":"article","venue":"International Journal of Hyperconnectivity and the Internet of Things","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Firefly algorithm; Benchmark (surveying); Metaheuristic; Computer science; Mathematical optimization; Set (abstract data type); Construct (python library); Algorithm; Mathematics","score_opus":0.04667345722033376,"score_gpt":0.2726082047840562,"score_spread":0.22593474756372242,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3039123993","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":[0.5450871,0.0004338971,0.45415014,0.0001891297,0.000072590825,0.0000403212,0.00000197687,8.2509973e-7,0.00002403046],"genre_scores_gemma":[0.96674144,0.00015756213,0.03241515,0.00029665304,0.0003634315,0.000001013379,0.000009627383,0.000009944075,0.0000051529914],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988134,0.00016633344,0.00044396124,0.00017970608,0.00031071322,0.00008591992],"domain_scores_gemma":[0.9991079,0.000073816955,0.00039658518,0.00008330125,0.00029060311,0.000047785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069421297,0.00011572847,0.00028776066,0.00009340046,0.000024127465,0.000041289808,0.00036329473,0.000057809135,0.0000067597657],"category_scores_gemma":[0.00019015055,0.00008524874,0.0001739605,0.00007291877,0.000108032815,0.000037267804,0.00015808013,0.00015873005,2.0221282e-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":[0.0020324953,0.00025016078,0.0011026104,0.000021826987,0.0018246216,0.00003778442,0.004077366,0.85182035,0.11199158,0.0012067232,0.00016386766,0.025470607],"study_design_scores_gemma":[0.0013494549,0.00009984485,0.00006039214,0.000025483318,0.00007028801,0.00014408903,0.00012252173,0.98452777,0.012107291,0.0012054687,0.00020579553,0.00008162299],"about_ca_topic_score_codex":0.00021982187,"about_ca_topic_score_gemma":0.0000074319064,"teacher_disagreement_score":0.421735,"about_ca_system_score_codex":0.0000280089,"about_ca_system_score_gemma":0.000031586143,"threshold_uncertainty_score":0.3476343},"labels":[],"label_agreement":null},{"id":"W3041336646","doi":"10.1073/pnas.1921625117","title":"Behavior-related gene regulatory networks: A new level of organization in the brain","year":2020,"lang":"en","type":"review","venue":"Proceedings of the National Academy of Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":86,"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; Canadian Institute for Advanced Research","funders":"","keywords":"Gene regulatory network; Heuristic; Biology; Neuroscience; Spatial organization; Computer science; Gene; Evolutionary biology; Artificial intelligence; Genetics; Gene expression","score_opus":0.07230272177443532,"score_gpt":0.32490785584745185,"score_spread":0.25260513407301655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3041336646","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014037617,0.98416424,0.000013079464,0.0008554439,0.000029263143,0.0006636344,0.000031938842,0.000004822789,0.00019995363],"genre_scores_gemma":[0.28443092,0.71390545,0.0007015928,0.00022269292,0.00036020856,0.000023419167,0.000019147103,0.000030538624,0.00030603833],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99791676,0.000043394004,0.0007322306,0.0003669688,0.0007957294,0.00014491462],"domain_scores_gemma":[0.99839973,0.000052387037,0.0012081389,0.000029079438,0.0002759804,0.000034669913],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001344041,0.00019138286,0.00052630116,0.00015243846,0.00007905994,0.00001421337,0.001455955,0.00034547498,0.0000070930596],"category_scores_gemma":[0.00054544845,0.00011832197,0.00024374324,0.0027945729,0.00046582808,0.000013346546,0.00023782798,0.00021439826,4.5149574e-7],"study_design_candidate":"not_applicable","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":[0.000050701914,0.00070344424,0.007516304,0.006721192,0.0017191507,2.7936744e-7,0.0011852973,0.008297821,0.2816069,0.02478384,0.06412197,0.60329306],"study_design_scores_gemma":[0.0028695418,0.0010455907,0.09971489,0.017671239,0.007429271,0.0005650694,0.0008842913,0.0034480116,0.23297472,0.012711003,0.6168242,0.0038621554],"about_ca_topic_score_codex":0.0000041289186,"about_ca_topic_score_gemma":2.6062847e-7,"teacher_disagreement_score":0.5994309,"about_ca_system_score_codex":0.00002772633,"about_ca_system_score_gemma":0.00024526272,"threshold_uncertainty_score":0.482503},"labels":[],"label_agreement":null},{"id":"W3043017930","doi":"10.1016/j.ecocom.2020.100855","title":"Organizations in reaction-diffusion systems: Effects of diffusion and boundary conditions","year":2020,"lang":"en","type":"article","venue":"Ecological Complexity","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Deutsche Forschungsgemeinschaft; Carl-Zeiss-Stiftung","keywords":"Diffusion; Reaction–diffusion system; Ordinary differential equation; Partial differential equation; Boundary value problem; Boundary (topology); Computer science; Dirichlet boundary condition; Focus (optics); Mathematics; Applied mathematics; Differential equation; Mathematical analysis; Physics; Thermodynamics","score_opus":0.01468921510871834,"score_gpt":0.23894714526045874,"score_spread":0.2242579301517404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3043017930","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":[0.9983623,0.00034540572,0.00057207595,0.00026223142,0.000054428005,0.00020610096,0.000011421564,0.000014299276,0.00017173235],"genre_scores_gemma":[0.9993024,0.00008972383,0.00015429138,0.00016161596,0.00007367235,0.0000116385345,0.00016841566,0.000006957537,0.000031302534],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99920607,0.00014567756,0.00020387524,0.00024938257,0.000077268756,0.00011770747],"domain_scores_gemma":[0.9995887,0.000043924723,0.00008173824,0.00013069536,0.000066246124,0.000088665554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006815449,0.000093324496,0.00019828376,0.000029434443,0.00010852083,0.000011480856,0.00008136756,0.00011919342,0.000039668543],"category_scores_gemma":[0.00025801614,0.000083666484,0.00003825528,0.00026174437,0.0001552712,0.0000030407077,0.00015773425,0.000075293014,0.0000043069053],"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":[0.00003430757,0.00027605088,0.11796908,0.00010751906,0.000042169897,0.0000070425326,0.000060922368,0.00028826797,0.8790782,0.0010302444,0.0010221674,0.0000840153],"study_design_scores_gemma":[0.0006045809,0.0003713745,0.9842264,0.000015977486,0.00003781633,0.0000063980024,0.00006785768,0.0041568577,0.0073725856,0.0004909102,0.0025014998,0.00014772976],"about_ca_topic_score_codex":0.000017287259,"about_ca_topic_score_gemma":0.00006966579,"teacher_disagreement_score":0.87170565,"about_ca_system_score_codex":0.000015604572,"about_ca_system_score_gemma":0.000028547394,"threshold_uncertainty_score":0.341182},"labels":[],"label_agreement":null},{"id":"W3043779982","doi":"10.1002/9781394229086.ch6","title":"Computational Logic for Biomedicine and Neurosciences","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Ottawa","funders":"","keywords":"Biomedicine; Computer science; Mathematical proof; Computational logic; Artificial intelligence; Archetype; AND gate; Theoretical computer science; Cognitive science; Logic gate; Description logic; Algorithm; Mathematics; Biology","score_opus":0.03564036088582057,"score_gpt":0.302425659838379,"score_spread":0.2667852989525584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3043779982","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":[0.6789368,0.0025114664,0.31013036,0.0048678587,0.0020668874,0.0008775106,0.00014330076,0.000097381875,0.0003684741],"genre_scores_gemma":[0.98181623,0.00028896466,0.010811463,0.0005228668,0.0005249182,0.000059532427,0.00094700727,0.000023668743,0.005005353],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991036,0.000019969697,0.00014942818,0.00048511618,0.000105626146,0.00013624887],"domain_scores_gemma":[0.99959856,0.000021030191,0.00007015707,0.0001841768,0.00006875079,0.00005731555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018072635,0.00012628878,0.00015205183,0.00007067759,0.000059481896,0.00002635144,0.00014550691,0.00014262873,0.00000541133],"category_scores_gemma":[0.00004551629,0.000104816405,0.00008355268,0.000074861644,0.0001365819,4.2227853e-7,0.00039338748,0.00004727509,0.000002132809],"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":[0.00015907217,0.00023425971,0.02439589,0.0009613204,0.0012004012,0.000014938242,0.00008552613,0.56661797,0.18040603,0.003785637,0.20779414,0.014344812],"study_design_scores_gemma":[0.0027199143,0.0020381457,0.06360026,0.00014748854,0.0008463573,0.00006114145,0.00041863142,0.6952083,0.01570825,0.13706699,0.0796294,0.0025551193],"about_ca_topic_score_codex":0.0000068427967,"about_ca_topic_score_gemma":0.000014960241,"teacher_disagreement_score":0.30287945,"about_ca_system_score_codex":0.0000037375735,"about_ca_system_score_gemma":0.00006354519,"threshold_uncertainty_score":0.4274289},"labels":[],"label_agreement":null},{"id":"W3046424967","doi":"10.1101/2020.08.02.233619","title":"Nonlinear delay differential equations and their application to modeling biological network motifs","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"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":"Ode; Network motif; Biological network; Ordinary differential equation; Nonlinear system; Computer science; Gene regulatory network; Feed forward; Delay differential equation; Differential equation; Theoretical computer science; Mathematics; Applied mathematics; Physics; Control engineering; Biology","score_opus":0.017241309666678112,"score_gpt":0.22206389144954083,"score_spread":0.20482258178286272,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3046424967","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":[0.5554067,0.0009990587,0.44269806,0.00015376833,0.00014972007,0.00041265,0.00007386934,0.00010549214,7.005682e-7],"genre_scores_gemma":[0.9879327,0.0003018473,0.009083359,0.0002850966,0.0020253742,0.00023050899,0.000013168877,0.00012669913,0.000001277704],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973477,0.00015136346,0.00048923644,0.0013535356,0.00017070709,0.00048742077],"domain_scores_gemma":[0.9980209,0.000022562364,0.00021676823,0.0010562399,0.0002845322,0.00039900298],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00026320154,0.00054175913,0.0005214842,0.000088954264,0.00017154812,0.00012117468,0.0004774369,0.0006777513,0.0000056169742],"category_scores_gemma":[0.000121408324,0.00051737996,0.00021541379,0.00034415312,0.000073262556,0.000004818598,0.001086873,0.00037767598,0.000014632964],"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":[0.00004114427,0.00006162187,0.0016791616,0.00004355889,0.00030876504,0.0000020572504,0.0000059689432,0.0918529,0.905739,0.00010599529,0.00014963115,0.000010205004],"study_design_scores_gemma":[0.00043360997,0.00018244337,0.0046836,0.00009501754,0.00026091153,3.5463835e-8,0.000005230178,0.8685281,0.119752556,0.000018967334,0.004690641,0.0013488783],"about_ca_topic_score_codex":0.000014996739,"about_ca_topic_score_gemma":0.000006505275,"teacher_disagreement_score":0.7859864,"about_ca_system_score_codex":0.000053208958,"about_ca_system_score_gemma":0.00018342056,"threshold_uncertainty_score":0.9997278},"labels":[],"label_agreement":null},{"id":"W3048608287","doi":"10.7554/elife.55778","title":"Geometric models for robust encoding of dynamical information into embryonic patterns","year":2020,"lang":"en","type":"article","venue":"eLife","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft; Simons Foundation","keywords":"Bifurcation; Function (biology); Segmentation; Biology; Dynamics (music); Encoding (memory); Dynamical systems theory; Topology (electrical circuits); Computer science; Evolutionary biology; Statistical physics; Physics; Artificial intelligence; Mathematics; Neuroscience; Combinatorics","score_opus":0.016659695165046,"score_gpt":0.22991428025149896,"score_spread":0.21325458508645295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3048608287","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":[0.5727977,0.00016859945,0.4266848,0.00015829086,0.000027578957,0.00008823527,0.000013202091,0.0000064539836,0.000055096876],"genre_scores_gemma":[0.9958159,0.00008957916,0.0033579206,0.00031179594,0.00014262322,0.000012873685,0.00024274708,0.000009129241,0.000017430313],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993782,0.00001580923,0.00021172053,0.0001350627,0.00013027056,0.00012890338],"domain_scores_gemma":[0.9995513,0.000008807832,0.0001019228,0.00015205004,0.000110728215,0.000075176344],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010258471,0.00008281374,0.00013278787,0.00006690507,0.000032731023,0.000010743981,0.00013558954,0.00007726496,0.000005914383],"category_scores_gemma":[0.000080534846,0.00008337067,0.00012285003,0.00021163361,0.000015195527,0.000009357432,0.00007682072,0.000036251215,0.000003817998],"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":[0.00013019495,0.000045275287,0.0075502144,0.00030838817,0.0003159492,4.311962e-7,0.00034495877,0.88169307,0.08771251,0.0001909523,0.0048615183,0.016846562],"study_design_scores_gemma":[0.00066832535,0.00028341875,0.0019188925,0.000013001782,0.000087090535,0.0000014193478,0.00015101922,0.8896548,0.1024287,0.00003714119,0.0045069167,0.00024926968],"about_ca_topic_score_codex":0.0000066070406,"about_ca_topic_score_gemma":0.000007251084,"teacher_disagreement_score":0.42332688,"about_ca_system_score_codex":0.00001268179,"about_ca_system_score_gemma":0.00003791643,"threshold_uncertainty_score":0.33997574},"labels":[],"label_agreement":null},{"id":"W3079594492","doi":"10.1007/978-3-030-57821-3_3","title":"SPOC: Identification of Drug Targets in Biological Networks via Set Preference Output Control","year":2020,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Set (abstract data type); Biological network; Realization (probability); Matching (statistics); Control (management); Identification (biology); Preference; Artificial intelligence; Computational biology; Mathematics; Biology","score_opus":0.01584496413489106,"score_gpt":0.22572914149453566,"score_spread":0.2098841773596446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3079594492","genre_codex":"methods","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":[0.009523805,0.001980037,0.98763967,0.00014617389,0.00030184365,0.00030379766,0.000014167796,0.000011452364,0.00007908107],"genre_scores_gemma":[0.9953328,0.00015284913,0.0036423139,0.0003323201,0.0003467543,0.000007738547,0.000096342694,0.000018322276,0.00007057884],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976738,0.000073634015,0.00058992574,0.0010399838,0.00029800597,0.00032462153],"domain_scores_gemma":[0.9987096,0.00006216358,0.00036321796,0.00062294933,0.00014793163,0.000094142524],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00059194496,0.00032114805,0.0004836582,0.00019427693,0.00005022481,0.00003839389,0.0008896178,0.0003898113,0.000008809959],"category_scores_gemma":[0.00006993891,0.0002885586,0.00014701477,0.0002673611,0.00048502302,0.000006975232,0.0003434891,0.00034045306,0.000004774874],"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":[0.000101757476,0.000050209113,0.005018674,0.00004643569,0.000082738916,0.000021617183,0.00017485637,0.8496031,0.055488534,0.00016524819,0.000084648156,0.08916214],"study_design_scores_gemma":[0.0009395819,0.00038471806,0.008538354,0.00019191578,0.00007042746,0.000023679764,7.84904e-7,0.93534744,0.039332315,0.012579825,0.0014567215,0.0011342543],"about_ca_topic_score_codex":0.000009391816,"about_ca_topic_score_gemma":0.000086256754,"teacher_disagreement_score":0.98580897,"about_ca_system_score_codex":0.00005077955,"about_ca_system_score_gemma":0.00013707002,"threshold_uncertainty_score":0.99995667},"labels":[],"label_agreement":null},{"id":"W3080133182","doi":"10.15252/msb.20199110","title":"SBML Level 3: an extensible format for the exchange and reuse of biological models","year":2020,"lang":"en","type":"review","venue":"Molecular Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":306,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Terry Fox Research Institute; University of Toronto","funders":"Los Alamos National Laboratory; Biological and Environmental Research; National Institute of Biomedical Imaging and Bioengineering; National Institute of General Medical Sciences; Fundação para a Ciência e a Tecnologia; Japan Society for the Promotion of Science; University of California, San Diego; National Nuclear Security Administration; National Institutes of Health; Novo Nordisk Foundation Center for Basic Metabolic Research; Novo Nordisk; Ministerstvo Školství, Mládeže a Tělovýchovy; Bundesministerium für Bildung und Forschung; National Institute of Allergy and Infectious Diseases; Leibniz-Institut für Arbeitsforschung an der TU Dortmund; Agence Nationale de la Recherche; Universiteit Maastricht; Ministry of Education, Culture, Sports, Science and Technology; Institut National de la Santé et de la Recherche Médicale; Institut national de recherche en informatique et en automatique (INRIA); Deutsche Forschungsgemeinschaft; Klaus Tschira Stiftung; AstraZeneca; National Science Foundation; UK Research and Innovation; European Molecular Biology Laboratory; University of Connecticut; European Commission; Advanced Scientific Computing Research; U.S. Department of Energy; Alan Turing Institute; Novo Nordisk Fonden; Newcastle University; Russian Foundation for Basic Research; Biotechnology and Biological Sciences Research Council; Cancer Research UK; Siberian Branch, Russian Academy of Sciences","keywords":"Library science; SBML; Computer science; World Wide Web","score_opus":0.1370302979095098,"score_gpt":0.3330880094755154,"score_spread":0.19605771156600563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3080133182","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00033912197,0.94783735,0.049699105,0.000035688525,0.00022545483,0.0014576971,0.00035786183,0.000016566002,0.00003117274],"genre_scores_gemma":[0.00805356,0.9891843,0.0006977053,0.00007998609,0.0003834388,0.00041346272,0.0010345962,0.00007852315,0.000074425094],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99711347,0.0006583303,0.0008126278,0.000874173,0.00010092679,0.00044046016],"domain_scores_gemma":[0.99757886,0.0000799094,0.00058180426,0.0014340465,0.00017184354,0.00015353702],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005812188,0.00054218556,0.0017832785,0.00010459517,0.00010916194,0.000028752676,0.0009137229,0.0010029167,0.0000023764392],"category_scores_gemma":[0.00013194441,0.0003414402,0.0006715835,0.00020405017,0.00026185464,0.000004399351,0.0006128637,0.00016496118,0.0000025092995],"study_design_candidate":"not_applicable","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":[0.00018378091,0.00016791819,0.000028432289,0.017531812,0.006005797,0.000035198078,0.00015090941,0.00086124084,0.02107242,0.0071025346,0.0047452324,0.9421147],"study_design_scores_gemma":[0.00027282417,0.0006388592,0.0000010551315,0.00033137412,0.00084232923,0.00013436042,0.00003270512,0.002425022,0.00024726512,0.00014067622,0.9945026,0.00043090936],"about_ca_topic_score_codex":0.000036742455,"about_ca_topic_score_gemma":0.0000133985195,"teacher_disagreement_score":0.98975736,"about_ca_system_score_codex":0.000021600254,"about_ca_system_score_gemma":0.00018314386,"threshold_uncertainty_score":0.99990374},"labels":[],"label_agreement":null},{"id":"W3080735409","doi":"10.1137/19m1303034","title":"Weakly reversible mass-action systems with infinitely many positive steady states","year":2019,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"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; Austrian Science Fund; National Science Foundation","keywords":"Multivariate statistics; Action (physics); Polynomial; Mathematics; Component (thermodynamics); Pure mathematics; Applied mathematics; Mathematical analysis; Physics; Thermodynamics; Statistics; Quantum mechanics","score_opus":0.0237682194544221,"score_gpt":0.17100065065089712,"score_spread":0.14723243119647503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3080735409","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":[0.98652446,0.00014118747,0.010424596,0.000016923968,0.00011290758,0.00020913333,0.000015985208,0.00002633183,0.0025284996],"genre_scores_gemma":[0.9853886,0.00016776753,0.00007947041,0.00003870464,0.00006543589,5.8197605e-7,0.00011967515,0.00002304336,0.014116735],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989463,0.00009620537,0.000108951994,0.00051841856,0.00006938451,0.00026071083],"domain_scores_gemma":[0.9991441,0.00001460764,0.00013095644,0.00045961735,0.00014821185,0.000102501166],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010530689,0.00018130451,0.00018586163,0.00010077122,0.00008443711,0.000029436036,0.0001925479,0.00013236777,0.0000436494],"category_scores_gemma":[0.0000035293722,0.00018515153,0.00009433373,0.00035637472,0.000061190956,0.000018696943,0.00006603034,0.0000911141,0.0001371886],"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":[0.0006863804,0.00008420873,0.14121954,0.00007256681,0.0008667931,0.0000840124,0.000052119172,0.7442105,0.10869993,0.002755376,0.0011834712,0.00008512076],"study_design_scores_gemma":[0.014220842,0.008578222,0.122553155,0.0006596039,0.003279732,0.00022900882,0.01895441,0.5016581,0.21461987,0.0017855943,0.106685385,0.006776069],"about_ca_topic_score_codex":0.00008058079,"about_ca_topic_score_gemma":0.000050076076,"teacher_disagreement_score":0.24255237,"about_ca_system_score_codex":0.00006842635,"about_ca_system_score_gemma":0.00007436733,"threshold_uncertainty_score":0.755026},"labels":[],"label_agreement":null},{"id":"W3082375882","doi":"10.1214/22-aap1904","title":"A spatial measure-valued model for chemical reaction networks in heterogeneous systems","year":2023,"lang":"en","type":"article","venue":"The Annals of Applied Probability","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"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; Centre de Recherches Mathématiques","keywords":"Measure (data warehouse); Statistical physics; Jump; Limit (mathematics); Markov process; Jump process; Mathematics; Process (computing); Scaling; Piecewise; Probability mass function; Biological system; Computer science; Physics; Probability density function; Mathematical analysis; Statistics; Data mining; Quantum mechanics","score_opus":0.05763088700405794,"score_gpt":0.2884766110811173,"score_spread":0.23084572407705933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3082375882","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":[0.9831612,0.00021089934,0.015457494,0.00011096015,0.00004712823,0.00088362704,0.00001262176,0.000023956734,0.00009212285],"genre_scores_gemma":[0.9991652,0.000033436667,0.00014179628,0.000050111,0.00016649965,0.00029767246,0.00010259175,0.000020607571,0.000022128055],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986923,0.00006949986,0.0003757281,0.0003838145,0.0001704259,0.00030823774],"domain_scores_gemma":[0.99902606,0.000027671664,0.00014694671,0.00061527186,0.00013336896,0.00005067],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014407266,0.0001494472,0.00026665072,0.00003540648,0.000048647536,0.000010209095,0.00024125638,0.00018686146,6.7957893e-7],"category_scores_gemma":[0.000052343545,0.0001209815,0.00017925199,0.0002224929,0.000098928154,0.0000017601826,0.00009847783,0.00008232779,0.000001632913],"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":[0.0007829056,0.0000677662,0.00009845973,0.00005758052,0.0000999702,1.3334981e-7,0.000065743494,0.81839585,0.1778956,0.0002193695,0.00039140944,0.0019252208],"study_design_scores_gemma":[0.00035688173,0.000052091247,0.0002663775,0.000010152411,0.000038432492,0.0000012234797,0.000020524143,0.90586716,0.088522404,0.0045783045,0.00012427128,0.00016217923],"about_ca_topic_score_codex":0.000035007855,"about_ca_topic_score_gemma":0.000066706576,"teacher_disagreement_score":0.08937321,"about_ca_system_score_codex":0.000015377933,"about_ca_system_score_gemma":0.000052581778,"threshold_uncertainty_score":0.49334824},"labels":[],"label_agreement":null},{"id":"W3083135238","doi":"10.1093/nar/gkaa734","title":"Engineered signal-coupled inducible promoters: measuring the apparent RNA-polymerase resource budget","year":2020,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"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; National Science Foundation","keywords":"Promoter; Biology; Synthetic biology; Computational biology; RNA polymerase; Genetics; Transcription (linguistics); RNA polymerase II; RNA; Gene; Gene expression","score_opus":0.044067403470053425,"score_gpt":0.2852202265860424,"score_spread":0.24115282311598898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3083135238","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":[0.9912945,0.0021574288,0.0010661379,0.0037729107,0.000033045682,0.00045553048,0.0000077664845,0.00004365684,0.0011690425],"genre_scores_gemma":[0.99789244,0.00008169938,0.00018993183,0.000321442,0.00080055173,0.00006540574,0.000058558115,0.00006591622,0.00052403094],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99693984,0.00043901143,0.00029938284,0.0007067706,0.0008890493,0.0007259448],"domain_scores_gemma":[0.9984592,0.000045800298,0.000060287202,0.00086672517,0.00021983664,0.00034810218],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001300933,0.00022960342,0.0002341097,0.00010396976,0.0003674816,0.000118952994,0.0008851486,0.00019977425,0.00017823554],"category_scores_gemma":[0.00026440434,0.00018055887,0.00018578472,0.00079597585,0.00021949277,0.0000065692675,0.0005780561,0.0005400075,0.00009525881],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014715325,0.00006181032,0.00054660125,0.000038095663,0.00023580094,0.0000143653715,0.00046570794,0.0026925826,0.9797721,0.00001857513,0.0110934675,0.0049137645],"study_design_scores_gemma":[0.00093111326,0.0005456844,0.0008705468,0.00003486208,0.000061605155,0.000011981826,0.0009615062,0.028049687,0.8660402,0.000036644302,0.10200628,0.00044986155],"about_ca_topic_score_codex":0.00002991695,"about_ca_topic_score_gemma":0.000009367583,"teacher_disagreement_score":0.113731846,"about_ca_system_score_codex":0.000047427802,"about_ca_system_score_gemma":0.00016073901,"threshold_uncertainty_score":0.73629767},"labels":[],"label_agreement":null},{"id":"W3083504805","doi":"10.7554/elife.55778.sa2","title":"Author response: Geometric models for robust encoding of dynamical information into embryonic patterns","year":2020,"lang":"en","type":"peer-review","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"McGill University","funders":"","keywords":"Function (biology); Dynamical systems theory; Biology; Bifurcation; Process (computing); Zygote; Epigenetics; Morphogenesis; Computer science; Evolutionary biology; Gene; Physics; Genetics; Embryogenesis; Nonlinear system","score_opus":0.03234065281208776,"score_gpt":0.2952702451951096,"score_spread":0.2629295923830218,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3083504805","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":[0.0048359623,0.025558462,0.940546,0.02533933,0.0007747729,0.0015565983,0.00089687615,0.00004493518,0.00044706208],"genre_scores_gemma":[0.49889448,0.025002906,0.06258134,0.009783761,0.0030018643,0.0013243108,0.0833906,0.00049805554,0.31552267],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99788296,0.00015078607,0.0008026127,0.00046177482,0.0003904538,0.00031138325],"domain_scores_gemma":[0.9980868,0.0000673921,0.0005452797,0.0006512155,0.0005002383,0.00014909262],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008209499,0.00036537094,0.0007479511,0.00036102918,0.00006317788,0.000029103669,0.00050280505,0.0005741013,0.00007581554],"category_scores_gemma":[0.0005640494,0.0003447394,0.00064671756,0.00059011846,0.00003985023,0.000011501673,0.00030273944,0.00019314312,0.000008755121],"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":[0.0002671336,0.00003297674,0.00002557512,0.00568245,0.00059216475,7.230149e-7,0.00002638224,0.027227214,0.0018916158,0.000036915186,0.9536296,0.010587257],"study_design_scores_gemma":[0.0004963682,0.00044657162,0.000058086967,0.00070122397,0.00084647624,0.000007151213,0.000041634936,0.1121754,0.0027753036,0.000057357673,0.8817035,0.0006909532],"about_ca_topic_score_codex":0.000030337096,"about_ca_topic_score_gemma":0.000055530778,"teacher_disagreement_score":0.8779647,"about_ca_system_score_codex":0.00008267234,"about_ca_system_score_gemma":0.00035962556,"threshold_uncertainty_score":0.99990046},"labels":[],"label_agreement":null},{"id":"W3086873215","doi":"10.1371/journal.pcbi.1008185","title":"Genetic buffering and potentiation in metabolism","year":2020,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"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":"Consejo Superior de Investigaciones Científicas; York University","keywords":"Biology; Pleiotropy; In silico; Reprogramming; Context (archaeology); Saccharomyces cerevisiae; Epistasis; Genetics; Potentiator; Mutation; Mutant; Gene; Mutagenesis; Transcriptome; Computational biology; Phenotype; Cell biology; Gene expression","score_opus":0.010905070233644554,"score_gpt":0.21587147229951617,"score_spread":0.2049664020658716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3086873215","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":[0.9850279,0.0014324056,0.012712998,0.00068028,0.000023323137,0.00006880949,0.0000049525324,0.00000853941,0.000040753337],"genre_scores_gemma":[0.9943024,0.000058836504,0.0046922346,0.0006209829,0.000174879,0.0000076226124,0.00012861697,0.000008604023,0.0000058520177],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99934953,0.00006786485,0.00015319105,0.00026564163,0.000047683992,0.00011608887],"domain_scores_gemma":[0.9997907,0.0000124749085,0.00004394686,0.00005935396,0.000037897957,0.000055597902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000037503087,0.00008292119,0.000121016,0.00004021879,0.000027357491,0.000007785477,0.00006592511,0.00007453683,0.000011706908],"category_scores_gemma":[0.000032915246,0.0000858074,0.000032252512,0.000099203884,0.0000388691,0.0000018260355,0.00007362559,0.000041454758,0.000006408301],"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":[0.000078162266,0.00006179131,0.19333243,0.00002827389,0.00025769422,0.0000050487297,0.00014064378,0.19383724,0.6039278,0.0010739879,0.00021037155,0.007046584],"study_design_scores_gemma":[0.001097669,0.0001736736,0.7730222,0.000005902206,0.00006993819,0.000014457571,0.000031123687,0.20893915,0.009825105,0.003391861,0.0030802984,0.00034865565],"about_ca_topic_score_codex":0.0000046878063,"about_ca_topic_score_gemma":0.0000065143745,"teacher_disagreement_score":0.5941027,"about_ca_system_score_codex":0.000004974135,"about_ca_system_score_gemma":0.000022233093,"threshold_uncertainty_score":0.3499124},"labels":[],"label_agreement":null},{"id":"W3092774307","doi":"10.1038/s41598-020-74725-2","title":"A recursive framework for predicting the time-course of drug sensitivity","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University; National Science Foundation","keywords":"Time point; Computer science; Drug action; Drug; Expression (computer science); Computational biology; Data mining; Machine learning; Artificial intelligence; Medicine; Biology; Pharmacology","score_opus":0.008429240885902549,"score_gpt":0.24171918641043946,"score_spread":0.2332899455245369,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3092774307","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":[0.9866015,0.0005005881,0.010527212,0.0011112711,0.0008164116,0.00032436938,0.000011703179,0.000013085225,0.00009391198],"genre_scores_gemma":[0.99682003,0.0000030281115,0.002142653,0.00010821711,0.00033041296,0.000012181943,0.00008368612,0.0000136397375,0.00048613444],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99872357,0.00008314189,0.00027980964,0.0005274579,0.00019419193,0.00019181386],"domain_scores_gemma":[0.9986593,0.000048833383,0.00033400883,0.0006434312,0.00022953909,0.00008488331],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012630195,0.00010263901,0.00015846973,0.000016013259,0.00019729901,0.000040078034,0.00010379502,0.00007350128,0.000012388457],"category_scores_gemma":[0.00057883485,0.00007693003,0.00021093481,0.0002611561,0.00022151413,0.0000029186406,0.000102655235,0.00006543993,0.000002514157],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005832817,0.00006895671,0.011447525,0.000052268762,0.0003198336,0.000029065832,0.0013898038,0.0049154502,0.88308704,0.000076285505,0.09623435,0.0023210703],"study_design_scores_gemma":[0.000115113275,0.000081192695,0.00088669965,0.00003945593,0.00021004389,0.00006475363,0.0005791544,0.006603427,0.9479094,0.005353362,0.037926845,0.00023054035],"about_ca_topic_score_codex":0.0000028191448,"about_ca_topic_score_gemma":0.000006810241,"teacher_disagreement_score":0.06482235,"about_ca_system_score_codex":0.000005292876,"about_ca_system_score_gemma":0.00012578625,"threshold_uncertainty_score":0.31371158},"labels":[],"label_agreement":null},{"id":"W3095532468","doi":"10.1016/j.cobme.2020.100251","title":"Exploiting noise to engineer adaptability in synthetic multicellular systems","year":2020,"lang":"en","type":"review","venue":"Current Opinion in Biomedical Engineering","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Fonds de recherche du Québec – Nature et technologies; National Institute of General Medical Sciences; Burroughs Wellcome Fund; National Institutes of Health; National Science Foundation","keywords":"Adaptability; Noise (video); Multicellular organism; Computer science; Engineering; Artificial intelligence; Biology; Ecology","score_opus":0.04302140512634013,"score_gpt":0.3133636522248877,"score_spread":0.2703422470985476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3095532468","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00019876739,0.98226196,0.013414238,0.00002331725,0.0032798233,0.00074772607,0.0000327584,0.00003912223,0.0000022788597],"genre_scores_gemma":[0.0025085034,0.9944331,0.00047143165,0.000002073538,0.0015291063,0.00042475358,0.0005247415,0.00010116346,0.0000051336474],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9968838,0.0001583987,0.0011189936,0.0009186537,0.00035857336,0.0005615552],"domain_scores_gemma":[0.9987611,0.00007997814,0.00013666472,0.0005593369,0.00003308774,0.00042980802],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00057725306,0.00055707607,0.0013407728,0.0005039172,0.000018426143,0.00003224802,0.000471474,0.00045088056,0.000009308299],"category_scores_gemma":[0.0005724194,0.0005435997,0.00038985623,0.0010889131,0.000036082423,0.0000043886907,0.00031438356,0.000554967,0.00003812342],"study_design_candidate":"not_applicable","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":[0.000016556087,0.00038468227,0.00008452078,0.07070257,0.00034692293,0.00002312357,0.00012343463,0.06882522,0.0006987106,0.00006072149,0.00060871756,0.85812485],"study_design_scores_gemma":[0.00018545047,0.00003609862,0.00001088828,0.012276243,0.00006850509,0.0000093995295,0.000014304828,0.03504069,0.000006398404,2.519789e-7,0.9518451,0.00050667854],"about_ca_topic_score_codex":0.000007068482,"about_ca_topic_score_gemma":6.2005e-7,"teacher_disagreement_score":0.95123637,"about_ca_system_score_codex":0.00021060173,"about_ca_system_score_gemma":0.00016452966,"threshold_uncertainty_score":0.99970156},"labels":[],"label_agreement":null},{"id":"W3100086432","doi":"10.1103/physrevx.8.021035","title":"Inheritance of Cell-Cycle Duration in the Presence of Periodic Forcing","year":2018,"lang":"en","type":"article","venue":"Physical Review X","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":39,"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; H2020 European Research Council; Helmholtz Association; Israel Science Foundation; Minerva Foundation","keywords":"Forcing (mathematics); Circadian clock; Coupling (piping); Circadian rhythm; Nonlinear system; Biological system; Realization (probability); Physics; Biology; Statistical physics; Mathematics; Neuroscience; Statistics; Atmospheric sciences; Materials science; Quantum mechanics","score_opus":0.010539008841791729,"score_gpt":0.279817796868652,"score_spread":0.2692787880268603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3100086432","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":[0.9873937,0.011733641,0.00017043142,0.00007981499,0.0000124151275,0.00011908799,0.0000010147927,8.416874e-7,0.0004890748],"genre_scores_gemma":[0.99685943,0.002788364,0.00009961683,0.00008851735,0.00013153083,0.000011550607,0.000004340588,0.0000037891302,0.000012836691],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99945915,0.00008308318,0.00016868283,0.000114929455,0.000099804456,0.00007433932],"domain_scores_gemma":[0.99953604,0.000013623488,0.000109538094,0.00027212192,0.0000567388,0.000011921313],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017178468,0.000053034153,0.00014901227,0.000007043895,0.00001600313,0.0000020713094,0.0001487399,0.0000150218075,0.000004474308],"category_scores_gemma":[0.0000620145,0.00003713484,0.00008495325,0.00016560074,0.000085710715,0.000002299341,0.000031775413,0.000027513543,0.0000024493656],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009690158,0.0000912347,0.001226658,0.0004888253,0.0000131361985,1.9224562e-7,0.00016282807,0.000065268105,0.99542767,0.0001976243,0.0003112039,0.0020056698],"study_design_scores_gemma":[0.00025787344,0.00033964685,0.01181594,0.0007046459,0.0001104206,0.0000016901059,0.00007077907,0.0024330907,0.977971,0.0010735642,0.005053154,0.0001681857],"about_ca_topic_score_codex":0.000005953342,"about_ca_topic_score_gemma":0.000014180701,"teacher_disagreement_score":0.01745666,"about_ca_system_score_codex":0.0000026145692,"about_ca_system_score_gemma":0.000017810473,"threshold_uncertainty_score":0.15143147},"labels":[],"label_agreement":null},{"id":"W3105015898","doi":"","title":"DYNAMIC BEHAVIOR OF STOCHASTIC GENE EXPRESSION MODELS IN THE PRESENCE OF BURSTING","year":2013,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Bursting; Generality; Expression (computer science); Statistical physics; Gene expression; Computer science; Gene; Biological system; Biology; Physics; Neuroscience; Genetics","score_opus":0.010736441828554447,"score_gpt":0.2411411046075566,"score_spread":0.23040466277900218,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3105015898","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":[0.96427155,0.00044226163,0.034950297,0.000016647324,0.00001270301,0.0001940967,0.0000017607853,0.0000019154254,0.00010878708],"genre_scores_gemma":[0.9975028,0.00001276493,0.0022956023,0.000010526896,0.0000110938,0.00004509284,0.000013482119,0.000006988927,0.000101644626],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993027,0.00005989166,0.00021390528,0.00015905357,0.00013018573,0.00013425552],"domain_scores_gemma":[0.99943537,0.00001782436,0.00009509066,0.00036053298,0.00007072383,0.000020434378],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001609009,0.0000747066,0.0001141791,0.00003483136,0.000018292058,0.000004233361,0.00023023771,0.00006429411,0.00002181219],"category_scores_gemma":[0.000022554541,0.00005113439,0.000062264866,0.00010200585,0.000055101907,0.000003632887,0.0000923634,0.000036440808,8.668482e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004007014,0.000045896395,0.0007441762,0.000006461364,0.0000075434755,1.9632662e-7,0.00005434769,0.07081402,0.92758054,0.0000136373255,0.00004700505,0.0006821865],"study_design_scores_gemma":[0.00037233933,0.00014669812,0.011786642,0.000045486366,0.000074591306,0.000007878908,0.00061563146,0.25373104,0.7324984,0.000519285,0.000003865722,0.00019811248],"about_ca_topic_score_codex":0.00008827895,"about_ca_topic_score_gemma":0.000031028816,"teacher_disagreement_score":0.19508211,"about_ca_system_score_codex":0.0000037582076,"about_ca_system_score_gemma":0.000018356186,"threshold_uncertainty_score":0.20852},"labels":[],"label_agreement":null},{"id":"W3110710111","doi":"10.2140/memocs.2020.8.261","title":"On a stochastic approach to model the double phosphorylation/dephosphorylation cycle","year":2020,"lang":"en","type":"article","venue":"Mathematics and Mechanics of Complex Systems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"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":"Otto von Guericke University Magdeburg; College of Engineering, Michigan State University; Freie Universität Berlin; Università degli Studi dell'Aquila; Centre National de la Recherche Scientifique; Universität zu Köln; Università degli Studi di Pavia; York University; Akademie Věd České Republiky; Universität Wien; Università Politecnica delle Marche; McGill University; Universidad Rey Juan Carlos; Louisiana State University; University of Pittsburgh; Vanderbilt University; Michigan State University; Wayne State University","keywords":"Dephosphorylation; Phosphorylation; Cell biology; Chemistry; Computer science; Computational biology; Biology; Phosphatase","score_opus":0.03212246915540286,"score_gpt":0.23758839202057314,"score_spread":0.2054659228651703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3110710111","genre_codex":"methods","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":[0.19203,0.00031228462,0.80628765,0.00012776403,0.00003491651,0.0005687595,0.000013616266,0.000012520341,0.0006124733],"genre_scores_gemma":[0.99479675,0.000007948866,0.0048241983,0.00013943993,0.000060870458,0.00004638998,0.000025395502,0.000026039905,0.00007293808],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99900997,0.000020434827,0.0003199557,0.0002621328,0.00023854803,0.00014896196],"domain_scores_gemma":[0.99923944,0.000019097699,0.00017013233,0.00035913676,0.000099746096,0.00011242447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024880675,0.00015398124,0.0002544835,0.000028268052,0.00009323331,0.000034643177,0.00020211887,0.0000742061,0.0000025462398],"category_scores_gemma":[0.00003055929,0.00011739713,0.00007811476,0.00014480761,0.00001693518,0.0000025465986,0.00010263726,0.00005156128,0.0000047033495],"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":[0.00005025913,0.000058842295,6.896026e-7,0.0000998791,0.00007688624,5.8560946e-8,0.00061631744,0.83490276,0.062440567,0.10104083,0.00065061107,0.000062289946],"study_design_scores_gemma":[0.00031093784,0.00012852724,0.0000053436247,0.000018992248,0.00005266505,0.000002868237,0.00029398393,0.99427485,0.0020075117,0.0026257786,0.00014662958,0.00013188052],"about_ca_topic_score_codex":0.0000078646,"about_ca_topic_score_gemma":0.0000015006393,"teacher_disagreement_score":0.8027668,"about_ca_system_score_codex":0.000008840479,"about_ca_system_score_gemma":0.000026362497,"threshold_uncertainty_score":0.4787316},"labels":[],"label_agreement":null},{"id":"W3113975382","doi":"","title":"Global community effect: large-scale cooperation yields collective survival of differentiating embryonic stem cells [preprint]","year":2020,"lang":"en","type":"preprint","venue":"The Journal of the American Medical Association (JAMA) Network (American Medical Association)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Canadian Institute for Advanced Research","keywords":"Multicellular organism; Embryonic stem cell; Biology; Preprint; Scale (ratio); Stem cell; Population; Cell biology; Cell; Evolutionary biology; Physics; Genetics; Gene; Sociology","score_opus":0.00689372212338196,"score_gpt":0.2481456814939612,"score_spread":0.24125195937057925,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3113975382","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":[0.96277356,0.00045588816,0.012795784,0.021169508,0.0017759773,0.0005789847,0.0001440459,0.000033358177,0.0002728716],"genre_scores_gemma":[0.9898428,0.001347975,0.00020380733,0.0039606337,0.004011408,0.000026419837,0.00007728601,0.00006744649,0.0004622674],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.97396284,0.016034244,0.0022338643,0.0005345928,0.0062651555,0.00096929003],"domain_scores_gemma":[0.9808716,0.0034996716,0.012060189,0.0010170141,0.0018586225,0.0006929063],"candidate_categories":["metaresearch","metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.020263648,0.00065537315,0.002297817,0.00007539203,0.00076404103,0.00016383217,0.0031668,0.0011370394,0.00016261313],"category_scores_gemma":[0.011321715,0.00046121262,0.0013178911,0.0020332537,0.0006850731,0.000026648482,0.0026612494,0.0052009816,0.0000131577535],"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":[0.0012418373,0.00091194717,0.7862505,0.00017162213,0.01093793,0.00001158073,0.0015699334,0.041601453,0.0013299646,0.000035365767,0.13545994,0.02047795],"study_design_scores_gemma":[0.008831308,0.0046330173,0.89396715,0.002067029,0.0077841794,0.00007983407,0.006293296,0.055370137,0.0055037187,0.0010602875,0.011785441,0.002624606],"about_ca_topic_score_codex":0.00040869004,"about_ca_topic_score_gemma":0.0012747543,"teacher_disagreement_score":0.1236745,"about_ca_system_score_codex":0.002208529,"about_ca_system_score_gemma":0.0029367618,"threshold_uncertainty_score":0.99978393},"labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"bench_or_experimental","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low"},{"model":"gpt","categories":[],"domain":null,"study_design":"bench_or_experimental","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high"}],"label_agreement":"agree"},{"id":"W3115793130","doi":"10.21203/rs.3.rs-129173/v1","title":"Applying an inverse homeostasis perspective to simplify the design and implemention of robustly-nearly-homeostatic biological networks","year":2020,"lang":"en","type":"preprint","venue":"Research Square","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Homeostasis; Perspective (graphical); Computer science; Biology; Cell biology; Artificial intelligence","score_opus":0.11144194689735039,"score_gpt":0.39265770784954906,"score_spread":0.2812157609521987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3115793130","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":[0.87509614,0.006578424,0.111634,0.0014695353,0.00007874737,0.0049169203,0.00014643457,0.00003445034,0.000045356515],"genre_scores_gemma":[0.9920925,0.002152247,0.0041211606,0.00012951033,0.00038255454,0.00066203636,0.00039735003,0.00004746412,0.000015184742],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99543387,0.0019386149,0.0003913669,0.001073847,0.00054266065,0.0006196182],"domain_scores_gemma":[0.99762475,0.00021580525,0.00015933582,0.00091487664,0.00073984044,0.00034536855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002415659,0.0003167122,0.00043989756,0.00016458648,0.00029878688,0.0001269288,0.0006407072,0.00041539778,0.000040353232],"category_scores_gemma":[0.00052746164,0.00024450378,0.0002184896,0.000588135,0.00031564402,0.00000534761,0.0021060184,0.0007157307,0.000005558676],"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":[0.002818394,0.00056755694,0.024404505,0.0009529459,0.0034519436,0.000059207727,0.004427994,0.76852417,0.11016552,0.0013114595,0.029498613,0.053817682],"study_design_scores_gemma":[0.006871305,0.03128069,0.16392529,0.0021349103,0.0020020546,0.00007643695,0.14298362,0.5088865,0.064667724,0.030317726,0.0394948,0.007358957],"about_ca_topic_score_codex":0.0002450953,"about_ca_topic_score_gemma":0.00014245643,"teacher_disagreement_score":0.25963768,"about_ca_system_score_codex":0.00011236133,"about_ca_system_score_gemma":0.00027161228,"threshold_uncertainty_score":0.9970575},"labels":[],"label_agreement":null},{"id":"W3118280626","doi":"10.1101/2021.01.07.425782","title":"dynUGENE: an R package for uncertainty-aware gene regulatory network inference, simulation, and visualization","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vector Institute; Princess Margaret Cancer Centre; University Health Network; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Computer science; Inference; Selection (genetic algorithm); Source code; Code (set theory); Identification (biology); Visualization; R package; Focus (optics); Data mining; Gene regulatory network; Interface (matter); Machine learning; Artificial intelligence; Gene; Programming language; Operating system; Gene expression","score_opus":0.013318986764133052,"score_gpt":0.26094651491382087,"score_spread":0.24762752814968783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3118280626","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":[0.86003524,0.0035768,0.13487616,0.000024081859,0.00047779363,0.000736549,0.00016397997,0.000108399916,0.0000010090262],"genre_scores_gemma":[0.99133736,0.0005222925,0.005539758,0.0002335537,0.001817424,0.00023565149,0.00009833357,0.00020356766,0.000012045475],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99639916,0.0003072864,0.00066736224,0.0016456455,0.0003344963,0.000646047],"domain_scores_gemma":[0.99591404,0.000050982715,0.0005392837,0.0018754631,0.0012463093,0.00037394027],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006956951,0.00068667653,0.00067349366,0.00015824859,0.0003358273,0.00030315612,0.00042819305,0.0010584405,0.000018586523],"category_scores_gemma":[0.0002062544,0.00081322674,0.00025834638,0.00045456053,0.00014868577,0.000023799113,0.00056518905,0.0002536992,0.0000019115691],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007494323,0.00011344704,0.012505905,0.00026128753,0.0005449123,0.00000777702,0.0000107933665,0.34903684,0.6368855,0.00018389794,0.00035819548,0.000016458229],"study_design_scores_gemma":[0.0017745642,0.0004015247,0.1238554,0.00046520072,0.0012001441,8.348899e-8,0.000024774767,0.2454658,0.6163612,0.000023708015,0.0071792724,0.0032483013],"about_ca_topic_score_codex":0.000013642778,"about_ca_topic_score_gemma":0.000034314016,"teacher_disagreement_score":0.13130215,"about_ca_system_score_codex":0.00010671164,"about_ca_system_score_gemma":0.00067916577,"threshold_uncertainty_score":0.99943185},"labels":[],"label_agreement":null},{"id":"W3119506349","doi":"10.1007/978-1-0716-1032-9_3","title":"Using Models to (Re-)Design Synthetic Circuits","year":2021,"lang":"en","type":"book-chapter","venue":"Methods in molecular biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Synthetic biology; Computer science; Electronic circuit; Gene regulatory network; Stochastic modelling; Theoretical computer science; Synthetic data; Algorithm; Computational biology; Mathematics; Engineering; Gene; Biology; Gene expression","score_opus":0.09142201883717109,"score_gpt":0.3699807417038736,"score_spread":0.27855872286670247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3119506349","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002431326,0.010586967,0.962621,0.000058364178,0.00032092875,0.00048459962,0.000020793097,0.000018858618,0.025645366],"genre_scores_gemma":[0.0019985915,0.00052566227,0.9643512,0.00095743703,0.0002994223,0.000057585094,0.00021820022,0.00026019514,0.031331744],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99547106,0.001316282,0.0007346639,0.0016323768,0.00017936522,0.000666269],"domain_scores_gemma":[0.99767166,0.0000840988,0.0002647414,0.0015604175,0.00020029485,0.00021876508],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0015000635,0.0007096247,0.0010688511,0.0004408879,0.000067098896,0.00002713974,0.0006251136,0.0015187216,0.00015695892],"category_scores_gemma":[0.00017542615,0.00079309585,0.00054986245,0.00018086261,0.00017200723,0.000002124121,0.00060883426,0.00041365586,0.000014240039],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021892174,0.000023879018,0.000005443633,0.00002563699,0.00044427085,0.00010153495,0.000023511977,0.072705425,0.90243953,0.010020535,0.00011912788,0.014069232],"study_design_scores_gemma":[0.00091066246,0.0007007056,0.0000033321878,0.00043647017,0.001020388,0.00023286583,0.000047928952,0.016329939,0.7516787,0.09894171,0.12617485,0.00352245],"about_ca_topic_score_codex":0.000015660811,"about_ca_topic_score_gemma":0.000022858003,"teacher_disagreement_score":0.15076081,"about_ca_system_score_codex":0.000118155935,"about_ca_system_score_gemma":0.00032677548,"threshold_uncertainty_score":0.9997775},"labels":[],"label_agreement":null},{"id":"W3120435289","doi":"10.1109/cdc42340.2020.9304088","title":"Control of negative feedback loops in genetic networks","year":2020,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"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 Victoria","funders":"","keywords":"Ode; Control theory (sociology); Negative feedback; Control (management); Feedback loop; Piecewise; Computer science; Loop (graph theory); Mode (computer interface); Sliding mode control; Mathematics; Physics; Nonlinear system; Applied mathematics; Mathematical analysis; Quantum mechanics; Artificial intelligence","score_opus":0.006227399995115334,"score_gpt":0.20329616759238492,"score_spread":0.19706876759726957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3120435289","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":[0.9346789,0.0012783472,0.06259632,0.00037660392,0.00002998485,0.00017317953,0.0000036475599,0.000007758857,0.0008552277],"genre_scores_gemma":[0.9979161,0.00007735383,0.00095028774,0.00074729323,0.00017501642,0.000006849894,0.000011859366,0.000014535234,0.00010072514],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913144,0.00007422005,0.0002547457,0.0002696933,0.00008415077,0.00018574673],"domain_scores_gemma":[0.9995554,0.000012570146,0.00007960692,0.00020305756,0.000057262918,0.000092091475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006585128,0.000117522555,0.00021796083,0.000023486931,0.000013284453,0.000005350348,0.00015563122,0.000109405395,0.000082682156],"category_scores_gemma":[0.000038375598,0.00011081112,0.0001083992,0.00022704346,0.00006150203,0.0000011374951,0.000057534224,0.00005987715,0.0000071119784],"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":[0.00037844788,0.00009390469,0.15278786,0.000029332143,0.0004093073,0.000010178029,0.00010472536,0.5822186,0.25447816,0.00011926116,0.0040459237,0.0053243185],"study_design_scores_gemma":[0.008042226,0.001267907,0.20928061,0.00003330817,0.00028332396,0.000010009011,0.0003825515,0.4980021,0.27383226,0.00020466938,0.0075906296,0.001070401],"about_ca_topic_score_codex":0.000023577171,"about_ca_topic_score_gemma":0.00007450937,"teacher_disagreement_score":0.08421648,"about_ca_system_score_codex":0.000005632353,"about_ca_system_score_gemma":0.000033045548,"threshold_uncertainty_score":0.4518746},"labels":[],"label_agreement":null},{"id":"W3121221297","doi":"10.7939/r3p26qj1c","title":"Systems biology and the integration of mechanistic explanation and mathematical explanation","year":2013,"lang":"en","type":"article","venue":"PhilSci-Archive (University of Pittsburgh)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Alberta","funders":"","keywords":"Mathematical and theoretical biology; Mechanism (biology); Systems biology; Computer science; Mathematical model; Robustness (evolution); Dynamical systems theory; Cognitive science; Epistemology; Management science; Biology; Computational biology; Mathematics; Psychology; Physics; Bioinformatics; Philosophy","score_opus":0.009506707162281646,"score_gpt":0.203334181684694,"score_spread":0.19382747452241236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121221297","genre_codex":"methods","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":[0.15074044,0.00032413105,0.8483693,0.00027763628,0.000022156972,0.00021406014,0.000007919701,0.0000039182123,0.000040444633],"genre_scores_gemma":[0.9994791,0.0002547554,0.00016437532,0.00000899947,0.000026569936,0.0000017119976,0.000054955162,0.000004235641,0.0000052556757],"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9994076,0.00014507536,0.00012134179,0.0001664442,0.000076722135,0.00008280156],"domain_scores_gemma":[0.9994937,0.00006855982,0.00015233393,0.00015571743,0.000090583104,0.000039087543],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023573216,0.00007762409,0.0001760905,0.000083256695,0.00007991171,0.000008160788,0.00010519615,0.00006097149,0.000017021632],"category_scores_gemma":[0.00004614337,0.00006497247,0.000046489546,0.000066256674,0.00031902827,0.000009699635,0.00008693882,0.00003931642,0.0000012032386],"study_design_candidate":"theoretical_or_conceptual","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":[0.00017519595,0.000059953316,0.00040812744,0.00012316398,0.00032530457,7.4952106e-7,0.0018120335,0.00021303953,0.6644585,0.32596433,0.00077023625,0.0056893486],"study_design_scores_gemma":[0.0013398634,0.00019826936,0.008405118,0.000044971504,0.00019569046,0.000015368556,0.004137134,0.040885918,0.00061913364,0.94366217,0.0003257641,0.00017061045],"about_ca_topic_score_codex":0.00020852398,"about_ca_topic_score_gemma":0.000035823894,"teacher_disagreement_score":0.8487387,"about_ca_system_score_codex":0.0000054711036,"about_ca_system_score_gemma":0.0000131572715,"threshold_uncertainty_score":0.26495004},"labels":[],"label_agreement":null},{"id":"W3123146320","doi":"10.1007/s00422-021-00860-2","title":"Sensitivity minimization, biological homeostasis and information theory","year":2021,"lang":"en","type":"review","venue":"Biological Cybernetics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Defense Advanced Research Projects Agency; Banff International Research Station for Mathematical Innovation and Discovery","keywords":"Sensitivity (control systems); Minification; Complex system; Computer science; Artificial intelligence; Mathematics; Mathematical optimization; Engineering","score_opus":0.029587395365959855,"score_gpt":0.2741827629214503,"score_spread":0.2445953675554904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123146320","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014066114,0.9964492,0.0013094434,0.000015870528,0.00010966889,0.0003315438,0.00013098921,0.000030368587,0.00021635037],"genre_scores_gemma":[0.0019012506,0.9923763,0.0008719286,0.00018376176,0.00031555851,0.00003714927,0.0042071748,0.000022962897,0.00008389338],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99694693,0.0012771244,0.00064892886,0.00062305323,0.00014240373,0.0003615371],"domain_scores_gemma":[0.9985754,0.00019540693,0.0003612759,0.00051869714,0.00017911727,0.00017009983],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0006233233,0.00050943496,0.0012066447,0.000090172296,0.000110091496,0.00007782906,0.00018960155,0.0013170418,0.00006106187],"category_scores_gemma":[0.00073127204,0.00035848012,0.0004900495,0.0003153144,0.00032431266,0.0000069997905,0.00052068254,0.00023328398,0.00003131571],"study_design_candidate":"not_applicable","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":[0.000012084646,0.000049755137,0.00018211048,0.0003377484,0.00035865643,0.0000101027135,0.000009214688,0.000014293821,0.000022860859,0.0011881277,0.0010960939,0.99671894],"study_design_scores_gemma":[0.000105341074,0.00014655972,0.00025240064,0.00024318937,0.00031903747,0.00009737342,0.000023339815,0.000009334502,0.000030002366,0.000068241214,0.99822515,0.00048002662],"about_ca_topic_score_codex":0.0000020383677,"about_ca_topic_score_gemma":0.0000028809484,"teacher_disagreement_score":0.9971291,"about_ca_system_score_codex":0.00002891253,"about_ca_system_score_gemma":0.00012634818,"threshold_uncertainty_score":0.99997944},"labels":[],"label_agreement":null},{"id":"W3124297061","doi":"10.1101/2021.01.26.428329","title":"A mean-field approach for modeling the propagation of perturbations in biochemical reaction networks","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Princess Margaret Cancer Centre; University of Waterloo","funders":"","keywords":"Ordinary differential equation; Perturbation (astronomy); Computer science; Network model; CHOP; Computational biology; Biological system; Differential equation; Biology; Physics; Artificial intelligence; Genetics; Endoplasmic reticulum","score_opus":0.013854522096118732,"score_gpt":0.21962065436243655,"score_spread":0.20576613226631782,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124297061","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":[0.7353156,0.002515679,0.2613113,0.00007809438,0.00014444147,0.0005998223,0.000013039708,0.000018667459,0.0000033423312],"genre_scores_gemma":[0.9909675,0.00035862802,0.0076131662,0.00006947949,0.0004861698,0.00042721248,0.000014506859,0.00006052893,0.0000028013108],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981135,0.00012954569,0.00051890285,0.0007434208,0.00019682678,0.000297808],"domain_scores_gemma":[0.99805844,0.000031812808,0.00031588558,0.0009980309,0.0005266902,0.00006914459],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006071636,0.0002980323,0.00036032478,0.00011096132,0.00009084456,0.000058875416,0.00034160167,0.000664983,0.0000016212307],"category_scores_gemma":[0.00023088128,0.00027654535,0.0002666775,0.00037034994,0.000052833904,0.000007921959,0.0002588176,0.00036387602,1.7916368e-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":[0.000044785054,0.000101468206,0.0006492004,0.0001310441,0.00016281687,4.6370616e-7,0.0000088654515,0.11339909,0.88534975,0.00005914358,0.0000901946,0.0000031625543],"study_design_scores_gemma":[0.0002943094,0.000043361346,0.0013398574,0.0001071485,0.00018946282,2.180513e-8,0.000022465094,0.5671252,0.43043154,0.0000013167704,0.000095185445,0.00035011524],"about_ca_topic_score_codex":0.000038289563,"about_ca_topic_score_gemma":0.000009994408,"teacher_disagreement_score":0.45491824,"about_ca_system_score_codex":0.00007891287,"about_ca_system_score_gemma":0.0003300143,"threshold_uncertainty_score":0.99996865},"labels":[],"label_agreement":null},{"id":"W3124754983","doi":"10.20381/ruor-3454","title":"Computational Investigations of Noise-mediated Cell Population Dynamics","year":2013,"lang":"en","type":"dissertation","venue":"uO Research (University of Ottawa)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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; National Institutes of Health; Government of Ontario; University of Ottawa","keywords":"Dynamics (music); Noise (video); Population; Computer science; Statistical physics; Artificial intelligence; Physics; Acoustics; Medicine","score_opus":0.015054149557011733,"score_gpt":0.2625310035748667,"score_spread":0.24747685401785496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124754983","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":[0.9937286,0.0001018478,0.00040226078,0.00006668011,0.000050068153,0.0002640452,0.00013062937,0.0000070965525,0.005248791],"genre_scores_gemma":[0.95323074,0.00009972362,0.0023759932,0.0000034559735,0.000039438644,0.0000011074037,0.028728448,0.000022567614,0.015498505],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99845517,0.00019899989,0.00021226617,0.00033082397,0.0005852721,0.00021749984],"domain_scores_gemma":[0.99816364,0.000051896197,0.00030305382,0.00032743454,0.001031044,0.0001229439],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031258917,0.00013794625,0.0002537652,0.00045889418,0.0001765947,0.000009915221,0.00038964636,0.00037324795,0.00014094498],"category_scores_gemma":[0.0000821064,0.00018406524,0.00017208488,0.0005094291,0.00018982985,0.000009754994,0.00008366999,0.00022059046,0.000025473033],"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":[0.00013724371,0.0011490288,0.423296,0.0027911395,0.0020132884,0.000018477509,0.001407811,0.11369001,0.37090498,0.011710503,0.066749655,0.006131869],"study_design_scores_gemma":[0.0017820384,0.00062121806,0.8416773,0.00019702686,0.0003662305,0.0000022863624,0.0064550578,0.119298905,0.018182883,0.0022889923,0.00822404,0.0009040006],"about_ca_topic_score_codex":0.00039938543,"about_ca_topic_score_gemma":0.0025924272,"teacher_disagreement_score":0.41838133,"about_ca_system_score_codex":0.00007211224,"about_ca_system_score_gemma":0.00029645886,"threshold_uncertainty_score":0.7505963},"labels":[],"label_agreement":null},{"id":"W3127860826","doi":"10.1111/febs.15760","title":"Stochastic models for single‐cell data: Current challenges and the way forward","year":2021,"lang":"en","type":"review","venue":"FEBS Journal","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Stochastic modelling; Computer science; Data set; Set (abstract data type); Stochastic process; Data quality; Experimental data; Econometrics; Data mining; Mathematics; Statistics; Artificial intelligence","score_opus":0.10897054815544979,"score_gpt":0.3276910864832244,"score_spread":0.21872053832777463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3127860826","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000003829297,0.9721682,0.026761279,0.00007392151,0.00044418007,0.0003787467,0.00007556139,0.0000033362246,0.000090928996],"genre_scores_gemma":[0.0001938228,0.9964186,0.000376158,0.000014627224,0.002209201,0.000045285615,0.0005113235,0.000061771934,0.00016919998],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980175,0.00031627808,0.0005397651,0.000573542,0.00021284721,0.00034004814],"domain_scores_gemma":[0.998163,0.00009832997,0.0005132617,0.0009173551,0.00016043645,0.00014763729],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009255519,0.00037847966,0.001132971,0.00006599263,0.00020074622,0.00012302658,0.00071546296,0.0002491605,0.000005333062],"category_scores_gemma":[0.00009523167,0.0002379704,0.0006881376,0.000067393295,0.000111958274,0.0000072987095,0.000531909,0.00036318717,0.0000017054163],"study_design_candidate":"not_applicable","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":[0.000016985727,0.000046967292,2.1164265e-8,0.0016282019,0.00066812226,0.0000028724392,0.000025741962,0.00052292837,0.000005756736,0.000094641975,0.0032143083,0.99377346],"study_design_scores_gemma":[0.00062122487,0.000066561384,4.739277e-8,0.0015525052,0.0027435469,0.00046678042,0.00003658462,0.0011029991,0.00000449713,0.00036523625,0.9927477,0.00029230083],"about_ca_topic_score_codex":2.5614685e-7,"about_ca_topic_score_gemma":0.0000059028025,"teacher_disagreement_score":0.99348116,"about_ca_system_score_codex":0.000029028502,"about_ca_system_score_gemma":0.00026345163,"threshold_uncertainty_score":0.9704151},"labels":[],"label_agreement":null},{"id":"W3135293353","doi":"10.1103/physreve.103.042401","title":"Pleiotropy enables specific and accurate signaling in the presence of ligand cross talk","year":2021,"lang":"en","type":"article","venue":"Physical review. E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Pleiotropy; Signal transduction; Receptor; Computational biology; Ligand (biochemistry); Cell signaling; Biology; Cell biology; G protein-coupled receptor; Computer science; Genetics; Phenotype; Gene","score_opus":0.017187972622846225,"score_gpt":0.31207100658775333,"score_spread":0.2948830339649071,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3135293353","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":[0.9181535,0.08139233,0.00008350228,0.00015801605,0.000012285729,0.00008696225,0.000003243897,0.0000013071474,0.00010881881],"genre_scores_gemma":[0.97047263,0.029074643,0.00007689535,0.00013697136,0.00015585392,0.000010277921,0.000018921612,0.000006777523,0.000047036057],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99918544,0.00013448282,0.00017988091,0.00024118746,0.00012385446,0.00013513012],"domain_scores_gemma":[0.99945515,0.00004805295,0.00007453139,0.00032469243,0.00006737821,0.000030211972],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002042795,0.00009356363,0.00022263633,0.000008115601,0.00003148252,0.000021636573,0.00014974026,0.000025309824,0.0000066416674],"category_scores_gemma":[0.000102290054,0.000065976994,0.000108586784,0.00020011644,0.00008525918,0.0000035405017,0.00009319489,0.00006280035,0.0000018202422],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000075578287,0.00006144753,0.0017885127,0.00024043085,0.00002963115,0.000007854089,0.000038538114,0.00033450543,0.99512804,0.0002406359,0.00046243225,0.0016604282],"study_design_scores_gemma":[0.00019504095,0.000052206677,0.005588467,0.00034547408,0.000056688623,0.000011894849,0.00004625685,0.0003226819,0.96714383,0.0009137077,0.025164453,0.00015928243],"about_ca_topic_score_codex":0.0000033384529,"about_ca_topic_score_gemma":0.0000070331457,"teacher_disagreement_score":0.052319095,"about_ca_system_score_codex":0.0000029213923,"about_ca_system_score_gemma":0.000026018997,"threshold_uncertainty_score":0.26904637},"labels":[],"label_agreement":null},{"id":"W3136254756","doi":"10.1038/s41467-021-21700-8","title":"Nonlinear delay differential equations and their application to modeling biological network motifs","year":2021,"lang":"en","type":"article","venue":"Nature Communications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":120,"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":"Nonlinear system; Computer science; Biological network; Delay differential equation; Computational biology; Physics; Biology","score_opus":0.01889591175950727,"score_gpt":0.2761219202232149,"score_spread":0.25722600846370763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3136254756","genre_codex":"methods","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":[0.44545302,0.016897002,0.5351134,0.0019905681,0.00007426083,0.00022966266,0.000030331792,0.000052376454,0.00015935357],"genre_scores_gemma":[0.9792329,0.00096117985,0.017770525,0.0004480729,0.0002702921,0.000061202874,0.0011899149,0.000020837359,0.0000450933],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999099,0.00015087095,0.00019386748,0.00031692343,0.000064529304,0.00017479763],"domain_scores_gemma":[0.9981534,0.000052731913,0.00004852696,0.001421078,0.00022712228,0.0000971719],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001237644,0.00013083263,0.0001397753,0.000030448236,0.00025942555,0.00003317354,0.0004238443,0.00031500324,0.000004477227],"category_scores_gemma":[0.00011816656,0.00011664315,0.00008906167,0.00030169392,0.00005439391,0.0000029623025,0.0006332297,0.00027539313,0.0000041605285],"study_design_candidate":"simulation_or_modeling","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":[0.00005583817,0.0006146657,0.009645384,0.000013293433,0.0007197134,0.0000011257855,0.00029249853,0.23257805,0.72080636,0.012310002,0.004020781,0.018942283],"study_design_scores_gemma":[0.00027132657,0.000057548757,0.0017371129,0.00001437034,0.000084462816,0.000015371597,0.00014033928,0.9104228,0.0073213596,0.00066704233,0.07889167,0.00037659635],"about_ca_topic_score_codex":0.000004202078,"about_ca_topic_score_gemma":0.00041028936,"teacher_disagreement_score":0.713485,"about_ca_system_score_codex":0.000013619024,"about_ca_system_score_gemma":0.00005052781,"threshold_uncertainty_score":0.47565696},"labels":[],"label_agreement":null},{"id":"W3136370955","doi":"10.3390/books978-3-03921-218-7","title":"Dynamical Models of Biology and Medicine","year":2019,"lang":"en","type":"book","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Division of Mathematical Sciences; Fundamental Research Funds for the Central Universities; European Regional Development Fund; Instituto de Salud Carlos III; Japan Society for the Promotion of Science; Natural Sciences and Engineering Research Council of Canada; Gobierno de Aragón; Natural Science Foundation of Liaoning Province; National Research Foundation of Korea; Ministerio de Economía y Competitividad; National Institute for Mathematical and Biological Synthesis; National Natural Science Foundation of China; Agence Nationale de la Recherche; Heilongjiang University; Specialized Research Fund for the Doctoral Program of Higher Education of China; Natural Science Foundation of Heilongjiang Province; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina; National Research Foundation; Bristol-Myers Squibb; Ministry of Education, Science and Technology; National Science Foundation","keywords":"Mathematical and theoretical biology; Computer science; Subject (documents); Systems medicine; Dynamical systems theory; Systems biology; Population; Management science; Data science; Biology; Computational biology; Bioinformatics; Medicine; Physics; Engineering","score_opus":0.009216309814006866,"score_gpt":0.2487902140351569,"score_spread":0.23957390422115002,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3136370955","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014914172,0.02026803,0.012787231,0.0002296915,0.00025720213,0.00037224064,0.0000572707,0.000016406562,0.9510977],"genre_scores_gemma":[0.13023481,0.0016706984,0.00040681942,0.00013776266,0.00038569944,0.000003157588,0.000996574,0.000040141364,0.86612433],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990989,0.00003177464,0.00026233224,0.00038991842,0.00007896846,0.00013808986],"domain_scores_gemma":[0.99925894,0.0000137928455,0.00014017607,0.00045155804,0.000077820514,0.000057745667],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000111110414,0.00019837343,0.0004619606,0.00007298531,0.000012468091,0.0000014731188,0.00015083642,0.0005613425,0.00009175003],"category_scores_gemma":[0.000009445593,0.000155679,0.000105597435,0.000025049023,0.000273234,5.3374555e-7,0.00016515648,0.000084121406,0.000004424607],"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":[0.00024635243,0.00009798769,0.0016382433,0.00073665153,0.0046216957,0.000005548743,0.000066925255,0.0038865546,0.34937254,0.18171048,0.44368258,0.013934442],"study_design_scores_gemma":[0.0032936835,0.0032444908,0.00028422277,0.00037121508,0.0020488363,0.00008558807,0.000052500913,0.03746768,0.008989627,0.14300898,0.79885787,0.002295307],"about_ca_topic_score_codex":0.000009693967,"about_ca_topic_score_gemma":0.000023075763,"teacher_disagreement_score":0.3551753,"about_ca_system_score_codex":0.000011286758,"about_ca_system_score_gemma":0.00011371341,"threshold_uncertainty_score":0.6348405},"labels":[],"label_agreement":null},{"id":"W3144837775","doi":"10.1021/acssynbio.0c00574","title":"An Automated Tabletop Continuous Culturing System with Multicolor Fluorescence Monitoring for Microbial Gene Expression and Long-Term Population Dynamics","year":2021,"lang":"en","type":"article","venue":"ACS Synthetic Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Bistability; Population; Gene expression; Biological system; Dynamics (music); Biology; Term (time); Expression (computer science); Computational biology; Regulation of gene expression; Gene; Computer science; Genetics; Physics","score_opus":0.006547052351400829,"score_gpt":0.2470724784409759,"score_spread":0.24052542608957508,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3144837775","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":[0.9885397,0.00062288984,0.010279786,0.000021652673,0.00017359643,0.00025252934,0.000031007123,0.000075121185,0.000003742654],"genre_scores_gemma":[0.9888809,0.00006029294,0.010034664,0.000008900987,0.00021533789,0.00004962174,0.0006798375,0.00003193088,0.000038562426],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99865836,0.00013899014,0.00024239214,0.0005885221,0.00005495788,0.00031677808],"domain_scores_gemma":[0.999196,0.000021136675,0.00014045794,0.0003923883,0.00016139486,0.00008865809],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012959275,0.00020404355,0.00028467312,0.000038434457,0.00017516797,0.000040179242,0.00013639325,0.00028538977,0.0000013573208],"category_scores_gemma":[0.0000324335,0.00017441908,0.00005357017,0.00007683828,0.00008322234,0.0000072516273,0.00009018358,0.00005970018,6.622834e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000075862976,0.000037004524,0.099626794,0.00006016081,0.000070520204,0.000006905643,0.000020880132,0.00058673497,0.89742833,0.000020124258,0.0000035159658,0.0020631775],"study_design_scores_gemma":[0.0006693642,0.00020045703,0.030744083,0.00011771546,0.00011905964,0.000188889,0.00012641735,0.012347183,0.95518166,0.0000026199668,0.00002173107,0.00028081905],"about_ca_topic_score_codex":0.000020852982,"about_ca_topic_score_gemma":0.00005486558,"teacher_disagreement_score":0.06888271,"about_ca_system_score_codex":0.000051019026,"about_ca_system_score_gemma":0.000034118948,"threshold_uncertainty_score":0.7112604},"labels":[],"label_agreement":null},{"id":"W3150077969","doi":"","title":"Cell Modeling using Agent-based Formalisms","year":2004,"lang":"en","type":"book-chapter","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Rotation formalisms in three dimensions; Computer science; Reusability; Ode; Unified Modeling Language; Ordinary differential equation; Programming language; Modeling language; Simple (philosophy); Theoretical computer science; Differential equation; Applied mathematics; Mathematics","score_opus":0.02150838103565012,"score_gpt":0.22627646109485708,"score_spread":0.20476808005920696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3150077969","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03854586,0.008061946,0.32240477,0.00005369861,0.0004182772,0.00057441124,0.000052642543,0.000088295645,0.6298001],"genre_scores_gemma":[0.68122137,0.00022720166,0.0111899,0.00046787708,0.0007658041,0.000005407636,0.00087279937,0.00020931446,0.30504036],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985943,0.000009861316,0.00033805956,0.00053323194,0.00022067413,0.00030388366],"domain_scores_gemma":[0.9989537,0.00000196583,0.00015563572,0.00065352203,0.00011165414,0.00012354377],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009906557,0.0003968943,0.00030838803,0.00010509135,0.00009264137,0.000027956492,0.00023100447,0.00059848017,0.00038889793],"category_scores_gemma":[0.0000019947454,0.00040073963,0.0004841352,0.000022749638,0.000043356235,0.0000016875947,0.000117554155,0.00013960023,0.00003840134],"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":[0.000022822043,0.000017914625,0.000007388522,0.00005689485,0.00018537304,0.000010801507,0.0000039588936,0.9686065,0.028788088,0.0014459249,0.00060682895,0.00024753422],"study_design_scores_gemma":[0.0023171143,0.0003416723,0.0000012180144,0.00027032034,0.0017152326,0.000027668504,0.000026722622,0.7142007,0.15752281,0.006095401,0.11415332,0.0033278288],"about_ca_topic_score_codex":0.000024616733,"about_ca_topic_score_gemma":0.000022239603,"teacher_disagreement_score":0.64267546,"about_ca_system_score_codex":0.000071716844,"about_ca_system_score_gemma":0.0002812097,"threshold_uncertainty_score":0.99984443},"labels":[],"label_agreement":null},{"id":"W3152301385","doi":"10.1109/wsc.2009.5429688","title":"DEVS-based design of spatial simulations of biological systems","year":2009,"lang":"en","type":"article","venue":"Proceedings of the 2009 Winter Simulation Conference (WSC)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"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":"","keywords":"DEVS; Formalism (music); Computer science; Modeling and simulation; Theoretical computer science; Distributed computing; Simulation","score_opus":0.038557912042407126,"score_gpt":0.26968848591550587,"score_spread":0.23113057387309874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3152301385","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":[0.87526137,0.00011302704,0.12393937,0.00007492271,0.000060779916,0.0003065019,0.000018096647,0.000008996673,0.00021693233],"genre_scores_gemma":[0.99888486,0.0000055437363,0.0009056404,0.000033446555,0.000072628354,0.0000031088027,0.000015010547,0.000007936752,0.00007182285],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988791,0.0000346128,0.0004957484,0.00023455595,0.00020758077,0.00014839723],"domain_scores_gemma":[0.99838406,0.00004300579,0.00052970543,0.00019182838,0.00081123336,0.00004017083],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021922872,0.00014854985,0.00027092613,0.00008142113,0.000037462596,0.0000148133695,0.00033837472,0.00015851573,0.000031990912],"category_scores_gemma":[0.00019220401,0.000113897375,0.00016059645,0.00016174639,0.000120801975,0.0000095092355,0.000051326107,0.000057757385,6.8183175e-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":[0.000116258205,0.00006619971,0.011095546,0.000021102249,0.000043807606,2.2933728e-8,0.000037078113,0.58607477,0.40182862,0.00009498772,0.000054135744,0.0005674625],"study_design_scores_gemma":[0.00042823763,0.00039520217,0.0165666,0.000089423615,0.00006901888,6.3158296e-7,0.000039106115,0.6330732,0.34886786,0.00021442558,0.00011956427,0.00013673338],"about_ca_topic_score_codex":0.000011356619,"about_ca_topic_score_gemma":0.000002229368,"teacher_disagreement_score":0.1236235,"about_ca_system_score_codex":0.000010676867,"about_ca_system_score_gemma":0.00006780082,"threshold_uncertainty_score":0.46446002},"labels":[],"label_agreement":null},{"id":"W3153969411","doi":"10.3390/math9080867","title":"Boolean Networks Models in Science and Engineering","year":2021,"lang":"en","type":"article","venue":"Mathematics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Junta de Comunidades de Castilla-La Mancha; Universidad de Castilla-La Mancha; Ministerio de Ciencia, Innovación y Universidades","keywords":"Generalization; Cellular automaton; Quarter (Canadian coin); Automaton; Boolean network; Computer science; Theoretical computer science; Boolean function; Artificial intelligence; Epistemology; Algorithm; Philosophy; History","score_opus":0.00836559977208489,"score_gpt":0.2093067752356259,"score_spread":0.200941175463541,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3153969411","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":[0.9477137,0.0013099376,0.050232764,0.000036043395,0.000032021704,0.000042800726,4.731646e-7,0.0000072442785,0.0006250703],"genre_scores_gemma":[0.9861259,0.00011427123,0.013524392,0.000041624906,0.000045726876,0.0000035921585,0.0000036001334,0.000010813537,0.00013010479],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994113,0.0000067042893,0.00011901334,0.00018378017,0.00011365438,0.0001655616],"domain_scores_gemma":[0.9996033,0.000006574757,0.000023535815,0.0002453886,0.000071136325,0.000050087605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026299345,0.000070667425,0.000096564334,0.000039236533,0.000031084717,0.00002903522,0.000087763096,0.000047357793,0.000002897904],"category_scores_gemma":[0.00006826831,0.000072968505,0.000022037957,0.00025486352,0.000049217088,0.0000033198291,0.00013236764,0.000042223597,7.1457265e-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":[0.0000028748552,0.00009385512,0.0010936505,0.00008974983,0.00004908289,0.00002109759,0.00029085611,0.57774436,0.4134112,0.0047856113,0.0003343166,0.002083324],"study_design_scores_gemma":[0.00012812368,0.000011020585,0.00046385094,0.000025783005,0.000014334888,0.000034194185,0.00009447499,0.9752269,0.02271336,0.0007246756,0.00042640776,0.00013687901],"about_ca_topic_score_codex":7.672378e-7,"about_ca_topic_score_gemma":0.000010660437,"teacher_disagreement_score":0.3974825,"about_ca_system_score_codex":0.000013057807,"about_ca_system_score_gemma":0.000054462926,"threshold_uncertainty_score":0.29755694},"labels":[],"label_agreement":null},{"id":"W3154244319","doi":"10.1016/j.patter.2021.100226","title":"A review of dynamical systems approaches for the detection of chaotic attractors in cancer networks","year":2021,"lang":"en","type":"review","venue":"Patterns","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":66,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Concordia University; McGill University","keywords":"Attractor; Causality (physics); Computer science; State space; Dynamical systems theory; Inference; Toolbox; Chaotic; Causal inference; Artificial intelligence; DECIPHER; Cancer; Series (stratigraphy); Machine learning; Bioinformatics; Biology; Mathematics; Econometrics; Statistics","score_opus":0.06562976491930257,"score_gpt":0.31845413232510783,"score_spread":0.2528243674058053,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3154244319","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001299096,0.98663986,0.012069877,0.0000069146377,0.00021303678,0.00086954876,0.000066638786,0.0000017526152,0.000002450707],"genre_scores_gemma":[0.023998806,0.9747571,0.0000061231676,0.000013235017,0.0002807223,0.0005573275,0.0003226075,0.00003627326,0.0000278359],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984537,0.00024493554,0.0006802509,0.00033607273,0.000104013816,0.00018105064],"domain_scores_gemma":[0.998745,0.0000752,0.0005690706,0.000506981,0.00007461705,0.000029104645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040713078,0.00023173992,0.0012226896,0.00004832044,0.00001822324,0.000005879758,0.00024676253,0.00027707827,0.000005828093],"category_scores_gemma":[0.00004027404,0.0001602394,0.0007254926,0.00023000065,0.00003680584,9.815942e-7,0.00007730684,0.00013651175,1.4167446e-7],"study_design_candidate":"design_other","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":[0.000003906744,0.00006095656,0.00032231456,0.18175304,0.0010231948,5.728853e-7,0.000005826651,0.003232668,0.000024934192,0.0000042058155,0.00007154354,0.8134968],"study_design_scores_gemma":[0.00025686037,0.00013631639,0.00020104088,0.21215095,0.006090084,0.000029038381,0.00004801301,0.015493447,0.000095170646,6.7524286e-7,0.7648526,0.0006458455],"about_ca_topic_score_codex":0.000101236095,"about_ca_topic_score_gemma":0.0003097168,"teacher_disagreement_score":0.812851,"about_ca_system_score_codex":0.000043580996,"about_ca_system_score_gemma":0.00010338516,"threshold_uncertainty_score":0.6534373},"labels":[],"label_agreement":null},{"id":"W3160568094","doi":"10.1137/21m1420307","title":"A Graph-Theoretic Condition for Delay Stability of Reaction Systems","year":2022,"lang":"en","type":"article","venue":"SIAM Journal on Applied Dynamical Systems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"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 Mathematical Sciences; Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Ode; Graph; Stability (learning theory); Exponential stability; Mathematics; Directed graph; Work (physics); Applied mathematics; Control theory (sociology); Computer science; Nonlinear system; Discrete mathematics; Physics; Thermodynamics","score_opus":0.0070266135528789415,"score_gpt":0.22788869751302898,"score_spread":0.22086208396015003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3160568094","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":[0.97630274,0.00051163445,0.021199577,0.000027738572,0.00070244045,0.0007192473,0.00009971572,0.000013450353,0.00042343888],"genre_scores_gemma":[0.99898505,0.000025678242,0.00005602622,0.000018050334,0.000322605,0.00024915067,0.0002418372,0.000032053915,0.00006955124],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99799734,0.00031512763,0.00064520084,0.00034144166,0.00042992842,0.0002709301],"domain_scores_gemma":[0.998763,0.000052823532,0.0005527959,0.00035630664,0.00013972273,0.00013532455],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012403724,0.0001804513,0.00036725643,0.00011697237,0.00027946508,0.00003393864,0.00021972072,0.00012829374,0.000014193901],"category_scores_gemma":[0.000026355345,0.00016674338,0.00028503672,0.0001980015,0.00008215315,0.000002983056,0.000056177494,0.00023682832,0.0000012173901],"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":[0.0011059856,0.0003222929,0.00038261394,0.00020679056,0.00046956353,0.00000398664,0.000041975207,0.1614626,0.80945873,0.025342992,0.0008537506,0.00034873877],"study_design_scores_gemma":[0.025905885,0.020810844,0.005104987,0.00056587317,0.0033877422,0.005366339,0.018760787,0.6847281,0.08158815,0.014572919,0.13309273,0.0061156787],"about_ca_topic_score_codex":0.000010137134,"about_ca_topic_score_gemma":0.0000028694167,"teacher_disagreement_score":0.7278706,"about_ca_system_score_codex":0.00018279893,"about_ca_system_score_gemma":0.000061386076,"threshold_uncertainty_score":0.6799598},"labels":[],"label_agreement":null},{"id":"W3164137849","doi":"10.1038/s41598-021-90353-w","title":"A top-down measure of gene-to-gene coordination for analyzing cell-to-cell variability","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"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":"Azrieli Foundation","keywords":"Spurious relationship; Gene expression; Computational biology; Biology; Gene; Biological data; Gene regulatory network; Measure (data warehouse); Biological system; Computer science; Bioinformatics; Data mining; Genetics; Machine learning","score_opus":0.008246968475069333,"score_gpt":0.23251653543689568,"score_spread":0.22426956696182634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3164137849","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":[0.9439119,0.00036834032,0.05367069,0.00012187248,0.001158429,0.0003631375,0.000013282339,0.0000093016115,0.0003830335],"genre_scores_gemma":[0.9831373,0.0000020083696,0.0122250635,0.000037805836,0.00013069026,0.000038917493,0.0003250453,0.000018079978,0.0040850565],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9976934,0.00010153794,0.0005253814,0.0010542681,0.00033541885,0.00028995445],"domain_scores_gemma":[0.99719393,0.000015482377,0.0002545248,0.001300052,0.0010519478,0.00018404867],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022292235,0.00014886382,0.00025064286,0.00012026374,0.00017196199,0.0000731481,0.0001508602,0.00011754769,0.000030776693],"category_scores_gemma":[0.00039856057,0.00015609077,0.0002626506,0.00082888274,0.00005511711,0.0000045325646,0.00012401598,0.000038971346,0.0000035071523],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012940253,0.00009437596,0.00713255,0.000035763023,0.000041389532,0.000010267834,0.000056619665,0.006836377,0.9788187,0.0000023847488,0.006319427,0.00063916633],"study_design_scores_gemma":[0.0001205146,0.000043222448,0.0006945144,0.000007242197,0.000091074384,0.000018045457,0.00003062779,0.00023826289,0.9812109,0.00021371777,0.01716559,0.00016627535],"about_ca_topic_score_codex":0.0000063480816,"about_ca_topic_score_gemma":0.000027950568,"teacher_disagreement_score":0.041445624,"about_ca_system_score_codex":0.000037082213,"about_ca_system_score_gemma":0.00036624676,"threshold_uncertainty_score":0.6365197},"labels":[],"label_agreement":null},{"id":"W3166402839","doi":"10.2139/ssrn.3487085","title":"Absolute Quantification of Transcription Factors Reveals Principles of Gene Regulation in Erythropoiesis","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Stem Cell Network; University of Ottawa","funders":"","keywords":"Erythropoiesis; Transcription factor; Computational biology; Gene; Biology; Transcription (linguistics); Genetics; Medicine; Internal medicine; Anemia","score_opus":0.011994312405088756,"score_gpt":0.2342512600915222,"score_spread":0.22225694768643345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3166402839","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":[0.9893731,0.0022564481,0.00805218,0.000041111052,0.00006303271,0.00014899459,0.0000029702132,0.000002397914,0.00005979262],"genre_scores_gemma":[0.9971138,0.0019132847,0.00017034153,0.00000276058,0.000051352847,0.0000021998574,0.000055688863,0.0000151618615,0.0006754056],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985379,0.00010870445,0.00048351107,0.00018835679,0.00017836387,0.00050315645],"domain_scores_gemma":[0.9991913,0.0000075361622,0.0003938829,0.00025958318,0.000121621124,0.000026092624],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00093908055,0.00010775254,0.00021702594,0.0001432248,0.000027018223,0.000005225991,0.00014700754,0.00011933844,0.000017026192],"category_scores_gemma":[0.000022429158,0.00010251352,0.00016274085,0.000200604,0.000038489416,0.000009684961,0.000011186107,0.00019157979,0.0000016706346],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000062797735,0.0000425857,0.042780593,0.000017376165,0.00012481525,4.131768e-8,0.00005483742,0.010410647,0.94365996,0.0021847377,0.0000044468443,0.00065714703],"study_design_scores_gemma":[0.00077161856,0.00044711612,0.32038876,0.00004485902,0.00009960774,0.000022673894,0.0007765603,0.0007489952,0.67209786,0.00402184,0.00036407515,0.00021603012],"about_ca_topic_score_codex":0.000033344466,"about_ca_topic_score_gemma":0.0004296333,"teacher_disagreement_score":0.2776082,"about_ca_system_score_codex":0.00012533877,"about_ca_system_score_gemma":0.0003388264,"threshold_uncertainty_score":0.418038},"labels":[],"label_agreement":null},{"id":"W3167381487","doi":"10.1101/2021.06.03.446189","title":"NLoed: A Python package for nonlinear optimal experimental design in systems biology","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Rice University","keywords":"Python (programming language); Computer science; Workflow; Modular design; Software; Variety (cybernetics); Documentation; Experimental data; Source code; Computation; Computer engineering; Computational science; Programming language; Artificial intelligence; Database","score_opus":0.016749487648528828,"score_gpt":0.24659025288271566,"score_spread":0.22984076523418684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3167381487","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":[0.9208253,0.014376279,0.062385935,0.000033208944,0.0008601505,0.0012135075,0.00023129096,0.000072625546,0.0000016967925],"genre_scores_gemma":[0.96452117,0.00031114958,0.03294519,0.00007154339,0.001053169,0.00087479514,0.000020638608,0.00019288767,0.00000945901],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99624753,0.00044639982,0.0007206185,0.0016224728,0.00019680678,0.0007661828],"domain_scores_gemma":[0.99739385,0.000041364558,0.00040144808,0.001559838,0.00036852303,0.00023495282],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00083294994,0.0006833103,0.0008576757,0.00024043948,0.00010875787,0.0001790211,0.00061567285,0.0011648013,0.000012876443],"category_scores_gemma":[0.00015342626,0.0007806845,0.00038798814,0.00033628196,0.00012886047,0.000008672268,0.00067140826,0.00037694103,0.0000074671207],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000985844,0.00021465562,0.001916261,0.00016156396,0.00035451763,0.000029234725,0.000007422734,0.009190604,0.9877039,0.000030457428,0.00029187693,9.020797e-7],"study_design_scores_gemma":[0.00094226416,0.00023479144,0.0011545123,0.00017160451,0.0001379497,8.020956e-8,0.000027262386,0.010191811,0.98255956,2.1238489e-7,0.0036437267,0.0009362301],"about_ca_topic_score_codex":0.000040523122,"about_ca_topic_score_gemma":0.000004873333,"teacher_disagreement_score":0.043695863,"about_ca_system_score_codex":0.00019700594,"about_ca_system_score_gemma":0.0007308463,"threshold_uncertainty_score":0.9994644},"labels":[],"label_agreement":null},{"id":"W3168446627","doi":"10.1007/s00285-021-01693-0","title":"Operon dynamics with state dependent transcription and/or translation delays","year":2021,"lang":"en","type":"article","venue":"Journal of Mathematical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Science Foundation of Sri Lanka; Natural Sciences and Engineering Research Council of Canada; Alexander von Humboldt-Stiftung; National Science Foundation","keywords":"Multistability; Mathematics; Translation (biology); State space; Homoclinic orbit; Operon; Control theory (sociology); Bifurcation; Statistical physics; Computer science; Physics; Gene; Biology; Genetics; Nonlinear system; Messenger RNA; Control (management); Artificial intelligence; Statistics","score_opus":0.013590768953632006,"score_gpt":0.25031859801383977,"score_spread":0.23672782906020776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3168446627","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":[0.7329269,0.0009112266,0.26573694,0.00024102943,0.000029852328,0.00003886142,0.000004126061,0.0000018345711,0.00010925366],"genre_scores_gemma":[0.98277783,0.0004059995,0.016474538,0.000074027426,0.000075187694,0.0000011333155,0.000022694816,0.000011420586,0.00015714708],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991656,0.0000965017,0.00035518,0.0001390264,0.00009897079,0.00014475311],"domain_scores_gemma":[0.9994651,0.00003319054,0.00014207965,0.00011815199,0.00015677774,0.0000847181],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037169436,0.00010197154,0.00023386332,0.00004433471,0.00002989967,0.000012741458,0.00007024502,0.00012039205,0.000047104557],"category_scores_gemma":[0.000035655416,0.000065873704,0.000080402664,0.00007503712,0.0000705164,0.000004808913,0.000015295853,0.00009754005,0.0000016832671],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011098755,0.00026091855,0.0018184659,0.00010565358,0.0006636078,0.00009666162,0.0001959754,0.0008988195,0.94953895,0.0013099816,0.00006136931,0.043939713],"study_design_scores_gemma":[0.010909267,0.011354958,0.004749561,0.00040252766,0.0021134105,0.015780011,0.0022571553,0.028853059,0.88297075,0.030140039,0.008869502,0.0015997582],"about_ca_topic_score_codex":5.378279e-7,"about_ca_topic_score_gemma":0.00009105409,"teacher_disagreement_score":0.24985096,"about_ca_system_score_codex":0.000016506492,"about_ca_system_score_gemma":0.00007377697,"threshold_uncertainty_score":0.26862517},"labels":[],"label_agreement":null},{"id":"W3172489267","doi":"10.4236/am.2021.125031","title":"Reducing Stochastic Discrete Models of Biochemical Networks","year":2021,"lang":"en","type":"article","venue":"Applied Mathematics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Stochastic modelling; Computer science; Stochastic process; Systems biology; Reduction (mathematics); Mathematical model; Sensitivity (control systems); Biological system; Work (physics); Mathematical optimization; Biochemical engineering; Mathematics; Bioinformatics; Engineering; Biology","score_opus":0.010733712371195744,"score_gpt":0.22753763748423975,"score_spread":0.216803925113044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3172489267","genre_codex":"methods","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":[0.33719954,0.0010114898,0.6594912,0.000024435043,0.000039996226,0.0001128453,0.000004756834,0.000013903113,0.0021018411],"genre_scores_gemma":[0.96400356,0.000053845197,0.03543746,0.000033232172,0.00014938384,0.000017460217,0.00010229229,0.000034489556,0.00016825084],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99894583,0.000012317603,0.0003430442,0.00030857127,0.00016071188,0.00022952358],"domain_scores_gemma":[0.9990381,0.000024014198,0.00014895057,0.00062382873,0.00008772131,0.000077355304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013805035,0.00016141847,0.00028106445,0.000025482683,0.000039945957,0.000012106419,0.00016367421,0.00015905623,0.00001930233],"category_scores_gemma":[0.000029713407,0.00016026867,0.00013887387,0.00018187771,0.000078018915,0.0000016178809,0.00018528911,0.00007860196,0.0000032879777],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011734827,0.00009210173,0.0000028953627,0.00007243863,0.00019141557,0.0000014571397,0.00008632027,0.3295344,0.6627971,0.0057009626,0.0010787041,0.0004304652],"study_design_scores_gemma":[0.00048119933,0.00003699627,0.000009207939,0.0000717264,0.00030564502,0.000034105535,0.00037909087,0.2989008,0.68790406,0.011318272,0.00012377795,0.0004351029],"about_ca_topic_score_codex":8.866336e-7,"about_ca_topic_score_gemma":0.0000012630414,"teacher_disagreement_score":0.62680405,"about_ca_system_score_codex":0.000009764849,"about_ca_system_score_gemma":0.000058154146,"threshold_uncertainty_score":0.65355664},"labels":[],"label_agreement":null},{"id":"W3172623022","doi":"10.1016/j.cels.2021.05.011","title":"Context-aware synthetic biology by controller design: Engineering the mammalian cell","year":2021,"lang":"en","type":"review","venue":"Cell Systems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":87,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Natural Sciences and Engineering Research Council of Canada; Natural Resources, Energy and Science Authority of Sri Lanka; National Institutes of Health; National Science Foundation","keywords":"Synthetic biology; Context (archaeology); Computer science; Regenerative medicine; Systems biology; Biology; Computational biology; Cell; Genetics","score_opus":0.01754311873939665,"score_gpt":0.23944786856385136,"score_spread":0.2219047498244547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3172623022","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00002377628,0.9898949,0.008167157,0.0000081223725,0.0006714391,0.0009758317,0.000077449375,0.000021567488,0.0001597083],"genre_scores_gemma":[0.022100275,0.9690486,0.000023858667,0.000029490355,0.00058088655,0.00040057133,0.00076055527,0.00014473389,0.0069110096],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9967349,0.0009708051,0.0007608243,0.000842877,0.0001475416,0.0005430182],"domain_scores_gemma":[0.99809754,0.00014248023,0.00047366283,0.0010308033,0.00010562826,0.00014988807],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00057862926,0.0006563556,0.0017978096,0.00006928175,0.00012101437,0.00009187865,0.0006873532,0.00084579876,0.000029110715],"category_scores_gemma":[0.000029119723,0.00045920964,0.000918003,0.00022067533,0.000075496886,0.0000014824428,0.00017350193,0.00028679371,0.00007990662],"study_design_candidate":"not_applicable","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":[0.00006535471,0.0006997101,0.00007605176,0.067237094,0.011528132,0.0001803847,0.0001653254,0.019209817,0.041442074,0.00025360569,0.41846687,0.4406756],"study_design_scores_gemma":[0.00022159547,0.00005656216,5.639837e-8,0.0008629875,0.0009871242,0.000043323605,0.000041322382,0.00043809228,0.0008054874,3.1443628e-7,0.9960547,0.00048841647],"about_ca_topic_score_codex":0.000040102896,"about_ca_topic_score_gemma":0.0000038846774,"teacher_disagreement_score":0.57758784,"about_ca_system_score_codex":0.00006383417,"about_ca_system_score_gemma":0.00019802156,"threshold_uncertainty_score":0.99978596},"labels":[],"label_agreement":null},{"id":"W3174337114","doi":"10.1063/5.0058345","title":"Introduction to Focus Issue: Dynamical disease: A translational approach","year":2021,"lang":"en","type":"article","venue":"Chaos An Interdisciplinary Journal of Nonlinear Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université de Montréal; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Society for Mathematical Biology; Simons Foundation","keywords":"Dynamical systems theory; Redress; Analogy; Focus (optics); Statistical physics; Computer science; Field (mathematics); Nonlinear dynamical systems; Dynamical system (definition); Cognitive science; Management science; Mathematics; Physics; Psychology; Epistemology; Engineering; Quantum mechanics; Political science; Nonlinear system; Pure mathematics; Philosophy","score_opus":0.009182642357932072,"score_gpt":0.297375456941156,"score_spread":0.28819281458322393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3174337114","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":[0.9345711,0.0006053642,0.057500973,0.006646159,0.0004527846,0.00007248297,0.00001415554,0.000005039806,0.00013194597],"genre_scores_gemma":[0.9663896,0.000021290374,0.028716322,0.00007846273,0.004347765,0.0000024590904,0.000047730686,0.000014933362,0.00038142945],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983802,0.00007075514,0.0003710174,0.00045458638,0.0004803643,0.00024308899],"domain_scores_gemma":[0.99839085,0.000005213412,0.00013788824,0.00040607198,0.0006239165,0.0004360363],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006047758,0.00013486332,0.00018579031,0.00017072512,0.00025192226,0.00007457139,0.00047592205,0.00005221027,0.0000875067],"category_scores_gemma":[0.00007355095,0.00011953441,0.00018326593,0.00061815855,0.00024621404,0.00003874059,0.00033192773,0.00013649052,0.000009676037],"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":[0.0007826302,0.0011824028,0.0020465178,0.00003645755,0.00016357932,0.00011024854,0.001032132,0.06736176,0.8956913,0.00018187938,0.0055499747,0.025861127],"study_design_scores_gemma":[0.0036060316,0.005301628,0.105640344,0.00027604628,0.00074440404,0.0061212257,0.006250336,0.46801373,0.31130522,0.0030605728,0.08700786,0.0026726115],"about_ca_topic_score_codex":2.9332782e-7,"about_ca_topic_score_gemma":0.0000054167813,"teacher_disagreement_score":0.58438605,"about_ca_system_score_codex":0.000039714072,"about_ca_system_score_gemma":0.00047894786,"threshold_uncertainty_score":0.48744717},"labels":[],"label_agreement":null},{"id":"W3175565214","doi":"10.1007/978-3-030-78710-3_52","title":"Sensitivity Analysis of a Smooth Muscle Cell Electrophysiological Model","year":2021,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lawson Health Research Institute; Western University","funders":"","keywords":"Computer science; Sensitivity (control systems); Mathematical model; Biological system; Linear model; Model validation; Artificial intelligence; Machine learning; Mathematics; Electronic engineering; Biology","score_opus":0.009418319421258672,"score_gpt":0.22026502029636724,"score_spread":0.21084670087510857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3175565214","genre_codex":"methods","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":[0.1287648,0.00075932464,0.8698756,0.000024879708,0.00006201427,0.000081391445,0.00001392244,0.00000785194,0.00041019855],"genre_scores_gemma":[0.9724328,0.00013368363,0.026665326,0.0002467497,0.00015269089,0.0000017416336,0.00009813906,0.000018705301,0.0002501635],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99778193,0.00005712605,0.00032081205,0.0011056613,0.00037820154,0.00035627],"domain_scores_gemma":[0.99846095,0.000052357613,0.00022063885,0.00093652605,0.00024193048,0.000087620836],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00036126087,0.00031783836,0.0006518457,0.0003857202,0.00007024703,0.00003218861,0.000415077,0.00037170804,0.000018035145],"category_scores_gemma":[0.000032496817,0.00029219556,0.0004764046,0.00069585326,0.00043712975,0.0000037247873,0.0005029283,0.00025807208,0.0000011743628],"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":[0.000008080764,0.000024320627,0.000042371023,0.000008432343,0.00011028561,0.000011515454,0.00001387304,0.70059025,0.28648332,0.00004268668,0.000004490254,0.012660347],"study_design_scores_gemma":[0.000104387014,0.00014958718,0.00086578174,0.000022145907,0.00038950364,0.000002450972,1.3802567e-7,0.9281354,0.06842344,0.0013709421,0.00013447944,0.0004017443],"about_ca_topic_score_codex":0.000011379762,"about_ca_topic_score_gemma":0.00018657757,"teacher_disagreement_score":0.843668,"about_ca_system_score_codex":0.000054951604,"about_ca_system_score_gemma":0.0003314439,"threshold_uncertainty_score":0.99995303},"labels":[],"label_agreement":null},{"id":"W3176012593","doi":"10.1096/fasebj.2019.33.1_supplement.600.4","title":"Multi ∑ QEME of Human Molecular Cell Sustainability in Psycho‐Neuro‐Endo Processes","year":2019,"lang":"en","type":"article","venue":"The FASEB Journal","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Parkwood Institute","funders":"","keywords":"Organism; Photobiology; Neuroscience; Living systems; Computer science; Conceptualization; Biology; Cognitive science; Biochemical engineering; Biological system; Ecology; Psychology; Artificial intelligence; Engineering","score_opus":0.0075664252487040555,"score_gpt":0.25416002811204025,"score_spread":0.2465936028633362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3176012593","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":[0.99766624,0.0011604268,0.00048625792,0.0001499426,0.000055241555,0.0001816829,0.0000022632107,0.0000030559836,0.00029490484],"genre_scores_gemma":[0.999128,0.000078937526,0.00015621951,0.00008278346,0.00007095827,0.000003919513,0.0000071804448,0.000018779705,0.00045323922],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99881613,0.00019403415,0.00032655074,0.000227323,0.0001738823,0.00026207647],"domain_scores_gemma":[0.99897444,0.000015842366,0.0002136482,0.00047223552,0.00025677634,0.000067061825],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004951195,0.00013963462,0.0001907117,0.0000702255,0.00006694852,0.00002053276,0.0004000784,0.0000788323,0.000049814458],"category_scores_gemma":[0.00007907731,0.00010418889,0.00015024412,0.00023234956,0.00008311867,0.0000044632166,0.00008732602,0.00019551755,0.0000048114016],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004183231,0.0001239378,0.047976635,0.00006731811,0.00003934569,0.000008400531,0.00008116404,0.004667659,0.9467064,0.000006338586,0.00013394572,0.0001469919],"study_design_scores_gemma":[0.0010638478,0.0002553229,0.010012029,0.000017383476,0.000047830592,0.00003242617,0.00044945834,0.00021709342,0.98685986,0.00029526599,0.0005807349,0.0001687628],"about_ca_topic_score_codex":0.000011833664,"about_ca_topic_score_gemma":0.000027743557,"teacher_disagreement_score":0.040153414,"about_ca_system_score_codex":0.000027397768,"about_ca_system_score_gemma":0.00017212845,"threshold_uncertainty_score":0.42486998},"labels":[],"label_agreement":null},{"id":"W3177141004","doi":"10.1016/j.ejps.2021.105919","title":"A mean-field approach for modeling the propagation of perturbations in biochemical reaction networks","year":2021,"lang":"en","type":"article","venue":"European Journal of Pharmaceutical Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Princess Margaret Cancer Centre; University of Waterloo","funders":"Canadian Institutes of Health Research","keywords":"Perturbation (astronomy); Ordinary differential equation; Computer science; Network model; Biological system; Computational biology; Differential equation; Biology; Mathematics; Physics; Artificial intelligence","score_opus":0.050072219697622246,"score_gpt":0.31623599441449024,"score_spread":0.266163774716868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3177141004","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":[0.6936543,0.0022955018,0.3025666,0.00065667887,0.00007899692,0.00007524442,5.5812626e-7,0.0000013768714,0.00067077554],"genre_scores_gemma":[0.9954143,0.00023633748,0.003916677,0.0001298504,0.0002746354,0.0000012371644,0.000004269596,0.000005028281,0.000017619945],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998993,0.00025724672,0.00031884856,0.0001380373,0.00016738518,0.00012548185],"domain_scores_gemma":[0.999508,0.00004237332,0.0001370998,0.000082559236,0.00018079515,0.00004917028],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016214749,0.0000589629,0.000094994604,0.000036464167,0.000075792,0.00002004593,0.00019723432,0.000024405415,0.0000035366356],"category_scores_gemma":[0.00022027871,0.000039067843,0.00011229601,0.00027481082,0.000094879666,0.000008624704,0.000045108,0.00011181591,1.2855551e-7],"study_design_candidate":"simulation_or_modeling","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":[0.00007457985,0.000092215756,0.00040059077,0.000011078297,0.000042098232,0.0000022349304,0.00007141439,0.20571107,0.7871217,0.0001627781,0.0003125251,0.005997689],"study_design_scores_gemma":[0.0004164849,0.00019137662,0.00026585592,0.00002393156,0.000073191004,0.00005358656,0.0003412226,0.84080166,0.15637445,0.000048031845,0.0013259852,0.00008422965],"about_ca_topic_score_codex":6.2350534e-7,"about_ca_topic_score_gemma":0.0000011196737,"teacher_disagreement_score":0.6350906,"about_ca_system_score_codex":0.000008974126,"about_ca_system_score_gemma":0.000070596274,"threshold_uncertainty_score":0.15931404},"labels":[],"label_agreement":null},{"id":"W3180999567","doi":"10.1139/cjm-2020-0549","title":"Advancing undergraduate synthetic biology education: insights from a Canadian iGEM student perspective","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Microbiology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"University of Ottawa; Institute for Work & Health; University of Calgary; McGill University; Concordia University; Queen's University; University of Waterloo; Institute for Christian Studies; University of Toronto","funders":"","keywords":"Synthetic biology; Transformative learning; Perspective (graphical); Competition (biology); Engineering ethics; Biology; Psychology; Pedagogy; Computer science; Computational biology; Ecology; Engineering; Artificial intelligence","score_opus":0.0038879905476243426,"score_gpt":0.2274070712815296,"score_spread":0.22351908073390525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3180999567","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":[0.96129286,0.032533403,0.00027774097,0.003404038,0.0011498984,0.00007764221,0.00007263372,0.0000022113836,0.0011895814],"genre_scores_gemma":[0.9964732,0.00027013154,0.0007681302,0.0012617235,0.0006206343,0.0000027916346,0.00019393938,0.000024286624,0.0003851763],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99843633,0.0003027851,0.00037769187,0.00037801624,0.000033537304,0.00047164722],"domain_scores_gemma":[0.99780494,0.000024531611,0.00021441924,0.00036984615,0.0007656368,0.0008206277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000119918746,0.00019957291,0.00034379258,0.0003121394,0.00017944504,0.000030973606,0.0003504657,0.0002630745,0.00016455677],"category_scores_gemma":[0.00015139363,0.0002006426,0.00021112437,0.00021928639,0.00018065357,0.000005452444,0.00003520412,0.0002084096,0.00002238031],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017236684,0.000054871613,0.018833255,0.0000049884025,0.0010682328,0.0002547219,0.0005152492,0.0005056293,0.96212363,0.0020105604,0.012934955,0.0016766544],"study_design_scores_gemma":[0.0010066279,0.0004665014,0.010603438,0.00011566398,0.00045278828,0.0025294751,0.007674531,0.000009981181,0.09089754,0.00543727,0.8799526,0.000853593],"about_ca_topic_score_codex":0.061559685,"about_ca_topic_score_gemma":0.9057353,"teacher_disagreement_score":0.87122613,"about_ca_system_score_codex":0.0005403737,"about_ca_system_score_gemma":0.012797183,"threshold_uncertainty_score":0.99279934},"labels":[],"label_agreement":null},{"id":"W3183856934","doi":"10.1016/j.ifacol.2021.06.174","title":"Insights from a qualitative analysis of a gene expression model with delays","year":2021,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"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 Lethbridge","funders":"","keywords":"Stability (learning theory); Translation (biology); Expression (computer science); Substrate (aquarium); Control theory (sociology); Computer science; Mathematics; Biological system; Chemistry; Control (management); Gene; Biology; Messenger RNA; Biochemistry; Ecology","score_opus":0.01440325626176632,"score_gpt":0.280921031486626,"score_spread":0.2665177752248597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3183856934","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":[0.9447675,0.0027529022,0.051959056,0.0000832291,0.000014735619,0.0000580401,0.00019337899,0.000009417765,0.00016173613],"genre_scores_gemma":[0.73309183,0.00008916443,0.264371,0.0001200544,0.000070263704,0.000009291898,0.0018467305,0.000019870322,0.00038177322],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985113,0.0001722385,0.000303447,0.0005653636,0.00026866494,0.00017896696],"domain_scores_gemma":[0.9987594,0.00003082151,0.000183416,0.00062656513,0.00029021173,0.00010960554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000660661,0.00021301485,0.00045921287,0.00011528166,0.000060464503,0.000011722039,0.00015989956,0.00015837848,0.00005088938],"category_scores_gemma":[0.000036440222,0.00017376275,0.0003046327,0.00071354717,0.00008110714,0.0000051943734,0.00008283015,0.00007609899,0.000002127629],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011032643,0.00011627975,0.0005646693,0.00000527974,0.002391326,0.000010458155,0.0013698047,0.10851437,0.8867529,0.00001574401,0.000008165498,0.00014065065],"study_design_scores_gemma":[0.00070740207,0.000115225026,0.0010045946,0.000024854076,0.0021503,0.0000020701966,0.0025900002,0.12495449,0.8679651,0.00007933949,0.000078018915,0.00032858906],"about_ca_topic_score_codex":0.00005081122,"about_ca_topic_score_gemma":0.0008241558,"teacher_disagreement_score":0.21241194,"about_ca_system_score_codex":0.000017035107,"about_ca_system_score_gemma":0.00014326099,"threshold_uncertainty_score":0.7085839},"labels":[],"label_agreement":null},{"id":"W3188894553","doi":"10.3390/biomimetics6030050","title":"Are There Biomimetic Lessons from Genetic Regulatory Networks for Developing a Lunar Industrial Ecology?","year":2021,"lang":"en","type":"review","venue":"Biomimetics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Industrial ecology; Robustness (evolution); Ecology; Synthetic biology; Architecture; Factory (object-oriented programming); Computer science; Engineering; Systems engineering; Biology; Computational biology; Geography; Sustainability","score_opus":0.08101239824098327,"score_gpt":0.32438674906747045,"score_spread":0.24337435082648717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3188894553","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0024278385,0.98864186,0.0056996923,0.00007686782,0.0013674858,0.0013047059,0.0004233807,0.000045259723,0.000012933856],"genre_scores_gemma":[0.000799325,0.982893,0.007652619,0.00015003944,0.0037158001,0.00038257075,0.0035575263,0.00031962976,0.00052949844],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9949516,0.0006971468,0.0013624484,0.0017488559,0.00029104124,0.0009488845],"domain_scores_gemma":[0.9957602,0.00023910271,0.0016223767,0.0018168093,0.0003012788,0.000260211],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00048372505,0.0011115207,0.0028132354,0.00028424192,0.00025136647,0.00013433471,0.0010058649,0.0029434585,0.000047617978],"category_scores_gemma":[0.00030813605,0.001078852,0.0018270452,0.0007712802,0.00026838493,0.0000037157497,0.0006356388,0.00042302403,0.000023513347],"study_design_candidate":"not_applicable","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":[0.00007473006,0.00029501144,0.00061272614,0.002731816,0.011413365,0.00013340318,0.000012109181,0.0007901879,0.00031981547,0.00024458783,0.040550876,0.9428214],"study_design_scores_gemma":[0.0007530949,0.00009843898,0.00013355972,0.0024844988,0.0048337923,0.000025280551,0.000023637078,0.00023062,0.00031621222,0.00004542724,0.989774,0.0012814201],"about_ca_topic_score_codex":0.000010417845,"about_ca_topic_score_gemma":0.00008331709,"teacher_disagreement_score":0.94922316,"about_ca_system_score_codex":0.00022595427,"about_ca_system_score_gemma":0.001412526,"threshold_uncertainty_score":0.9991662},"labels":[],"label_agreement":null},{"id":"W3190148550","doi":"10.1103/physreve.104.024402","title":"Multilayer network structure enhances the coexistence of competitive species","year":2021,"lang":"en","type":"article","venue":"Physical review. E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University; Université de Montréal","funders":"National Safety Academic Fund; Fundamental Research Funds for the Central Universities; National Key Research and Development Program of China; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Master equation; Bursting; Gene regulatory network; Biological system; RNA splicing; Alternative splicing; Steady state (chemistry); Marginal distribution; Computer science; Statistical physics; Joint probability distribution; Messenger RNA; Gene expression; Computational biology; Gene; Mathematics; Biology; Chemistry; Physics; RNA; Genetics; Statistics; Neuroscience","score_opus":0.01201961639643149,"score_gpt":0.2905905102529579,"score_spread":0.2785708938565264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3190148550","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":[0.92515635,0.0713692,0.00025342975,0.0005861147,0.000113562215,0.00018500055,0.000024629742,0.0000057464276,0.0023059503],"genre_scores_gemma":[0.9864709,0.011622341,0.00025714285,0.0005788336,0.00066078955,0.000007412428,0.000054593736,0.000009292747,0.00033871096],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990973,0.0001476963,0.00017712868,0.00025072502,0.00016340333,0.00016376028],"domain_scores_gemma":[0.9991769,0.00004143682,0.00012410952,0.0004430903,0.00017528869,0.00003916899],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000082623206,0.00012500303,0.000303347,0.0000036649558,0.000057589114,0.000008043291,0.00020429131,0.000029067563,0.00006207058],"category_scores_gemma":[0.00008709719,0.00008234548,0.00024350517,0.00021181826,0.00015175354,0.0000018533642,0.00013142817,0.00007919301,0.0000067291758],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009665784,0.00005423216,0.0005592653,0.00019655809,0.00020345069,0.0000023633631,0.000037908612,0.0006900341,0.98759836,0.0033685956,0.005493003,0.0017865658],"study_design_scores_gemma":[0.00010005697,0.000052851476,0.0048155743,0.00030792845,0.00020466569,0.000005691087,0.000056775192,0.00021327558,0.8499996,0.00080614066,0.14325625,0.00018119217],"about_ca_topic_score_codex":0.0000013907362,"about_ca_topic_score_gemma":0.000031954096,"teacher_disagreement_score":0.13776325,"about_ca_system_score_codex":0.00000494599,"about_ca_system_score_gemma":0.00004223241,"threshold_uncertainty_score":0.33579513},"labels":[],"label_agreement":null},{"id":"W3191293713","doi":"10.4236/jamp.2021.98120","title":"A Modified Inhomogeneous Stochastic Simulation Algorithm to Model Reactive Boundary Conditions","year":2021,"lang":"en","type":"article","venue":"Journal of Applied Mathematics and Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Jump; Boundary (topology); Computer science; Constraint (computer-aided design); Grid; Mathematical optimization; Position (finance); Algorithm; Expression (computer science); Process (computing); Applied mathematics; Mathematics; Physics; Mathematical analysis; Geometry","score_opus":0.013330495391015449,"score_gpt":0.2602571462554898,"score_spread":0.24692665086447435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3191293713","genre_codex":"methods","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":[0.3175007,0.00009672235,0.68204457,0.000021516156,0.00002305841,0.000068307614,0.000015912303,0.0000021185751,0.00022706146],"genre_scores_gemma":[0.91691625,0.000021912883,0.082600854,0.00010764136,0.00025093424,0.0000049210917,0.000029164914,0.000020561747,0.000047737445],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992517,0.000007784927,0.00029175577,0.00014491976,0.0001803417,0.00012346442],"domain_scores_gemma":[0.99914795,0.000029824463,0.00023618618,0.00019136321,0.00028072437,0.00011392899],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011531075,0.00012639495,0.0002448991,0.00002676394,0.000086673885,0.000038551098,0.00007175639,0.00007067326,0.0000025691659],"category_scores_gemma":[0.000019256533,0.000122006946,0.00010488278,0.00012167072,0.000033426022,0.0000045460133,0.00006443445,0.000087501685,0.0000015135371],"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":[0.000019597488,0.00011387658,3.7655894e-7,0.000015732625,0.00017245402,0.0000034568254,0.00025520698,0.8640373,0.12946133,0.0012352318,0.00010966946,0.0045757825],"study_design_scores_gemma":[0.00040085678,0.00008354321,0.000007520382,0.000026102627,0.0002309179,0.000047339832,0.00020104446,0.911165,0.033793736,0.053715248,0.0001448697,0.00018380395],"about_ca_topic_score_codex":1.8833352e-7,"about_ca_topic_score_gemma":8.490445e-7,"teacher_disagreement_score":0.59944373,"about_ca_system_score_codex":0.000017783697,"about_ca_system_score_gemma":0.00014524741,"threshold_uncertainty_score":0.49752986},"labels":[],"label_agreement":null},{"id":"W3192533213","doi":"10.5772/intechopen.99329","title":"Synthetic Gene Circuits for Antimicrobial Resistance and Cancer Research","year":2021,"lang":"en","type":"book-chapter","venue":"IntechOpen eBooks","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Laufer Center for Physical and Quantitative Biology, Stony Brook University; National Defense Science and Engineering Graduate; Government of Canada; National Institutes of Health; University of Alberta; National Institute of General Medical Sciences","keywords":"Synthetic biology; Electronic circuit; Computational biology; Rational design; Gene; Biology; Computer science; Biochemical engineering; Genetics; Engineering","score_opus":0.03543124410998327,"score_gpt":0.30224882925865,"score_spread":0.2668175851486667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3192533213","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034047168,0.06093552,0.0024197833,0.00081838836,0.0010410815,0.0038327524,0.0010736617,0.00007663699,0.895755],"genre_scores_gemma":[0.09104603,0.0017360515,0.0004808426,0.0001818365,0.0007622186,0.00015862835,0.0001786636,0.00015075035,0.90530497],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979355,0.000058083868,0.00034011435,0.0010043939,0.00024538697,0.00041656932],"domain_scores_gemma":[0.9982694,0.000040116287,0.00014816958,0.00084660633,0.0005738835,0.000121818855],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00049111206,0.00033860913,0.00044727427,0.00013976873,0.00020638487,0.00009355661,0.0003967523,0.0006027729,0.00007664836],"category_scores_gemma":[0.000055477485,0.00036413135,0.00025245378,0.000023578357,0.00035416498,0.0000015504597,0.00041273548,0.0003288447,0.000008364153],"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":[0.00012708962,0.000013228234,0.0000070473598,0.00024906662,0.00084159244,0.000031640906,0.000038482925,0.000010474927,0.9353033,0.0037033854,0.03062566,0.029049058],"study_design_scores_gemma":[0.00025583294,0.000049420734,0.000002091316,0.00037780267,0.00013722143,0.000017626617,0.000007675638,0.00000296507,0.3152977,0.000984114,0.68250155,0.00036598742],"about_ca_topic_score_codex":0.000016705133,"about_ca_topic_score_gemma":0.00062937796,"teacher_disagreement_score":0.6518759,"about_ca_system_score_codex":0.00006995502,"about_ca_system_score_gemma":0.00036408522,"threshold_uncertainty_score":0.9998811},"labels":[],"label_agreement":null},{"id":"W3195724427","doi":"10.1503/jpn.210141","title":"Randomness and nondeterminism: from genes to free will with implications for psychiatry","year":2021,"lang":"en","type":"editorial","venue":"Journal of Psychiatry and Neuroscience","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; Douglas College","funders":"McGill University","keywords":"Randomness; Dice; Selection (genetic algorithm); Gene; Computer science; Genetics; Psychology; Philosophy; Cognitive science; Biology; Artificial intelligence; Computational biology; Mathematics; Statistics","score_opus":0.007049244917046724,"score_gpt":0.26146605349580576,"score_spread":0.25441680857875903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3195724427","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3503545,0.026079617,0.017176526,0.0058118543,0.59944123,0.00046079714,0.0006491446,0.000007765771,0.000018584948],"genre_scores_gemma":[0.03222534,0.0089364555,0.04690486,0.0014731422,0.9097145,0.000059440987,0.00012365085,0.000120724726,0.00044186186],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99838674,0.000068551206,0.0004322517,0.0006011171,0.00028003217,0.00023129248],"domain_scores_gemma":[0.998323,0.000073574716,0.0005031413,0.00052359916,0.00032323418,0.00025344695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027104391,0.00026498546,0.00044553122,0.00010246668,0.00022067041,0.00012599837,0.00051896315,0.00028595308,0.0000013873386],"category_scores_gemma":[0.00018975777,0.0002136841,0.00017145864,0.00020240649,0.00014492612,0.000016409625,0.00015998005,0.00021756634,6.87224e-8],"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":[0.0007247131,0.00015809035,0.01177115,0.000114870774,0.0001526027,0.000003183909,0.00002326705,0.00022578433,0.06701278,0.00004352557,0.9182622,0.001507842],"study_design_scores_gemma":[0.0057757027,0.003293432,0.014346206,0.00037899587,0.0011204962,0.00023205153,0.00010216067,0.000043450418,0.0023389233,0.0019181635,0.96950895,0.00094145647],"about_ca_topic_score_codex":0.000003413295,"about_ca_topic_score_gemma":0.00015818584,"teacher_disagreement_score":0.31812915,"about_ca_system_score_codex":0.000006188281,"about_ca_system_score_gemma":0.0008275174,"threshold_uncertainty_score":0.8713785},"labels":[],"label_agreement":null},{"id":"W3196465538","doi":"10.1101/2021.08.30.458258","title":"Quantifying biochemical reaction rates from static population variability within complex networks","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"University of Toronto","funders":"Connaught Fund; Natural Sciences and Engineering Research Council of Canada; Council for Higher Education; Ben-Gurion University of the Negev; University of Toronto","keywords":"Inference; Computer science; Statistical inference; Population; Sequence (biology); Systems biology; Complex system; Computational biology; Biology; Mathematics; Artificial intelligence; Statistics; Genetics","score_opus":0.02257547826027657,"score_gpt":0.2511589582833071,"score_spread":0.22858348002303053,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3196465538","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":[0.97815055,0.0013012686,0.018903332,0.0000630645,0.0009131307,0.0004275813,0.00011466097,0.00012492969,0.0000015113598],"genre_scores_gemma":[0.9863873,0.00023315125,0.011763507,0.00014172336,0.0010934361,0.00008857454,0.00014882047,0.00014168464,0.0000018195055],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99571514,0.00066826644,0.0009100565,0.0017805628,0.00038884528,0.0005371404],"domain_scores_gemma":[0.9963648,0.00006600205,0.0007551285,0.001995086,0.0005444554,0.00027456504],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010217974,0.00067664095,0.00076753215,0.00011954921,0.00019983077,0.0002662018,0.0004644185,0.001109261,0.0000434471],"category_scores_gemma":[0.00039153942,0.0007864804,0.0003515988,0.00044813342,0.00012171651,0.000016462853,0.00065758516,0.00067162875,0.000007183264],"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":[0.000049618713,0.00011612497,0.06787283,0.00010803114,0.0005010135,0.000008843028,0.0000046508626,0.009902646,0.9211663,0.00001846739,0.00024946313,0.0000020081955],"study_design_scores_gemma":[0.000446458,0.000038999024,0.48351496,0.00023507225,0.00054183125,3.648469e-8,0.000010165848,0.045933817,0.46783948,0.000004831579,0.00027826955,0.001156053],"about_ca_topic_score_codex":0.00038714925,"about_ca_topic_score_gemma":0.00004459495,"teacher_disagreement_score":0.45332682,"about_ca_system_score_codex":0.00023021914,"about_ca_system_score_gemma":0.00034289432,"threshold_uncertainty_score":0.9994586},"labels":[],"label_agreement":null},{"id":"W3196874416","doi":"10.1103/physreve.104.044406","title":"Inferring gene regulation dynamics from static snapshots of gene expression variability","year":2021,"lang":"en","type":"preprint","venue":"Physical review. E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto; Connaught Fund; Harvard Medical School; National Science Foundation","keywords":"Computational biology; Biology; Gene; Gene regulatory network; Regulation of gene expression; Population; Systems biology; Gene expression; Dynamics (music); Genetics; Physics","score_opus":0.012387890670312129,"score_gpt":0.2964608737609468,"score_spread":0.28407298309063467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3196874416","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":[0.94792193,0.012517657,0.03868755,0.00006705716,0.00014548138,0.00040499165,0.00012768748,0.000012368252,0.000115294824],"genre_scores_gemma":[0.9760414,0.0074089044,0.008239017,0.00008518842,0.00047511427,0.00006488259,0.0076217595,0.00004346573,0.000020282221],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9972904,0.0005044149,0.00066818035,0.00092571194,0.0003757901,0.00023553503],"domain_scores_gemma":[0.99724674,0.00006054018,0.000585161,0.001683172,0.00030132293,0.00012303812],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003888194,0.00037148272,0.0009534889,0.000030243433,0.000041624884,0.000023711531,0.00037321143,0.00023252677,0.00006009234],"category_scores_gemma":[0.00031621713,0.0003614465,0.0006270697,0.00016122866,0.00007535902,0.00000502217,0.0008288141,0.00027431114,0.000003122364],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017877699,0.00023103533,0.0024335897,0.0014342308,0.00030251942,0.0000017379696,0.000036535923,0.013961872,0.9768788,0.000028298984,0.00020985153,0.004463632],"study_design_scores_gemma":[0.00023358138,0.00005158029,0.010806765,0.002120942,0.0009992351,0.000001454491,0.000010636115,0.041883618,0.9374254,0.0054834657,0.00034542207,0.00063792],"about_ca_topic_score_codex":0.00004906039,"about_ca_topic_score_gemma":0.000021665264,"teacher_disagreement_score":0.03945344,"about_ca_system_score_codex":0.000084988795,"about_ca_system_score_gemma":0.00018936417,"threshold_uncertainty_score":0.9998838},"labels":[],"label_agreement":null},{"id":"W3202982215","doi":"10.1007/978-1-0716-1740-3_1","title":"Quantitative Genetic Screens for Mapping Bacterial Pathways and Functional Networks","year":2021,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina; University of Saskatchewan","funders":"Canadian Institutes of Health Research","keywords":"Mutant; Pairwise comparison; Biology; Computational biology; Gene; Genetics; Genetic screen; Genetic Fitness; Strain (injury); Replica; Gene mapping; Computer science; Artificial intelligence; Chromosome; Geography","score_opus":0.03730979353986242,"score_gpt":0.3380916449980746,"score_spread":0.3007818514582122,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3202982215","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22763288,0.004723005,0.7671133,0.00006706907,0.0002354108,0.00014699831,0.000011636421,0.0000067849123,0.00006288763],"genre_scores_gemma":[0.072136894,0.00026746438,0.92639875,0.000333856,0.00025743616,0.00008379718,0.00041876893,0.000033923803,0.000069115864],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.997634,0.0009426715,0.00033382155,0.0006732634,0.00004895687,0.00036726616],"domain_scores_gemma":[0.9992251,0.00011608557,0.00010054019,0.00033920148,0.00014190548,0.00007716332],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070085353,0.00020632756,0.0003249266,0.00008976468,0.00007679312,0.000020014282,0.00010090389,0.00032509465,0.000025729307],"category_scores_gemma":[0.0003745168,0.00021987438,0.00016549075,0.00022039759,0.00014502708,0.0000018717881,0.00019147963,0.000105879066,6.7693026e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008732337,0.000025962003,0.0038099233,0.000010941734,0.00016441163,0.000010522239,0.000014104677,0.0033578954,0.981674,0.0016121417,0.00007192148,0.009160815],"study_design_scores_gemma":[0.003749713,0.0011272199,0.035074983,0.00004676719,0.0002526181,0.00020235912,0.00034591786,0.048206158,0.85422444,0.013621042,0.0417569,0.0013918827],"about_ca_topic_score_codex":0.0000048201487,"about_ca_topic_score_gemma":0.00003364649,"teacher_disagreement_score":0.15928543,"about_ca_system_score_codex":0.000015990348,"about_ca_system_score_gemma":0.00009017597,"threshold_uncertainty_score":0.89662164},"labels":[],"label_agreement":null},{"id":"W3203248540","doi":"10.1007/978-1-0716-1740-3_14","title":"Chemical–Genetic Interactions as a Means to Characterize Drug Synergy","year":2021,"lang":"en","type":"review","venue":"Methods in molecular biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia Hospital; University of British Columbia","funders":"","keywords":"Leverage (statistics); Mechanism (biology); Computational biology; Computer science; Genomics; Genome; Data science; Biology; Genetics; Gene; Artificial intelligence; Epistemology","score_opus":0.02756061491471542,"score_gpt":0.4003648136021292,"score_spread":0.3728041986874138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3203248540","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00030155145,0.829444,0.16880472,0.00007147091,0.00049608137,0.00050365645,0.00003674822,0.000021826228,0.00031996658],"genre_scores_gemma":[0.000010917482,0.6985844,0.29820827,0.00044433805,0.00031698565,0.00049053074,0.0010049347,0.00013654193,0.0008031337],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9924789,0.0036971755,0.0011678794,0.0017453402,0.00013949796,0.0007711889],"domain_scores_gemma":[0.9973215,0.00015460391,0.00039692695,0.0016910078,0.00014363271,0.00029236765],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00087131845,0.0008354397,0.0023919563,0.0004948465,0.000057596233,0.000043476106,0.0009392157,0.0008609106,0.00016607376],"category_scores_gemma":[0.0008122805,0.00081987976,0.0013273705,0.0010622705,0.00013600738,0.0000022177926,0.0009351512,0.00056967273,0.0000624455],"study_design_candidate":"not_applicable","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":[0.000009564176,0.000092647715,0.0000063770494,0.0004605456,0.0008006234,0.000084219624,0.00002099375,0.000045412315,0.2486462,0.00016090438,0.00033252567,0.74934],"study_design_scores_gemma":[0.00013405741,0.000059281047,0.0000014274111,0.00089062564,0.00060204574,0.00021841502,0.0000130197,0.000012105219,0.021610526,0.00010486304,0.9755831,0.00077058194],"about_ca_topic_score_codex":0.000051243565,"about_ca_topic_score_gemma":0.000046601173,"teacher_disagreement_score":0.97525054,"about_ca_system_score_codex":0.00013675856,"about_ca_system_score_gemma":0.00043064862,"threshold_uncertainty_score":0.99942523},"labels":[],"label_agreement":null},{"id":"W3206734141","doi":"10.1103/physreve.104.044406","title":"Inferring gene regulation dynamics from static snapshots of gene expression variability","year":2021,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Harvard Medical School","keywords":"Computational biology; Biology; Gene; Regulation of gene expression; Population; Gene regulatory network; Gene expression; Dynamics (music); Systems biology; Genetics; Physics","score_opus":0.020366529835341575,"score_gpt":0.1709769529913736,"score_spread":0.15061042315603204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3206734141","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":[0.8258724,0.00006783747,0.17367794,0.00000865303,0.00005376506,0.00005180008,0.000031527496,0.000009148502,0.00022692834],"genre_scores_gemma":[0.99587107,0.00007154539,0.0029350878,0.000018414285,0.000060256312,3.107345e-7,0.0006897866,0.000014148329,0.00033938617],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988755,0.00018751647,0.00018753312,0.0005200128,0.00006516522,0.00016425965],"domain_scores_gemma":[0.998849,0.000030017249,0.00014668019,0.00069909054,0.0001918321,0.00008341332],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014986384,0.00013396784,0.00018814515,0.00004476351,0.000066564855,0.000008947906,0.00016729353,0.00014848851,0.0001038178],"category_scores_gemma":[0.000060152233,0.00016139721,0.00013667837,0.00029518898,0.00006532043,0.000010081292,0.00016020457,0.000060604936,0.0000033008819],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047675097,0.000068645226,0.058412265,0.000012611145,0.00010754533,0.000015387765,0.000022023294,0.19850296,0.7422174,0.00038641584,0.000039015304,0.00016801625],"study_design_scores_gemma":[0.0004994737,0.000034989946,0.030934166,0.000016926459,0.00015514193,0.0000023398363,0.000090929345,0.12805122,0.8370345,0.002847325,0.00011097941,0.00022199671],"about_ca_topic_score_codex":0.00004025763,"about_ca_topic_score_gemma":0.00010560471,"teacher_disagreement_score":0.17074285,"about_ca_system_score_codex":0.00006649139,"about_ca_system_score_gemma":0.000096397656,"threshold_uncertainty_score":0.6581587},"labels":[],"label_agreement":null},{"id":"W3208891486","doi":"10.6000/1929-6029.2021.10.12","title":"Cancer Growth Inhibition Using Predictive Mathematical Models of Signaling Pathways","year":2021,"lang":"en","type":"article","venue":"International Journal of Statistics in Medical Research","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Multicellular organism; Signalling; Process (computing); Rivalry; Mechanism (biology); Signalling pathways; Identification (biology); Cancer cell; Computer science; Ordinary differential equation; Cell division; Cancer; Biology; Neuroscience; Signal transduction; Computational biology; Cell; Differential equation; Cell biology; Economics; Ecology; Mathematics","score_opus":0.06430780700632911,"score_gpt":0.39885860791307093,"score_spread":0.33455080090674183,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3208891486","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":[0.62106526,0.00067072234,0.37766242,0.00021415674,0.00012275869,0.000034401608,0.000072656345,6.6027485e-7,0.00015699021],"genre_scores_gemma":[0.983793,0.0012949432,0.01439782,0.00004097639,0.00041128873,0.0000026921468,0.000028602239,0.000011447271,0.000019180909],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9966097,0.00029768058,0.0006053497,0.00014837136,0.0021564984,0.00018238557],"domain_scores_gemma":[0.99601793,0.00026220919,0.00018633665,0.000090683825,0.003300142,0.00014271263],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019458929,0.00007157318,0.00019819752,0.00021117988,0.000025656967,0.000019050334,0.00026869753,0.00012659193,0.0002589821],"category_scores_gemma":[0.002737431,0.00006623105,0.000074808675,0.00020473002,0.00020544819,0.000009495575,0.0001836361,0.0003747102,6.619667e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009543822,0.001332274,0.007710633,0.00024698375,0.0016941733,0.0032365595,0.00089645793,0.10757571,0.8052792,0.04794523,0.002973797,0.02015461],"study_design_scores_gemma":[0.0021810085,0.00039791534,0.0009229819,0.0016328198,0.000081158716,0.0004623498,0.0009306449,0.37410364,0.38417587,0.23471385,0.00016487011,0.00023289748],"about_ca_topic_score_codex":0.000021783353,"about_ca_topic_score_gemma":0.000026938103,"teacher_disagreement_score":0.42110333,"about_ca_system_score_codex":0.000116433206,"about_ca_system_score_gemma":0.0011552237,"threshold_uncertainty_score":0.32771584},"labels":[],"label_agreement":null},{"id":"W3209507722","doi":"10.1016/j.mbs.2021.108720","title":"Uniqueness of weakly reversible and deficiency zero realizations of dynamical systems.","year":2021,"lang":"en","type":"article","venue":"PubMed","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"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; Simons Foundation; National Science Foundation","keywords":"Uniqueness; Multistability; Mathematics; Dynamical systems theory; Zero (linguistics); Action (physics); Realization (probability); Dynamical system (definition); Invariant (physics); Statistical physics; Mathematical analysis; Physics; Nonlinear system; Mathematical physics; Quantum mechanics","score_opus":0.009336690136555633,"score_gpt":0.20457129002738478,"score_spread":0.19523459989082914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3209507722","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":[0.9898354,0.0038137892,0.0050738,0.000040941217,0.000051120736,0.00012032874,0.00001785073,0.0000036601118,0.0010431246],"genre_scores_gemma":[0.9987092,0.00031984493,0.0001781749,0.000008708664,0.000015319954,0.000036595466,0.00006381171,0.0000069741413,0.0006613714],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99937934,0.000069745714,0.00017998258,0.0001687159,0.00008253426,0.00011967095],"domain_scores_gemma":[0.99945134,0.0000079849315,0.00008404863,0.000247945,0.00015798015,0.000050707415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001503053,0.000057137007,0.00013933583,0.000033549954,0.00002238702,0.0000050823696,0.00006243294,0.000079281046,0.0000018799806],"category_scores_gemma":[0.00006609254,0.0000585216,0.000049842296,0.00021340004,0.00006633433,0.0000016325959,0.00007200847,0.000020027428,1.0254096e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000097250755,0.00052580296,0.24470522,0.0011646275,0.00075692165,0.000014919465,0.00010835289,0.027460035,0.6851104,0.016616369,0.004313699,0.019126438],"study_design_scores_gemma":[0.000898045,0.00008440776,0.44284955,0.000057633126,0.00048627623,0.0000745878,0.000330172,0.0028228303,0.54147905,0.00053910713,0.0098774005,0.0005009704],"about_ca_topic_score_codex":0.000024713543,"about_ca_topic_score_gemma":0.000023947161,"teacher_disagreement_score":0.19814433,"about_ca_system_score_codex":0.000007800551,"about_ca_system_score_gemma":0.000048215803,"threshold_uncertainty_score":0.23864415},"labels":[],"label_agreement":null},{"id":"W3209522025","doi":"10.32920/ryerson.14653782.v1","title":"Numerical studies of higher order tau-leaping methods","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Scheme (mathematics); Order (exchange); Algorithm; Stochastic simulation; Basis (linear algebra); Mathematical optimization; Applied mathematics; Mathematics; Statistics","score_opus":0.04219549741962515,"score_gpt":0.38099242242496445,"score_spread":0.3387969250053393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3209522025","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":[0.50118756,0.19374935,0.29410404,0.0009633166,0.0025623655,0.0005076287,0.000011282935,0.000072308,0.006842108],"genre_scores_gemma":[0.74644434,0.0023360546,0.24327582,0.0002914018,0.0005502387,0.000041388394,0.00020446442,0.0000562334,0.0068000704],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9981066,0.00036457815,0.00043987815,0.0006874527,0.0001690468,0.00023244777],"domain_scores_gemma":[0.99825674,0.00003021244,0.0002366055,0.0009029131,0.000507205,0.000066299566],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00037032072,0.00029506072,0.00069006695,0.00005617571,0.000038519283,0.000019407473,0.00028525657,0.0004193256,0.00023038175],"category_scores_gemma":[0.00013283083,0.00026361903,0.00041367544,0.00020241752,0.00012455018,9.196809e-7,0.0012861764,0.00020174007,0.0000022743216],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000077266086,0.00035902506,0.0053721787,0.0013156502,0.018508112,0.000022940983,0.0003865437,0.10612114,0.8027541,0.00025619642,0.030271947,0.03455491],"study_design_scores_gemma":[0.00048782318,0.000148231,0.0028607931,0.00020795118,0.0011889344,0.000010514303,0.00093017373,0.0019147304,0.93821776,0.0005898326,0.052162528,0.0012807089],"about_ca_topic_score_codex":0.000029490599,"about_ca_topic_score_gemma":0.0000119663455,"teacher_disagreement_score":0.24525675,"about_ca_system_score_codex":0.000021677244,"about_ca_system_score_gemma":0.00015896169,"threshold_uncertainty_score":0.9999816},"labels":[],"label_agreement":null},{"id":"W3210669402","doi":"10.1007/s11424-021-1271-1","title":"Biological Systems: Reliable Functions out of Randomness","year":2021,"lang":"en","type":"article","venue":"Journal of Systems Science and Complexity","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Randomness; Computer science; Statistical physics; Mathematics; Physics; Statistics","score_opus":0.0516302327458224,"score_gpt":0.2709079932763991,"score_spread":0.21927776053057668,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3210669402","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":[0.98749423,0.007441856,0.0035645396,0.00005797645,0.00082387537,0.0000633915,0.0000056801405,0.0000020690848,0.00054636766],"genre_scores_gemma":[0.99901456,0.00022587761,0.00015327323,0.000015769449,0.00025603015,0.0000017792141,0.000002585151,0.0000032019486,0.0003269217],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987271,0.000110398316,0.00045315656,0.00019059346,0.00035629107,0.00016248344],"domain_scores_gemma":[0.99799424,0.000016491264,0.00036968023,0.00023098031,0.0012726474,0.00011597267],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015559305,0.0000829794,0.00033221272,0.00007258347,0.00015622705,0.000057625144,0.00020726562,0.00006462057,0.0000052890773],"category_scores_gemma":[0.00015733804,0.000060261005,0.00010052896,0.0003205894,0.00048945064,0.000012006482,0.00009979444,0.000066914756,0.0000012524984],"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":[0.00012541177,0.00012142036,0.022860464,0.000098748664,0.00017229059,0.000016097249,0.00006714082,0.0038531965,0.9679534,0.0014114497,0.0031035482,0.00021684985],"study_design_scores_gemma":[0.016876154,0.0059385463,0.15351379,0.0020937345,0.0013578436,0.0102608185,0.03454669,0.029758599,0.34868377,0.0019558943,0.3922232,0.0027909314],"about_ca_topic_score_codex":0.000020825579,"about_ca_topic_score_gemma":0.000007610067,"teacher_disagreement_score":0.6192696,"about_ca_system_score_codex":0.000022160411,"about_ca_system_score_gemma":0.0003545567,"threshold_uncertainty_score":0.24573725},"labels":[],"label_agreement":null},{"id":"W3210782469","doi":"10.1007/s10884-021-10097-z","title":"Carryover of a Saddle-Node Bifurcation After Transforming a Parameter into a Variable","year":2021,"lang":"en","type":"article","venue":"Journal of Dynamics and Differential Equations","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Athabasca University; University of Alberta","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Athabasca University","keywords":"Saddle-node bifurcation; Bifurcation diagram; Bifurcation; Mathematics; Variable (mathematics); Ordinary differential equation; Singularity theory; Node (physics); Bifurcation theory; Mathematical analysis; Singularity; Applied mathematics; Control theory (sociology); Differential equation; Nonlinear system; Computer science; Physics","score_opus":0.005506410777742386,"score_gpt":0.2236839728931201,"score_spread":0.2181775621153777,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3210782469","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":[0.6179875,0.0007461729,0.38107744,0.00006446643,0.00006002114,0.000024689583,0.000009578349,6.2726576e-7,0.00002948058],"genre_scores_gemma":[0.99509376,0.00016999168,0.004393702,0.000029850955,0.00009663237,0.000003174625,0.000058346544,0.0000091657685,0.00014540149],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992766,0.0000467378,0.00034036385,0.00010922263,0.00013439289,0.0000926937],"domain_scores_gemma":[0.9993322,0.000024974206,0.00018326155,0.00013312591,0.00026596338,0.000060506598],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009208845,0.000083378945,0.00017877425,0.00007170687,0.000041758394,0.000024774234,0.000055317094,0.00008454196,0.000037265276],"category_scores_gemma":[0.00006998031,0.00007541615,0.00014901554,0.00012561001,0.00003363367,0.00000851019,0.000029778219,0.00006495754,1.8231444e-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":[0.00034643215,0.0005385372,0.017336164,0.00017398839,0.0014656696,0.000012088324,0.0007191083,0.0103791235,0.94448787,0.0051844907,0.000077154305,0.019279396],"study_design_scores_gemma":[0.0060161324,0.0011587808,0.045252994,0.0004322841,0.003783426,0.00026685977,0.00122079,0.8113462,0.11348654,0.013843146,0.0020309347,0.0011619509],"about_ca_topic_score_codex":0.000012419486,"about_ca_topic_score_gemma":0.00016422926,"teacher_disagreement_score":0.8310013,"about_ca_system_score_codex":0.000018726716,"about_ca_system_score_gemma":0.00012579477,"threshold_uncertainty_score":0.30753812},"labels":[],"label_agreement":null},{"id":"W3211922492","doi":"10.1371/journal.pdig.0000072","title":"A parsimonious model of blood glucose homeostasis","year":2022,"lang":"en","type":"article","venue":"PLOS Digital Health","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"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 Tech University","funders":"Mitacs; University of Ontario Institute of Technology","keywords":"Glucose homeostasis; Data assimilation; Computer science; Homeostasis; Diabetes mellitus; Biological system; Applied mathematics; Mathematics; Biology; Physics; Endocrinology; Insulin resistance","score_opus":0.016896252622120855,"score_gpt":0.23732918213985338,"score_spread":0.22043292951773252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3211922492","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":[0.99178284,0.0068924376,0.00020931894,0.0002144342,0.00002255036,0.00015023488,0.00032497407,0.000015201617,0.00038799774],"genre_scores_gemma":[0.9984755,0.0003282067,0.00023590786,0.00030445532,0.000042030846,0.000029985611,0.00028477877,0.000026347563,0.00027279914],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988243,0.000046247267,0.0002828637,0.00029801266,0.00026036115,0.0002882144],"domain_scores_gemma":[0.99924684,0.0000068266804,0.0001614353,0.0004059579,0.00004433633,0.00013462776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000113942806,0.00012121996,0.00022529594,0.000059511116,0.0001307781,0.0000138107,0.00021001948,0.000034879482,0.00001578985],"category_scores_gemma":[0.000016807859,0.00013286405,0.00014346497,0.0001898887,0.00004162766,0.000003891853,0.00026604038,0.00007740155,0.0000024808537],"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":[0.001082079,0.012793016,0.028669983,0.0011254621,0.004910537,0.00003805635,0.0015004791,0.45006517,0.29609433,0.0009717633,0.036980223,0.1657689],"study_design_scores_gemma":[0.008870487,0.0148118595,0.0016808232,0.00012406304,0.001143013,0.00021192213,0.002744985,0.1658407,0.7400924,0.0054231165,0.055512246,0.0035443862],"about_ca_topic_score_codex":0.000012114537,"about_ca_topic_score_gemma":0.0000113410115,"teacher_disagreement_score":0.44399807,"about_ca_system_score_codex":0.000028535176,"about_ca_system_score_gemma":0.0002801436,"threshold_uncertainty_score":0.54180384},"labels":[],"label_agreement":null},{"id":"W3214516348","doi":"10.3934/jcd.2021024","title":"A mathematical analysis of an activator-inhibitor Rho GTPase model","year":2021,"lang":"en","type":"article","venue":"Journal of Computational Dynamics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"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 Manitoba","funders":"University of Johannesburg; University of Sussex; European Commission; Engineering and Physical Sciences Research Council; National Institute for Health and Care Research; Leverhulme Trust; Wolfson Foundation","keywords":"Bistability; Bifurcation; Activator (genetics); Positive feedback; Negative feedback; Biological system; Bifurcation theory; Computer science; GTPase; Control theory (sociology); Statistical physics; Physics; Mathematics; Chemistry; Biology; Artificial intelligence; Cell biology; Nonlinear system; Gene; Engineering","score_opus":0.0075559788652653035,"score_gpt":0.25871042123357807,"score_spread":0.25115444236831275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3214516348","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":[0.67276305,0.00007264473,0.32697746,0.00006380993,0.000024812674,0.00001554118,0.00002399377,0.0000013650056,0.00005728977],"genre_scores_gemma":[0.9528748,0.000011131994,0.046624355,0.00006664825,0.0001075876,5.5256885e-7,0.00023152694,0.000012748943,0.00007065775],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99873364,0.000085475804,0.0005384169,0.00015173027,0.00037995237,0.00011077016],"domain_scores_gemma":[0.9984371,0.00003774457,0.00041342847,0.00019942973,0.0007930231,0.00011926954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002447557,0.0001097593,0.00036191236,0.000188223,0.000034647393,0.000019047795,0.00014712586,0.00009435313,0.00002410359],"category_scores_gemma":[0.00007210043,0.00010531264,0.0004505154,0.00046134583,0.000040064824,0.000010362942,0.00005201847,0.00008834258,5.828942e-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":[0.00005297136,0.00022616527,0.0005687963,0.00001199669,0.0016804596,0.000013117749,0.000023357341,0.983542,0.011588644,0.0016757285,0.000059966533,0.00055677403],"study_design_scores_gemma":[0.0002954069,0.00009149803,0.0018644204,0.000010511469,0.0009112642,0.000061116734,0.00006152056,0.9852758,0.0036981571,0.007609885,0.000020331114,0.00010007698],"about_ca_topic_score_codex":4.366756e-7,"about_ca_topic_score_gemma":0.0000151002605,"teacher_disagreement_score":0.28035313,"about_ca_system_score_codex":0.00004034812,"about_ca_system_score_gemma":0.00033618015,"threshold_uncertainty_score":0.42945248},"labels":[],"label_agreement":null},{"id":"W3216319821","doi":"10.1002/rnc.5887","title":"AutoRepar: A method to obtain identifiable and observable reparameterizations of dynamic models with mechanistic insights","year":2021,"lang":"en","type":"article","venue":"International Journal of Robust and Nonlinear Control","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"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":"European Social Fund; Agencia Estatal de Investigación; Consejo Superior de Investigaciones Científicas; Banff International Research Station for Mathematical Innovation and Discovery; Xunta de Galicia; European Regional Development Fund; Consellería de Cultura, Educación e Ordenación Universitaria, Xunta de Galicia","keywords":"Observable; Identifiability; Observability; Computer science; Ode; Parameterized complexity; Nonlinear system; Interpretation (philosophy); State variable; Algorithm; Mathematics; Applied mathematics; Machine learning","score_opus":0.008972713847886466,"score_gpt":0.2562203971531281,"score_spread":0.24724768330524163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3216319821","genre_codex":"methods","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":[0.43988067,0.0013230026,0.5584292,0.00018799338,0.00006860096,0.00006406501,0.000019954405,0.0000018353271,0.000024665516],"genre_scores_gemma":[0.86151564,0.00020720049,0.13771269,0.0001381485,0.00008703426,0.0000029883784,0.00002500238,0.000011216132,0.00030006634],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913734,0.0000883196,0.0003169136,0.00016864503,0.00020421762,0.000084572755],"domain_scores_gemma":[0.9986972,0.000037448943,0.00022369646,0.00012358629,0.00083425984,0.00008376219],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002328056,0.00009255207,0.00024720907,0.00009185521,0.000032329946,0.000042776457,0.00012089747,0.0000531883,0.0000058642345],"category_scores_gemma":[0.00009139695,0.00007658016,0.00007306461,0.000096110016,0.000026020716,0.0000148328045,0.000055956545,0.000052228315,1.6646416e-7],"study_design_candidate":"simulation_or_modeling","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":[0.0006748881,0.00015535319,0.00067903596,0.00009442007,0.0021447837,0.00009722628,0.00013996067,0.32845652,0.6654831,0.0007492454,0.00008436944,0.0012410795],"study_design_scores_gemma":[0.0029587026,0.00063793926,0.00064611493,0.00039096657,0.00073934835,0.00073245825,0.00023294098,0.9451614,0.045012828,0.0016220015,0.0015689253,0.0002963689],"about_ca_topic_score_codex":0.0000068258687,"about_ca_topic_score_gemma":0.00005312565,"teacher_disagreement_score":0.6204703,"about_ca_system_score_codex":0.000014245036,"about_ca_system_score_gemma":0.0001299943,"threshold_uncertainty_score":0.31228483},"labels":[],"label_agreement":null},{"id":"W33581941","doi":"10.1007/978-3-319-08927-0_11","title":"Analytic Considerations and Axiomatic Approaches to the Concept Cell Death and Cell Survival Functions in Biology and Cancer Treatment","year":2014,"lang":"en","type":"article","venue":"Advances in experimental medicine and biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Axiom; Axiomatic system; Connection (principal bundle); Set (abstract data type); Process (computing); Biological cell; Theoretical computer science; Mathematical economics; Computer science; Mathematics; Management science; Biology; Biological system","score_opus":0.045640981826697964,"score_gpt":0.32370345539748296,"score_spread":0.278062473570785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W33581941","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":[0.91678935,0.08157428,0.00026083543,0.0007974043,0.000077868965,0.00019101749,0.000006101837,0.0000027169267,0.00030044853],"genre_scores_gemma":[0.9948583,0.0043327417,0.0002305414,0.00027898987,0.0001210495,0.00008372279,0.000034775967,0.000006141175,0.000053727133],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99911404,0.00014907126,0.00018506269,0.0003615277,0.000022290773,0.0001680317],"domain_scores_gemma":[0.9996532,0.000094617724,0.00004749153,0.00012706502,0.000008290338,0.00006929657],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000121465564,0.00014905077,0.0002587394,0.00006959434,0.00008232493,0.000005736236,0.000033525168,0.00007750128,0.000009514431],"category_scores_gemma":[0.000019260888,0.00009410344,0.000014079586,0.000073805786,0.0003833974,0.000005385438,0.00006559157,0.000040741357,2.3109098e-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":[0.00011740184,0.00023145432,0.530246,0.000037418453,0.0001165935,0.0000026740734,0.0031496466,0.00070435123,0.44100547,0.0037930317,0.00009993282,0.020496015],"study_design_scores_gemma":[0.03187747,0.031337276,0.15229835,0.00029988177,0.0010965049,0.0003080666,0.0619944,0.021695338,0.51109797,0.011744514,0.17274447,0.0035057557],"about_ca_topic_score_codex":0.00022220818,"about_ca_topic_score_gemma":0.0012681687,"teacher_disagreement_score":0.37794766,"about_ca_system_score_codex":0.00001624553,"about_ca_system_score_gemma":0.000013504882,"threshold_uncertainty_score":0.3837427},"labels":[],"label_agreement":null},{"id":"W36478636","doi":"10.1002/cphc.202200731","title":"A Matrix Based Approach For Modeling Robotic Swarm Behavior.","year":2006,"lang":"en","type":"article","venue":"International Conference on Artificial Intelligence","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"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":"Swarm behaviour; Computer science; Matrix (chemical analysis); Artificial intelligence","score_opus":0.07657845565800311,"score_gpt":0.33389200321859475,"score_spread":0.25731354756059166,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W36478636","genre_codex":"methods","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":[0.09689573,0.00005027964,0.90039176,0.0002215771,0.00023149585,0.00026837987,0.000020059431,0.000022950459,0.0018977837],"genre_scores_gemma":[0.984829,0.000009958138,0.013375478,0.00009321735,0.00049670634,0.00015808805,0.00047691114,0.00002392681,0.00053672265],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985767,0.000034646735,0.00038130305,0.00049585657,0.0002658937,0.0002455763],"domain_scores_gemma":[0.9991649,0.000014152117,0.00010137078,0.00028631638,0.00037536983,0.000057924175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000191318,0.00018982371,0.00015138587,0.00011407546,0.00009558046,0.00009647978,0.00041171713,0.00012645454,0.00007559266],"category_scores_gemma":[0.000042478707,0.00019685212,0.00018944996,0.000100863814,0.000064886786,0.000006103943,0.000046564568,0.00008542163,0.000025692927],"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":[0.00012048649,0.00023655414,0.0001409399,0.0000053880335,0.00003323831,0.0000012875958,0.000005926555,0.8938645,0.066827156,0.035820883,0.00011213994,0.002831509],"study_design_scores_gemma":[0.000046399407,0.00009484772,0.000018253508,0.000009262215,0.000034554145,0.000002243353,0.00005113145,0.88813835,0.1069256,0.0042842655,0.00019296445,0.00020213204],"about_ca_topic_score_codex":0.000059853755,"about_ca_topic_score_gemma":0.00007261434,"teacher_disagreement_score":0.88793325,"about_ca_system_score_codex":0.00003982678,"about_ca_system_score_gemma":0.00009333386,"threshold_uncertainty_score":0.8027397},"labels":[],"label_agreement":null},{"id":"W4200596465","doi":"10.1101/2021.12.28.474323","title":"A versatile active learning workflow for optimization of genetic and metabolic networks","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Max-Planck-Gesellschaft; Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement; Agence Nationale de la Recherche; Bundesministerium für Bildung und Forschung; University of Bristol; Gordon and Betty Moore Foundation","keywords":"Workflow; Computer science; Modular design; Distributed computing; Synthetic biology; Systems biology; Bioinformatics; Biology; Operating system; Database","score_opus":0.006901175422245043,"score_gpt":0.2036809716992228,"score_spread":0.19677979627697775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200596465","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":[0.76558447,0.013896645,0.21967216,0.000020340403,0.0002603205,0.0004934615,0.000037556754,0.00003338414,0.0000016441558],"genre_scores_gemma":[0.950815,0.003267154,0.04512686,0.000034335902,0.0004676799,0.00016558466,0.00000779089,0.00010928734,0.0000062939353],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99792975,0.00018027448,0.0004334924,0.0009058895,0.00017512709,0.00037545452],"domain_scores_gemma":[0.9979816,0.000031635307,0.0004989929,0.0007469618,0.0005866361,0.00015416718],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00028021375,0.0004050846,0.0005973701,0.00013053491,0.000120631055,0.00008630841,0.0002467397,0.00061463506,0.000014384976],"category_scores_gemma":[0.00017665944,0.00048154063,0.0002571058,0.00030725735,0.00010852495,0.0000074962886,0.00044481762,0.0002842379,3.4208298e-7],"study_design_candidate":"simulation_or_modeling","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":[0.00006869705,0.000050653907,0.0064842366,0.00014542424,0.0007919287,0.0000028465474,0.000008135575,0.76053804,0.2318124,0.0000098642795,0.00004669623,0.000041079096],"study_design_scores_gemma":[0.0015240641,0.00021959252,0.07338332,0.0003523225,0.0017137745,6.2918126e-8,0.000026096874,0.33824828,0.5798644,0.0000010528898,0.003208466,0.0014585974],"about_ca_topic_score_codex":0.000011497043,"about_ca_topic_score_gemma":0.000003423005,"teacher_disagreement_score":0.42228976,"about_ca_system_score_codex":0.000034067016,"about_ca_system_score_gemma":0.00030586237,"threshold_uncertainty_score":0.9997636},"labels":[],"label_agreement":null},{"id":"W4206190331","doi":"10.3934/math.2022313","title":"Biochemical Problems, Mathematical Solutions","year":2022,"lang":"en","type":"article","venue":"AIMS Mathematics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Lethbridge","funders":"","keywords":"Computer science; Biochemical engineering; Management science; Engineering","score_opus":0.016722049535727198,"score_gpt":0.23131546948130177,"score_spread":0.21459341994557457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206190331","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":[0.92962813,0.002100447,0.057634268,0.0007786062,0.0001841175,0.0006482484,0.00005676027,0.00012079986,0.0088486355],"genre_scores_gemma":[0.9824732,0.000031212476,0.013959086,0.00018207791,0.00016519098,0.0001929117,0.00015793793,0.000053455962,0.0027849053],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.998615,0.00006201461,0.00033531603,0.00030728878,0.00032109162,0.00035923734],"domain_scores_gemma":[0.99907297,0.000021906782,0.00011713557,0.00063791923,0.000048141428,0.000101920894],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040525125,0.00017060933,0.00020891584,0.00005530738,0.00031902205,0.000020347785,0.00034742622,0.00007663203,0.0005258189],"category_scores_gemma":[0.00006364818,0.00017156744,0.00018756159,0.00022896088,0.00008833043,0.0000020897235,0.00057300064,0.00014367866,0.00007651942],"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":[0.000025645517,0.0021099008,0.000393145,0.0003402834,0.00073437963,0.0000136141925,0.0008595415,0.012829372,0.77101547,0.03849028,0.17228216,0.00090621127],"study_design_scores_gemma":[0.0032459006,0.0016164522,0.00029579818,0.00011670244,0.0013040687,0.0016595438,0.004617416,0.09645513,0.1558219,0.18529926,0.54585236,0.0037154842],"about_ca_topic_score_codex":0.0000011305381,"about_ca_topic_score_gemma":0.0000014450461,"teacher_disagreement_score":0.61519355,"about_ca_system_score_codex":0.000036598834,"about_ca_system_score_gemma":0.00006281128,"threshold_uncertainty_score":0.69963175},"labels":[],"label_agreement":null},{"id":"W4210526703","doi":"10.1109/cdc45484.2021.9683536","title":"Global analysis of networks of piecewise affine bistable switches","year":2021,"lang":"en","type":"article","venue":"2021 60th IEEE Conference on Decision and Control (CDC)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Toronto","funders":"","keywords":"Bistability; Topology (electrical circuits); Interconnection; Set (abstract data type); Piecewise; Affine transformation; Differential equation; Computer science; Piecewise linear function; Control theory (sociology); Network topology; Applied mathematics; Mathematics; Physics; Mathematical analysis; Pure mathematics; Telecommunications; Control (management); Combinatorics","score_opus":0.011487873319094077,"score_gpt":0.2543111249114276,"score_spread":0.24282325159233353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210526703","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":[0.9146603,0.004624912,0.07904356,0.00013841722,0.00014849941,0.00010856531,0.00009799794,0.0000054077677,0.0011723669],"genre_scores_gemma":[0.9974274,0.0014049951,0.00030594613,0.00014249016,0.0000857767,0.0000076190518,0.00008384865,0.0000105529325,0.0005313604],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982361,0.00011132171,0.0005312176,0.00055591523,0.00030274934,0.00026264935],"domain_scores_gemma":[0.9982355,0.00006633607,0.00026222758,0.0007213476,0.00056437,0.00015019129],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028745568,0.00022786767,0.0007476126,0.00010325323,0.000055641798,0.000039044757,0.00021912134,0.00021116392,0.0003947109],"category_scores_gemma":[0.00011229536,0.00020625954,0.00037589963,0.0009899037,0.000108919376,0.0000053324898,0.00008563391,0.00007201228,0.0000024589817],"study_design_candidate":"simulation_or_modeling","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":[0.0023360779,0.00088749855,0.092687,0.000044536064,0.009334082,0.000049114984,0.000042437652,0.16838396,0.45771644,0.0018843263,0.0031101601,0.26352435],"study_design_scores_gemma":[0.011956302,0.001526294,0.3481355,0.00032166476,0.011972268,0.000030779058,0.00064679974,0.49687424,0.114090316,0.0016329777,0.011052568,0.0017602751],"about_ca_topic_score_codex":0.00002964456,"about_ca_topic_score_gemma":0.0005924281,"teacher_disagreement_score":0.34362614,"about_ca_system_score_codex":0.000013764943,"about_ca_system_score_gemma":0.00020097,"threshold_uncertainty_score":0.841102},"labels":[],"label_agreement":null},{"id":"W4211029243","doi":"10.1090/fic/036","title":"Dynamical Systems and Their Applications in Biology","year":2003,"lang":"en","type":"book","venue":"American Mathematical Society eBooks","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; McMaster University; Dalhousie University","funders":"","keywords":"Biology; Computer science","score_opus":0.006288808248049007,"score_gpt":0.23882577995198992,"score_spread":0.23253697170394091,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4211029243","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.041227993,0.009567966,0.17966728,0.0001803251,0.00015322134,0.003835519,0.00028086582,0.00015036849,0.76493645],"genre_scores_gemma":[0.24384981,0.0007729565,0.009556572,0.0010126103,0.0009233058,0.001212871,0.0012991586,0.00042487922,0.74094784],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984054,0.00010144318,0.00042441385,0.00061517616,0.00009598261,0.00035759102],"domain_scores_gemma":[0.9988997,0.00008409403,0.00023844118,0.0005867642,0.000046191406,0.00014482542],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022844243,0.00038661563,0.0007249294,0.000035962967,0.00007085247,0.000025909783,0.00022853822,0.0004345674,0.000008905622],"category_scores_gemma":[0.000015894653,0.00031709927,0.00035932675,0.000059711918,0.000980933,7.435068e-7,0.00015341645,0.00026679834,0.000009916718],"study_design_candidate":"theoretical_or_conceptual","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":[0.0001043096,0.0012981488,0.003733457,0.004286084,0.0120989075,0.000013386719,0.003238939,0.00046325364,0.06999206,0.71608835,0.13194913,0.056733992],"study_design_scores_gemma":[0.0011942192,0.00075190293,0.00010505046,0.000323803,0.00071689795,0.00011817066,0.002784895,0.008464921,0.0007724174,0.20853545,0.77292377,0.0033085314],"about_ca_topic_score_codex":0.0000067761684,"about_ca_topic_score_gemma":0.0000074897666,"teacher_disagreement_score":0.64097464,"about_ca_system_score_codex":0.00009005554,"about_ca_system_score_gemma":0.00017682668,"threshold_uncertainty_score":0.9999281},"labels":[],"label_agreement":null},{"id":"W4212895190","doi":"10.1007/s11432-020-3136-3","title":"Stabilization of Boolean control networks with state-triggered impulses","year":2022,"lang":"en","type":"article","venue":"Science China Information Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Boolean network; Set (abstract data type); Computer science; Quotient; Domain (mathematical analysis); State (computer science); State space; Boolean function; Hybrid system; Algorithm; Control (management); Topology (electrical circuits); Mathematics; Control theory (sociology); Artificial intelligence; Machine learning","score_opus":0.003765207309372975,"score_gpt":0.21774880985356423,"score_spread":0.21398360254419127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4212895190","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":[0.9154371,0.00008590831,0.08326654,0.000050013205,0.000100652476,0.00017403028,0.000011779227,0.000010323108,0.0008636525],"genre_scores_gemma":[0.9992457,0.000012144026,0.0005297224,0.00013299964,0.000017875542,0.000011800893,0.000023171297,0.0000026461876,0.000023909304],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983416,0.000047993657,0.00031395227,0.00020561277,0.00081333023,0.00027751375],"domain_scores_gemma":[0.99914527,0.0000116765905,0.000332224,0.00023034637,0.00020878804,0.00007166947],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023439312,0.00009224422,0.00011113374,0.00027319984,0.0007855638,0.00008102094,0.000557928,0.000018170622,0.00003590376],"category_scores_gemma":[0.00007115689,0.00007208754,0.000040351177,0.0020239546,0.0010311559,0.00010796025,0.00014752975,0.000055863566,0.000001011125],"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":[0.000051708877,0.000016750511,0.021477785,0.000004436048,0.000008845147,9.804046e-8,0.00031718757,0.9634366,0.00918669,0.00018211965,0.00008621413,0.005231544],"study_design_scores_gemma":[0.0021219077,0.0033561212,0.17288503,0.000019024179,0.00005852825,0.000049448707,0.007186297,0.698661,0.105629906,0.0003729267,0.0087879365,0.00087186357],"about_ca_topic_score_codex":0.000029719897,"about_ca_topic_score_gemma":0.000019761766,"teacher_disagreement_score":0.2647756,"about_ca_system_score_codex":0.000033732616,"about_ca_system_score_gemma":0.00042095577,"threshold_uncertainty_score":0.60420007},"labels":[],"label_agreement":null},{"id":"W4214690913","doi":"10.3410/f.1020672.237433","title":"Faculty Opinions recommendation of Regulation through the secondary channel--structural framework for ppGpp-DksA synergism during transcription.","year":2004,"lang":"en","type":"dataset","venue":"Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Clinical Research Institute","funders":"","keywords":"Transcription (linguistics); Channel (broadcasting); Computational biology; Biology; Chemistry; Computer science; Computer network; Linguistics","score_opus":0.019917808042313037,"score_gpt":0.32393971552745565,"score_spread":0.30402190748514263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4214690913","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000014006217,0.0028162901,0.0013021249,0.08661824,0.00094892853,0.0015089355,0.90676093,0.000018292238,0.000012257299],"genre_scores_gemma":[0.00033182898,0.0005687825,0.0020852792,0.001905989,0.0009460551,0.00035963597,0.99321556,0.000042556756,0.00054433953],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9960949,0.00038732268,0.0014546855,0.0007971056,0.0008687366,0.00039723836],"domain_scores_gemma":[0.99331397,0.000065422915,0.0015455759,0.0017152822,0.0032062093,0.00015354223],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007831645,0.0005653535,0.0007877394,0.00015542141,0.0004943782,0.000099569814,0.0014102081,0.0010801441,0.00020607011],"category_scores_gemma":[0.001900401,0.00035706421,0.0011271567,0.0011708285,0.0003986852,0.000056021658,0.00028574074,0.0007562241,0.0000055094665],"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":[0.000034431767,0.00008455421,0.0000010439124,0.00378957,0.00037697342,5.7968293e-8,0.00011498259,0.000025632624,0.000094908195,0.0004362517,0.9944915,0.0005500519],"study_design_scores_gemma":[0.00068237516,0.00011461001,0.000990761,0.0032257198,0.00038695804,0.0000318523,0.000042130378,0.000019378042,0.00054962817,0.0006407456,0.99295145,0.00036437187],"about_ca_topic_score_codex":0.000030298444,"about_ca_topic_score_gemma":0.000011681722,"teacher_disagreement_score":0.08645461,"about_ca_system_score_codex":0.00010329975,"about_ca_system_score_gemma":0.0004764331,"threshold_uncertainty_score":0.9998881},"labels":[],"label_agreement":null},{"id":"W4220787490","doi":"10.1101/2022.03.31.486579","title":"Fundamental trade-off between speed of switching and robustness of genetic switches limits dynamic control of metabolism","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"University of Toronto","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; Genome Canada","keywords":"Robustness (evolution); Predictability; Metabolic engineering; Synthetic biology; Computer science; Gene regulatory network; Modularity (biology); Phenotype; Systems biology; Computational biology; Biology; Gene; Genetics; Gene expression; Physics","score_opus":0.008995375342194507,"score_gpt":0.21654316474047183,"score_spread":0.20754778939827734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220787490","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":[0.9788375,0.015619264,0.0042371247,0.000037249578,0.0002574653,0.0005232452,0.00046602768,0.000020758755,0.000001345811],"genre_scores_gemma":[0.99661696,0.00094343245,0.0020526932,0.000013543083,0.00022330327,0.000032556974,0.0000039678835,0.00011152329,0.0000020408597],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9969442,0.0002453561,0.0010625307,0.00089928304,0.0004499799,0.00039864724],"domain_scores_gemma":[0.99710953,0.000044847315,0.0012740365,0.0011835921,0.00021020966,0.00017775422],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00060207344,0.0005351179,0.0012843354,0.00028670847,0.00008362616,0.000024284085,0.000617932,0.000474474,0.000020309393],"category_scores_gemma":[0.00007137055,0.00060447137,0.00039961058,0.0003534491,0.00021624545,0.00000771671,0.0005757866,0.000375599,2.4128656e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000066931665,0.00010378554,0.095040075,0.0004689466,0.0011010555,0.0000024288095,0.000009246619,0.011516853,0.89165384,0.000007407737,0.0000074273407,0.000022002616],"study_design_scores_gemma":[0.0010032726,0.00012667548,0.4748694,0.00011393957,0.0012042263,4.5149108e-8,0.000016555514,0.002733729,0.5191776,0.0000010267415,0.00023397114,0.0005195264],"about_ca_topic_score_codex":0.000033979144,"about_ca_topic_score_gemma":0.000004924994,"teacher_disagreement_score":0.37982932,"about_ca_system_score_codex":0.000056328376,"about_ca_system_score_gemma":0.00037628706,"threshold_uncertainty_score":0.99964064},"labels":[],"label_agreement":null},{"id":"W4220836239","doi":"10.18280/ria.360116","title":"Biological Network, Gene Regulatory Network Inference Using Causal Inference Approach","year":2022,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Inference; Gene regulatory network; Causal inference; Computer science; Granger causality; Artificial intelligence; Cluster analysis; Computational biology; Causality (physics); Machine learning; Data mining; Gene; Biology; Mathematics; Econometrics; Gene expression; Genetics","score_opus":0.05703095590954063,"score_gpt":0.28189520791514894,"score_spread":0.2248642520056083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220836239","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":[0.7408226,0.002941797,0.25400704,0.000044076944,0.0004987892,0.00036719412,0.000016136937,0.000060348295,0.0012419611],"genre_scores_gemma":[0.9898154,0.00022724422,0.00730507,0.00024792572,0.00112445,0.00009350299,0.00024333916,0.000048117552,0.0008949622],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99660885,0.000457788,0.0006783181,0.0010253992,0.0003201245,0.0009094912],"domain_scores_gemma":[0.99814945,0.00007863357,0.00029526144,0.00114013,0.00013363839,0.00020287042],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010780108,0.00037556989,0.00042666183,0.00007702847,0.00080114714,0.000055999208,0.000789432,0.00021701331,0.00037227076],"category_scores_gemma":[0.000110333596,0.00039784785,0.00028418427,0.00092448184,0.0002574892,0.000009933957,0.001032683,0.000399388,0.000034167024],"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":[0.000044080705,0.00011056048,0.008927812,0.000008988359,0.00008107307,0.000008832516,0.00006454089,0.9270602,0.059248973,0.000965519,0.0011104733,0.0023689612],"study_design_scores_gemma":[0.00014287519,0.00053555117,0.0015746041,0.00003292789,0.00012719641,0.00017579574,0.00057358074,0.9173013,0.05288233,0.001522781,0.023857893,0.001273141],"about_ca_topic_score_codex":0.000028269284,"about_ca_topic_score_gemma":0.000010110858,"teacher_disagreement_score":0.24899274,"about_ca_system_score_codex":0.000094511815,"about_ca_system_score_gemma":0.00017247323,"threshold_uncertainty_score":0.99984735},"labels":[],"label_agreement":null},{"id":"W4221027506","doi":"10.1007/s12080-022-00533-1","title":"Diverse perspectives from diverse scholars are vital for theoretical biology","year":2022,"lang":"en","type":"article","venue":"Theoretical Ecology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"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":"Université de Montréal; Fulbright Canada; University of Minnesota","keywords":"Perspective (graphical); Corollary; Diversity (politics); Epistemology; Identity (music); Process (computing); Computer science; Variety (cybernetics); Cognitive science; Data science; Management science; Sociology; Artificial intelligence; Psychology; Mathematics; Philosophy","score_opus":0.006506837004142996,"score_gpt":0.24537227609456663,"score_spread":0.23886543909042363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221027506","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":[0.99358493,0.00045201537,0.002717245,0.0009690145,0.00040476263,0.00035735365,0.0005025887,0.00003664157,0.00097546715],"genre_scores_gemma":[0.9971268,0.000042509848,0.00085497735,0.0007193112,0.00047767095,0.00017475353,0.00045061248,0.000041977342,0.00011138281],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99750966,0.00063487334,0.00027307007,0.0008443977,0.00014630216,0.0005916847],"domain_scores_gemma":[0.9987888,0.00022609832,0.00012437576,0.0005493691,0.00012344238,0.00018796884],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005132595,0.00026322296,0.00040717254,0.00009071319,0.00048265798,0.000019589765,0.00055802276,0.00027682405,0.005572821],"category_scores_gemma":[0.00045724263,0.0002589621,0.00036089701,0.00014716513,0.0022613737,0.000004292699,0.0010137905,0.0002998981,0.00003923455],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007293869,0.0002462241,0.010981479,0.0000041235858,0.0004664342,0.000014352476,0.00021240239,0.00032317857,0.043111924,0.9412981,0.0019425325,0.000669851],"study_design_scores_gemma":[0.0069401134,0.005540012,0.013625131,0.000007641614,0.001211831,0.00008927585,0.027810553,0.0036465141,0.02072884,0.8863386,0.032152865,0.0019086584],"about_ca_topic_score_codex":0.000005728162,"about_ca_topic_score_gemma":0.00002002277,"teacher_disagreement_score":0.054959547,"about_ca_system_score_codex":0.00009282441,"about_ca_system_score_gemma":0.00008536829,"threshold_uncertainty_score":0.99998623},"labels":[],"label_agreement":null},{"id":"W4221142374","doi":"10.1093/nar/gkac331","title":"BioSimulators: a central registry of simulation engines and services for recommending specific tools","year":2022,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Victoria","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of General Medical Sciences; National Institutes of Health","keywords":"Python (programming language); Computer science; SBML; Reuse; Software engineering; Software; Interface (matter); Systems engineering; Programming language; World Wide Web; XML; Operating system; Engineering","score_opus":0.04485659951256313,"score_gpt":0.33061839791150266,"score_spread":0.28576179839893956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221142374","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":[0.9972168,0.0012852421,0.0007715383,0.0001716417,0.000065648455,0.00029687458,0.000061951185,0.000008739458,0.00012156349],"genre_scores_gemma":[0.9983145,0.00015114035,0.0007981767,0.000023243292,0.00024038796,0.00004020228,0.00016119787,0.000026940574,0.0002441887],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985875,0.00016543448,0.00021633302,0.00035441524,0.00031247977,0.00036385687],"domain_scores_gemma":[0.9991785,0.00012149815,0.000074921314,0.0003967368,0.00014628968,0.000082031656],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074040133,0.00010290129,0.00015523007,0.00013514113,0.000306845,0.00004395161,0.00027533842,0.000079501486,0.000076834374],"category_scores_gemma":[0.00006708321,0.00011037786,0.0000910092,0.00030577322,0.00008243791,0.0000076202973,0.00035399458,0.0001350078,7.1380583e-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":[0.00071829336,0.00018514023,0.033535067,0.00034202443,0.00029266273,0.0000034245602,0.0004909381,0.1685419,0.758834,0.00033720618,0.0048201466,0.031899203],"study_design_scores_gemma":[0.0017864417,0.0010632031,0.012779821,0.000044391534,0.000051231695,0.000011736842,0.0026290205,0.13951357,0.087283365,0.00046563812,0.7538785,0.00049308635],"about_ca_topic_score_codex":0.000007912069,"about_ca_topic_score_gemma":0.0000040518216,"teacher_disagreement_score":0.74905837,"about_ca_system_score_codex":0.000044691064,"about_ca_system_score_gemma":0.000040309704,"threshold_uncertainty_score":0.45010784},"labels":[],"label_agreement":null},{"id":"W4224075414","doi":"10.1101/2022.04.12.488093","title":"Evolution of cell size control is canalized towards adders or sizers by cell cycle structure and selective pressures","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Cell cycle; Cell size; Cell biology; Cell division; Biology; Cell; Biological system; Genetics","score_opus":0.003379354484517074,"score_gpt":0.1929610442020204,"score_spread":0.18958168971750333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224075414","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":[0.985672,0.010551377,0.0004751027,0.00005355195,0.00025618682,0.0006920857,0.002241921,0.00004246108,0.00001531239],"genre_scores_gemma":[0.9978532,0.0004900915,0.0010297678,0.00016071134,0.00018024353,0.00010225677,0.000004551433,0.00011238682,0.000066779015],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99703616,0.00033834027,0.0005056672,0.0011915199,0.00043155218,0.00049675046],"domain_scores_gemma":[0.997589,0.000042631833,0.0006643494,0.0010106327,0.00045230964,0.00024108187],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00029706862,0.00058250845,0.00073633523,0.00012183635,0.00017484071,0.000052827963,0.0005006093,0.0006413872,0.0002436458],"category_scores_gemma":[0.00012455252,0.0005989548,0.00024941398,0.0003817605,0.00021234072,0.000008360623,0.00047439875,0.00046122872,6.833247e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002943984,0.0000816339,0.005501427,0.00029933563,0.0006409745,0.0000049857795,0.00001743964,0.0028450303,0.98480576,0.0000025415754,0.005505653,7.900644e-7],"study_design_scores_gemma":[0.0016324301,0.00018596495,0.015561422,0.000028592485,0.00079630525,2.483318e-8,0.00002680926,0.00071600394,0.975577,0.000002407702,0.0047546616,0.000718401],"about_ca_topic_score_codex":0.0005618585,"about_ca_topic_score_gemma":0.00004023331,"teacher_disagreement_score":0.012181211,"about_ca_system_score_codex":0.00020466401,"about_ca_system_score_gemma":0.001220234,"threshold_uncertainty_score":0.9996462},"labels":[],"label_agreement":null},{"id":"W4225157602","doi":"10.1002/cjce.24427","title":"Robustness analysis of chemical process systems based on complex network non‐linear load capacity model","year":2022,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Robustness (evolution); Cascading failure; Chemical process; Computer science; Complex system; Reliability engineering; Engineering; Electric power system; Artificial intelligence","score_opus":0.012978043493423646,"score_gpt":0.20256047159503895,"score_spread":0.1895824281016153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225157602","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":[0.98631436,0.00023811044,0.013121526,0.00009181645,0.00008162346,0.00007532032,0.000035147023,0.0000035178207,0.000038596027],"genre_scores_gemma":[0.9989474,6.6870734e-7,0.00064054056,0.00007125615,0.0002551346,0.000008431684,0.000041828698,0.000025796047,0.000008960056],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99859494,0.000041201936,0.00043965277,0.00017919492,0.00040277594,0.000342209],"domain_scores_gemma":[0.99882764,0.00002849413,0.00024286771,0.00034442407,0.00024271136,0.00031385024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055828964,0.00017603766,0.0004393374,0.0001584352,0.000085677835,0.000016413449,0.00054404483,0.00009509414,0.000023954966],"category_scores_gemma":[0.00007291632,0.00015489415,0.00034977656,0.00076242466,0.00007475911,0.000003358852,0.000037035665,0.0003419081,1.0391181e-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":[0.000032899796,0.000012863732,0.00021049696,0.00002110031,0.0005003637,0.000004104413,0.00002462007,0.86193365,0.13694717,0.000012150339,0.00028887883,0.0000117116615],"study_design_scores_gemma":[0.00022340837,0.00003590285,0.000032976874,0.000017635624,0.00049544376,0.000017546596,0.000010181039,0.95988923,0.03899549,0.0000032750406,0.0001268971,0.00015200565],"about_ca_topic_score_codex":0.00020098295,"about_ca_topic_score_gemma":0.00006676527,"teacher_disagreement_score":0.0979556,"about_ca_system_score_codex":0.00023692116,"about_ca_system_score_gemma":0.0006279481,"threshold_uncertainty_score":0.63164},"labels":[],"label_agreement":null},{"id":"W4226087859","doi":"","title":"Complexity of fixed point counting problems in Boolean Networks","year":2021,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Compute Canada","funders":"","keywords":"Mathematics; Fixed point; Boolean circuit; Computer science; Point (geometry); Discrete mathematics; Boolean network; Theoretical computer science; Boolean function","score_opus":0.015925657627068608,"score_gpt":0.22261800537033252,"score_spread":0.20669234774326392,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4226087859","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":[0.85449535,0.005001446,0.13374175,0.0010999108,0.00013045727,0.00038717565,0.000023239063,0.000034306227,0.005086369],"genre_scores_gemma":[0.9834516,0.000805276,0.013147346,0.000047021666,0.000037563626,0.00003408248,0.0016140592,0.0000412042,0.0008218161],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99493736,0.0030059908,0.0006758399,0.0007788689,0.00026724924,0.00033467272],"domain_scores_gemma":[0.99583524,0.0001247982,0.0006193556,0.0019282567,0.0013911948,0.00010112368],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0037853718,0.0002915384,0.0004795434,0.000115659495,0.00010452307,0.000119145836,0.0007887012,0.00039447803,0.000059735383],"category_scores_gemma":[0.00045160146,0.00034197862,0.00030748345,0.00033673047,0.00030359667,0.000006496587,0.0016731614,0.00043378395,0.000001516016],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010034548,0.003906668,0.2422743,0.0022245955,0.0020458286,0.000026790714,0.011080132,0.3026154,0.3783734,0.012610679,0.0039149914,0.04082683],"study_design_scores_gemma":[0.0023127394,0.0000031514398,0.08304883,0.006860138,0.0003399671,0.000028719609,0.00078568247,0.411495,0.48306903,0.0028690645,0.0069933264,0.0021943522],"about_ca_topic_score_codex":0.00093587814,"about_ca_topic_score_gemma":0.009184928,"teacher_disagreement_score":0.15922548,"about_ca_system_score_codex":0.000056744873,"about_ca_system_score_gemma":0.00024793882,"threshold_uncertainty_score":0.9999032},"labels":[],"label_agreement":null},{"id":"W4230244601","doi":"10.3410/f1000research.2-19.v1","title":"Moving beyond Type I and Type II neuron types","year":2013,"lang":"en","type":"preprint","venue":"F1000Research","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"University of Toronto; University Health Network","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Context (archaeology); Neuroscience; Terminology; Cognitive science; Computer science; Type (biology); Psychology; Biology; Ecology","score_opus":0.02076604723057324,"score_gpt":0.29412511363704696,"score_spread":0.2733590664064737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230244601","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":[0.98494804,0.010814614,0.00002340268,0.0003176093,0.00033921388,0.00032266602,0.000010691508,0.000024145234,0.0031995906],"genre_scores_gemma":[0.9790168,0.0031072316,0.0005303018,0.00011690833,0.0007408746,0.000026604019,0.00036728638,0.00007872388,0.016015306],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981114,0.00017407085,0.00021253889,0.0007280389,0.00033904324,0.00043485925],"domain_scores_gemma":[0.99831337,0.000019753674,0.00007553872,0.0008870017,0.0005129364,0.0001913937],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00034788923,0.00025632908,0.00026738245,0.00013734798,0.00017278623,0.000101067286,0.0004707556,0.0004412106,0.0003482685],"category_scores_gemma":[0.00020786858,0.0002491959,0.000080996324,0.00024784295,0.00015520607,0.0000029718892,0.0032407718,0.00047728338,0.00010762914],"study_design_candidate":"not_applicable","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":[0.000350442,0.00021488593,0.034967713,0.00058736594,0.0013543487,0.000040375035,0.00023192591,0.0070492956,0.68077326,0.00033170226,0.24239174,0.031706933],"study_design_scores_gemma":[0.0015769424,0.0034593798,0.11763964,0.00029505155,0.00070288795,0.0000873474,0.00020575446,0.028669557,0.10645644,0.0063519045,0.73090076,0.0036543498],"about_ca_topic_score_codex":0.00010017417,"about_ca_topic_score_gemma":0.00003584535,"teacher_disagreement_score":0.57431686,"about_ca_system_score_codex":0.000023394867,"about_ca_system_score_gemma":0.0002899219,"threshold_uncertainty_score":0.999996},"labels":[],"label_agreement":null},{"id":"W4230702056","doi":"10.1137/1.9781611974713.ch2","title":"CHAPTER 2: Linear Stochastic Systems","year":2018,"lang":"en","type":"book-chapter","venue":"Society for Industrial and Applied Mathematics eBooks","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"McGill University","funders":"","keywords":"Set (abstract data type); Class (philosophy); Domain (mathematical analysis); Range (aeronautics); Dynamical systems theory; Identification (biology); Computer science; Feature (linguistics); Mathematics; Theoretical computer science; Artificial intelligence; Engineering; Mathematical analysis; Physics","score_opus":0.039034242976192415,"score_gpt":0.23499659383995566,"score_spread":0.19596235086376323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230702056","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026360042,0.004384921,0.0935914,0.00014596526,0.0027683706,0.013671592,0.0016994259,0.00034773396,0.8570306],"genre_scores_gemma":[0.03475066,0.00012183767,0.011210925,0.00020940612,0.013870297,0.00039462154,0.00076183316,0.0005200423,0.93816036],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99836963,0.000003005963,0.0005056568,0.0005719777,0.00023025597,0.0003194934],"domain_scores_gemma":[0.9987894,0.000036817444,0.00041184202,0.0004976283,0.00011753505,0.0001467366],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00032371114,0.0004930833,0.0006172956,0.00003295982,0.0002105112,0.000054105585,0.00020692374,0.0012314775,0.00003295844],"category_scores_gemma":[0.000011125446,0.00045447014,0.0006451722,0.0000096291515,0.00030515416,0.0000010237591,0.00018966496,0.00024307886,0.000017002758],"study_design_candidate":"not_applicable","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":[0.0004182536,0.00012792172,7.3949514e-7,0.0017122526,0.01111626,0.0000020284383,0.0017541636,0.0009122322,0.036761276,0.8340917,0.09914826,0.0139548695],"study_design_scores_gemma":[0.004650584,0.00087781076,9.263607e-8,0.00070068036,0.003851684,0.000045462668,0.0008035547,0.0043758694,0.0071746362,0.065211944,0.90940803,0.0028996582],"about_ca_topic_score_codex":7.6847266e-7,"about_ca_topic_score_gemma":0.0000016117111,"teacher_disagreement_score":0.81025976,"about_ca_system_score_codex":0.000022055503,"about_ca_system_score_gemma":0.0000804242,"threshold_uncertainty_score":0.9997907},"labels":[],"label_agreement":null},{"id":"W4231152591","doi":"10.1109/csb.2004.1332515","title":"A genetic algorithm for inferring time delays in gene regulatory networks","year":2004,"lang":"en","type":"article","venue":"Proceedings. 2004 IEEE Computational Systems Bioinformatics Conference, 2004. CSB 2004.","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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 Saskatchewan","funders":"","keywords":"Gene regulatory network; Computer science; Boolean network; Genetic algorithm; Algorithm; Genetic network; Gene; Boolean function; Machine learning; Biology; Gene expression; Genetics","score_opus":0.010060245032442551,"score_gpt":0.21957455008838334,"score_spread":0.2095143050559408,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231152591","genre_codex":"methods","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":[0.15651412,0.0028853985,0.83760893,0.00004045631,0.0004625509,0.00155946,0.000094141156,0.000105717474,0.0007292118],"genre_scores_gemma":[0.8944907,0.0000783675,0.102938235,0.00017166654,0.00091117324,0.00029419933,0.00055177975,0.00009892101,0.00046494813],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99607253,0.000030257665,0.0015677888,0.0007019958,0.0006558665,0.00097153394],"domain_scores_gemma":[0.99745506,0.000030927407,0.000719585,0.00034966375,0.0011023132,0.00034244603],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00066855876,0.0006589794,0.00073596055,0.0004735365,0.0002915138,0.0003023606,0.000588132,0.00056391215,0.000013415361],"category_scores_gemma":[0.000049550912,0.0007047743,0.00029798588,0.00070332247,0.00018188929,0.00007723498,0.00011563574,0.00027357897,0.00006540121],"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":[0.000038710285,0.00011445374,0.0006792514,0.0001626408,0.00022853183,0.0000038402072,0.0001849611,0.9901751,0.0014198844,0.0003733183,0.0022756606,0.0043436456],"study_design_scores_gemma":[0.0025493249,0.00027215522,0.0015925111,0.00029018978,0.00010909756,0.00016533125,0.00015385576,0.9906009,0.0014685581,0.000863034,0.0010112342,0.0009238276],"about_ca_topic_score_codex":0.000045973495,"about_ca_topic_score_gemma":0.000019096322,"teacher_disagreement_score":0.7379766,"about_ca_system_score_codex":0.00037247414,"about_ca_system_score_gemma":0.00066263584,"threshold_uncertainty_score":0.9995403},"labels":[],"label_agreement":null},{"id":"W4231562440","doi":"10.21203/rs.3.rs-748009/v1","title":"Carryover of a saddle-node bifurcation after transforming a parameter into a variable","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Athabasca University; University of Alberta","funders":"","keywords":"Bifurcation; Saddle-node bifurcation; Variable (mathematics); Saddle; Node (physics); Mathematics; Mathematical analysis; Control theory (sociology); Economics; Computer science; Physics; Mathematical optimization; Control (management); Artificial intelligence; Nonlinear system","score_opus":0.02307081640292161,"score_gpt":0.32927307124205696,"score_spread":0.3062022548391353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231562440","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":[0.9794939,0.011477476,0.0077394135,0.00011227537,0.00009654281,0.0005790134,0.000052868734,0.00001057989,0.00043789763],"genre_scores_gemma":[0.9921835,0.0007375075,0.005035014,0.000031729785,0.00028367335,0.00040126924,0.00075366243,0.000056685116,0.00051697873],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99693036,0.00052125886,0.00043372705,0.00084153307,0.0007502388,0.000522901],"domain_scores_gemma":[0.997482,0.00005805061,0.00011109039,0.0012860016,0.00090902974,0.00015384112],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010771021,0.00026920743,0.00042960802,0.00027226587,0.00008572853,0.00008805479,0.00039746935,0.00064871873,0.00020147579],"category_scores_gemma":[0.00025517773,0.0002726014,0.00041401776,0.00049255363,0.00015929,0.000005611941,0.00077581283,0.00058817834,0.0000059940676],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011011121,0.00085718057,0.036035206,0.0090517765,0.0032351196,0.00008329204,0.0038063757,0.03210154,0.8905419,0.000109500244,0.0027130467,0.02036396],"study_design_scores_gemma":[0.0025826634,0.0011755514,0.019396754,0.0047872295,0.00093677634,0.000041267296,0.0035884145,0.01837186,0.8806804,0.003457737,0.06217907,0.0028022635],"about_ca_topic_score_codex":0.00048709518,"about_ca_topic_score_gemma":0.0003197131,"teacher_disagreement_score":0.059466023,"about_ca_system_score_codex":0.00010832677,"about_ca_system_score_gemma":0.0008331266,"threshold_uncertainty_score":0.99997264},"labels":[],"label_agreement":null},{"id":"W4232922950","doi":"10.32920/ryerson.14644779.v1","title":"Adaptive time-stepping in the numerical solution of the reaction-diffusion master equation","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Reaction–diffusion system; Time stepping; Computer science; Diffusion; Computer simulation; Master equation; Stochastic simulation; Scheme (mathematics); Applied mathematics; Numerical analysis; Mathematical optimization; Statistical physics; Algorithm; Mathematics; Simulation; Mathematical analysis; Physics","score_opus":0.024568505154887635,"score_gpt":0.23504387890389053,"score_spread":0.21047537374900288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232922950","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":[0.96093273,0.0005080768,0.03596977,0.0005413418,0.00019077928,0.0003397526,0.00000335165,0.0000050234544,0.0015091541],"genre_scores_gemma":[0.99835056,0.000058028363,0.0005594197,0.00012549276,0.0001634052,0.000025954938,0.00016867684,0.0000117245445,0.0005367302],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985775,0.00040232524,0.00029411027,0.00035040907,0.00024130296,0.00013436403],"domain_scores_gemma":[0.99895793,0.00001989906,0.00023706055,0.0006608107,0.00010769613,0.000016574384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036370388,0.00014975305,0.00018385438,0.00003846435,0.00005611934,0.0000192294,0.0002774641,0.0002835633,0.000034232373],"category_scores_gemma":[0.000045350986,0.00009456543,0.00024802992,0.0001752239,0.000044955803,0.0000021210187,0.00053402747,0.00022363084,0.0000034493846],"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":[0.00005875134,0.00015067529,0.00304182,0.000034603614,0.0002114748,0.0000011212895,0.00036874038,0.02698382,0.96457034,0.000041452935,0.00084113283,0.0036960396],"study_design_scores_gemma":[0.0014229877,0.00032577827,0.21052778,0.00067027967,0.0009770623,0.000043136348,0.003913916,0.49464107,0.28129908,0.0008225097,0.0039023717,0.0014540051],"about_ca_topic_score_codex":0.00015610804,"about_ca_topic_score_gemma":0.00013177523,"teacher_disagreement_score":0.6832713,"about_ca_system_score_codex":0.00004018776,"about_ca_system_score_gemma":0.00011178949,"threshold_uncertainty_score":0.38562664},"labels":[],"label_agreement":null},{"id":"W4233892161","doi":"10.3410/f.725236495.793508584","title":"Faculty Opinions recommendation of Synthetic biology. Genomically encoded analog memory with precise in vivo DNA writing in living cell populations.","year":2015,"lang":"en","type":"dataset","venue":"Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"In vivo; Biology; DNA; Computational biology; Genetics","score_opus":0.02336189903627517,"score_gpt":0.3176608367309541,"score_spread":0.2942989376946789,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233892161","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002914118,0.00204459,0.000058301783,0.012493804,0.00021218155,0.0010104772,0.9838214,0.000010462698,0.000057366713],"genre_scores_gemma":[0.0016316868,0.00031100836,0.0013063123,0.00051700714,0.00017722668,0.00016601612,0.99561924,0.00003062674,0.00024089881],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9956765,0.0008396463,0.0016718111,0.00082377973,0.00060553476,0.00038272573],"domain_scores_gemma":[0.99468577,0.00008173931,0.001322276,0.0013422833,0.00235683,0.00021110618],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0020661002,0.00047458863,0.00090669625,0.0005007431,0.000096518226,0.00005316592,0.0011474736,0.00079826557,0.00011069068],"category_scores_gemma":[0.0028866853,0.00033945718,0.00036651106,0.0017396203,0.00027527503,0.000031614127,0.000491118,0.00060869404,0.000005533282],"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":[0.000019961744,0.00033255052,0.00031457646,0.0015347422,0.000078596226,2.7376848e-7,0.00005927457,0.000023522178,0.00019187383,0.000012561905,0.9968394,0.00059263903],"study_design_scores_gemma":[0.00056790793,0.00014931658,0.002465362,0.0053866743,0.00015703442,0.00001677986,0.00005072479,0.00006858759,0.0002383795,0.000017017204,0.990508,0.00037416953],"about_ca_topic_score_codex":0.00007783847,"about_ca_topic_score_gemma":0.00016864395,"teacher_disagreement_score":0.011976797,"about_ca_system_score_codex":0.00013523048,"about_ca_system_score_gemma":0.0006238959,"threshold_uncertainty_score":0.99990577},"labels":[],"label_agreement":null},{"id":"W4234525228","doi":"10.32920/14650038","title":"Adaptive Methods For Stochastic Simulation Of Biochemical Systems","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Key (lock); Scale (ratio); Noise (video); Stochastic simulation; Stochastic process; Mathematical optimization; Stochastic modelling; Mathematics; Artificial intelligence","score_opus":0.03167196576424023,"score_gpt":0.3477356095726567,"score_spread":0.31606364380841645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234525228","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":[0.07561052,0.0063068327,0.9171958,0.000009365525,0.00029035623,0.0004822686,0.000028362754,0.000009768627,0.00006670597],"genre_scores_gemma":[0.91889274,0.000023456401,0.07950352,0.0000118847975,0.00031992266,0.00010566472,0.0008007867,0.00003394358,0.00030807406],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984789,0.000181038,0.00043119336,0.00060918793,0.0001145484,0.00018516515],"domain_scores_gemma":[0.9983702,0.00009186117,0.00029686975,0.0006590206,0.00051260524,0.000069449954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038571205,0.0002413632,0.0004903724,0.00006312378,0.00002595466,0.000023203114,0.00021012394,0.00057701557,0.000010785199],"category_scores_gemma":[0.0001841487,0.00024034239,0.00044231536,0.00008470457,0.000057269328,8.4288183e-7,0.00044164414,0.00010792318,3.5896366e-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":[0.000048312595,0.000031238018,0.000007668214,0.00012901699,0.00051760307,1.0630989e-7,0.0000132921705,0.82651967,0.17153782,0.00002783585,0.00018719517,0.0009802711],"study_design_scores_gemma":[0.00022287613,0.000089271976,0.000020239695,0.00007254292,0.0003801199,0.0000015056287,0.00013978902,0.85938835,0.13899253,0.000109532804,0.0002981994,0.0002850315],"about_ca_topic_score_codex":0.000019311388,"about_ca_topic_score_gemma":0.0000033343276,"teacher_disagreement_score":0.8432822,"about_ca_system_score_codex":0.000026871212,"about_ca_system_score_gemma":0.00018540883,"threshold_uncertainty_score":0.9800878},"labels":[],"label_agreement":null},{"id":"W4234842352","doi":"10.32920/ryerson.14653782","title":"Numerical studies of higher order tau-leaping methods","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Scheme (mathematics); Order (exchange); Algorithm; Stochastic simulation; Basis (linear algebra); Mathematical optimization; Applied mathematics; Mathematics; Statistics","score_opus":0.04219549741962515,"score_gpt":0.38099242242496445,"score_spread":0.3387969250053393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234842352","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":[0.50118756,0.19374935,0.29410404,0.0009633166,0.0025623655,0.0005076287,0.000011282935,0.000072308,0.006842108],"genre_scores_gemma":[0.74644434,0.0023360546,0.24327582,0.0002914018,0.0005502387,0.000041388394,0.00020446442,0.0000562334,0.0068000704],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9981066,0.00036457815,0.00043987815,0.0006874527,0.0001690468,0.00023244777],"domain_scores_gemma":[0.99825674,0.00003021244,0.0002366055,0.0009029131,0.000507205,0.000066299566],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00037032072,0.00029506072,0.00069006695,0.00005617571,0.000038519283,0.000019407473,0.00028525657,0.0004193256,0.00023038175],"category_scores_gemma":[0.00013283083,0.00026361903,0.00041367544,0.00020241752,0.00012455018,9.196809e-7,0.0012861764,0.00020174007,0.0000022743216],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000077266086,0.00035902506,0.0053721787,0.0013156502,0.018508112,0.000022940983,0.0003865437,0.10612114,0.8027541,0.00025619642,0.030271947,0.03455491],"study_design_scores_gemma":[0.00048782318,0.000148231,0.0028607931,0.00020795118,0.0011889344,0.000010514303,0.00093017373,0.0019147304,0.93821776,0.0005898326,0.052162528,0.0012807089],"about_ca_topic_score_codex":0.000029490599,"about_ca_topic_score_gemma":0.0000119663455,"teacher_disagreement_score":0.24525675,"about_ca_system_score_codex":0.000021677244,"about_ca_system_score_gemma":0.00015896169,"threshold_uncertainty_score":0.9999816},"labels":[],"label_agreement":null},{"id":"W4234971056","doi":"10.22215/etd/2009-09081","title":"DEVS-based dynamic simulation of deformable biological structures","year":2009,"lang":"en","type":"dissertation","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Library and Archives Canada","funders":"","keywords":"DEVS; Computer science; Simulation; Modeling and simulation","score_opus":0.007366422830298818,"score_gpt":0.27204560655574783,"score_spread":0.264679183725449,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234971056","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":[0.9931651,0.0011139236,0.003956065,0.000004729495,0.00009818907,0.00015828012,0.00001123217,0.00001529741,0.0014771897],"genre_scores_gemma":[0.9882156,0.00006693466,0.0010323935,0.00005157312,0.00006768397,0.000005161405,0.008401131,0.000019952755,0.0021395348],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989359,0.000044932232,0.00034122635,0.00033722524,0.00015188662,0.00018887989],"domain_scores_gemma":[0.9991663,0.000009772881,0.00026086174,0.0003488221,0.0001658039,0.000048422997],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008286362,0.00023979715,0.00029656867,0.00010052885,0.000046454836,0.000010099278,0.00018113242,0.0005896911,0.00008345239],"category_scores_gemma":[0.00003131768,0.00019662084,0.00025652928,0.00013124188,0.000027161788,0.0000014041586,0.000012826672,0.00008367639,0.0000031129384],"study_design_candidate":"simulation_or_modeling","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":[0.00027949843,0.00004775301,0.0005611391,0.00006346242,0.00018157523,8.034858e-7,0.00000895134,0.8037761,0.17903765,0.000033686218,0.00017654723,0.015832882],"study_design_scores_gemma":[0.0010468478,0.00094168703,0.0689734,0.00006214095,0.00036799762,0.0000023471362,0.00016609256,0.25504902,0.66540956,0.0012487917,0.005588582,0.001143536],"about_ca_topic_score_codex":0.000011107778,"about_ca_topic_score_gemma":0.00036433752,"teacher_disagreement_score":0.54872704,"about_ca_system_score_codex":0.000018180845,"about_ca_system_score_gemma":0.000115144074,"threshold_uncertainty_score":0.8017965},"labels":[],"label_agreement":null},{"id":"W4235868717","doi":"10.1016/j.bpj.2014.11.1999","title":"Environmental Statistics and Optimal Regulation","year":2015,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Thresholding; Bayesian probability; Expression (computer science); Organism; Set (abstract data type); Computer science; Econometrics; Statistics; Biology; Artificial intelligence; Mathematics","score_opus":0.008582016018746872,"score_gpt":0.224083788581655,"score_spread":0.21550177256290814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4235868717","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":[0.9827883,0.0001405624,0.01685083,0.00005529752,0.00006594298,0.00002580879,0.000010857623,0.0000027929073,0.00005955694],"genre_scores_gemma":[0.9935471,0.000053963944,0.0053690625,0.00004165747,0.00071685156,8.1559904e-7,0.000036486414,0.00001052978,0.0002235225],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99942404,0.00004416411,0.00011739434,0.00013298835,0.0001548067,0.00012659573],"domain_scores_gemma":[0.9996062,0.000003261208,0.00006252685,0.00010343721,0.000023241888,0.0002013506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000094666226,0.000083224404,0.00008423023,0.000018891027,0.000060641974,0.000032757,0.000060259492,0.00005373664,0.000017542336],"category_scores_gemma":[0.000012555798,0.00007473808,0.000041591356,0.000028131752,0.000080018704,0.000003811633,0.000055576056,0.000065572,0.0000140019265],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057083213,0.000053661082,0.0017841392,0.0000013146368,0.000066197346,0.000006996356,0.000027807768,0.00091089745,0.9820987,0.00008019388,0.008461343,0.00645165],"study_design_scores_gemma":[0.005510431,0.0032439886,0.21718529,0.000025747584,0.0005819408,0.0016915997,0.000732656,0.0641933,0.58784294,0.0022445964,0.11506527,0.001682243],"about_ca_topic_score_codex":6.266582e-7,"about_ca_topic_score_gemma":4.1010017e-7,"teacher_disagreement_score":0.3942558,"about_ca_system_score_codex":0.000017817401,"about_ca_system_score_gemma":0.000026905713,"threshold_uncertainty_score":0.30477303},"labels":[],"label_agreement":null},{"id":"W4237714638","doi":"10.1109/iembs.2006.4398785","title":"A Neural Network Based Approach for Inference and Verification of Transcriptional Regulatory Interactions","year":2006,"lang":"en","type":"article","venue":"Conference proceedings","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Queen's University","funders":"","keywords":"Correctness; Computer science; Robustness (evolution); Inference; Artificial neural network; Machine learning; Artificial intelligence; Data mining; Set (abstract data type); Sensitivity (control systems); Gene regulatory network; Algorithm; Gene; Engineering","score_opus":0.018093619629102577,"score_gpt":0.24207227924160035,"score_spread":0.22397865961249777,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237714638","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":[0.887477,0.00030468896,0.111158565,0.00008498064,0.000038215123,0.00022765249,0.000011035746,0.000013602364,0.00068425684],"genre_scores_gemma":[0.98960674,0.000009716704,0.00967573,0.000033369382,0.00019992833,0.000088064546,0.0001848605,0.000011489076,0.00019012846],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992421,0.000008011627,0.00020968694,0.00029403766,0.000090098394,0.00015602543],"domain_scores_gemma":[0.9994012,0.000009443372,0.00012727776,0.00010019473,0.00032191584,0.000039946855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013037148,0.00011651546,0.00013797669,0.00004318577,0.00007739683,0.000028354762,0.000104807914,0.00008109411,0.000007888159],"category_scores_gemma":[0.000021576336,0.00012093747,0.00007557381,0.00010883892,0.000114809714,0.000010465785,0.000018253182,0.000048657563,1.7210643e-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":[0.000144243,0.00008880347,0.033838626,0.00012583961,0.000047696423,3.3565538e-8,0.000044690863,0.0071603516,0.9442975,0.011078182,0.001547512,0.0016265373],"study_design_scores_gemma":[0.0016443854,0.00040880503,0.18514094,0.0000743082,0.00028595552,0.000012310224,0.00027095727,0.6611031,0.13551146,0.003042479,0.011792094,0.0007131969],"about_ca_topic_score_codex":0.0000066647403,"about_ca_topic_score_gemma":0.000006593737,"teacher_disagreement_score":0.80878603,"about_ca_system_score_codex":0.000008385177,"about_ca_system_score_gemma":0.000059088125,"threshold_uncertainty_score":0.49316868},"labels":[],"label_agreement":null},{"id":"W4238044183","doi":"10.1145/952548.952561","title":"Inference of transcriptional regulation relationships from gene expression data","year":2003,"lang":"en","type":"article","venue":"Proceedings of the 2003 ACM symposium on Applied computing - SAC '03","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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":"","keywords":"False positive paradox; Inference; Event (particle physics); Computer science; Gene; Computational biology; Expression (computer science); Correlation; Microarray analysis techniques; Data mining; Transcriptional regulation; Gene expression; Biology; Artificial intelligence; Mathematics; Genetics","score_opus":0.02942175734017426,"score_gpt":0.24623415979889218,"score_spread":0.2168124024587179,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4238044183","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":[0.9928925,0.0002202641,0.0026025428,0.0001069238,0.00014392375,0.0002950193,0.000039531114,0.000018975477,0.0036803284],"genre_scores_gemma":[0.9814266,0.000028225217,0.018064318,0.000045824778,0.00013736771,0.000006314549,0.00016515535,0.000026525327,0.000099676334],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983177,0.000045280012,0.00048255236,0.00056727935,0.0003776291,0.00020954064],"domain_scores_gemma":[0.9982647,0.00005217888,0.0005114634,0.0008219782,0.00028914018,0.00006057525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006055127,0.00021045712,0.00025153736,0.00006664714,0.00019428799,0.00002359239,0.0009995772,0.00021375186,0.000014883978],"category_scores_gemma":[0.00035119863,0.00018088231,0.00008681713,0.0004101277,0.00010705344,0.000010862899,0.00032238103,0.00019368604,0.0000046093724],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005958959,0.000075290656,0.010312572,0.000023620087,0.00007075818,2.0552108e-8,0.000088763416,0.007399703,0.9778981,0.0027746256,0.0011425688,0.00015435944],"study_design_scores_gemma":[0.00048597218,0.000041141135,0.012728768,0.00007731277,0.00011155254,0.0000018202471,0.000073727446,0.0031339875,0.97961205,0.0020765236,0.0014405438,0.00021660085],"about_ca_topic_score_codex":0.00000470871,"about_ca_topic_score_gemma":0.0000012910103,"teacher_disagreement_score":0.015461775,"about_ca_system_score_codex":0.000022983773,"about_ca_system_score_gemma":0.000075540476,"threshold_uncertainty_score":0.73761666},"labels":[],"label_agreement":null},{"id":"W4239557454","doi":"10.1515/iupac.76.0122","title":"Allometry (in Biology)","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Glossary; Toxicokinetics; Relation (database); Toxicology; Computer science; Medicine; Biology; Pharmacology; Data mining; Linguistics; Philosophy","score_opus":0.008187261707805824,"score_gpt":0.37338863058081345,"score_spread":0.36520136887300764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4239557454","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0051466287,0.004761875,0.00016397609,0.00015996216,0.0003516285,0.00015686975,0.98922104,0.0000115434195,0.000026454452],"genre_scores_gemma":[0.0010393957,0.0034808267,0.00006469942,0.0002260964,0.001310232,0.000015477035,0.9933564,0.00004293743,0.00046393074],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977016,0.0001488135,0.0004784375,0.0008124766,0.00034254373,0.0005161632],"domain_scores_gemma":[0.99820423,0.000017371536,0.00022288435,0.0012033698,0.00021093387,0.00014119755],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005554434,0.0004406608,0.0005897552,0.0003293882,0.00004699872,0.000018948609,0.00057217415,0.00085966307,0.0007155878],"category_scores_gemma":[0.00027585137,0.00035729326,0.0002897066,0.0002925814,0.00016592424,0.0000019208671,0.0003234399,0.0002597662,0.0000025381144],"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":[0.00008522934,0.00010512321,0.00038912456,0.000031815613,0.00022658113,0.00001581503,7.085162e-7,0.000013076523,0.00253848,0.0000018151243,0.9946309,0.0019613556],"study_design_scores_gemma":[0.0006731534,0.00020064837,0.00014307717,0.00007740416,0.00009184097,0.000007694747,0.000004491942,0.000002839649,0.00059306645,0.000065825596,0.9977007,0.0004392738],"about_ca_topic_score_codex":0.000045899484,"about_ca_topic_score_gemma":0.0015528878,"teacher_disagreement_score":0.004135343,"about_ca_system_score_codex":0.00015539426,"about_ca_system_score_gemma":0.0004903233,"threshold_uncertainty_score":0.9998879},"labels":[],"label_agreement":null},{"id":"W4239695298","doi":"10.32920/ryerson.14663355","title":"Numerical studies of Implicit Tau Leaping methods for stochastic biochemical systems","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Toronto Metropolitan University","funders":"","keywords":"Randomness; Computer science; Statistical physics; Population; Key (lock); Applied mathematics; Algorithm; Mathematical optimization; Mathematics; Statistics; Physics","score_opus":0.04412917166856525,"score_gpt":0.38147800565509166,"score_spread":0.33734883398652643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4239695298","genre_codex":"methods","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":[0.13012819,0.055861056,0.81284994,0.00005885241,0.0005328632,0.00049229735,0.000017559483,0.000018206129,0.000041042167],"genre_scores_gemma":[0.9193596,0.0003692024,0.07855339,0.00004589776,0.0005849697,0.00028549918,0.00040904252,0.000059910275,0.0003324517],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9976714,0.00022906005,0.000683603,0.00091304985,0.0001525251,0.00035031058],"domain_scores_gemma":[0.9978977,0.00012505385,0.00036672287,0.00091346924,0.0005922911,0.000104795006],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005949408,0.0003829303,0.0010598436,0.00007889463,0.000056731576,0.000034238914,0.00036537444,0.00055992714,0.0000071541795],"category_scores_gemma":[0.0004472789,0.00035547357,0.00068799267,0.00013714416,0.00012619652,0.0000010774461,0.0009494852,0.00018420526,5.536997e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000053393054,0.000080839694,0.000058929672,0.0012294375,0.0039986656,8.529552e-7,0.000073059695,0.1220659,0.86713475,0.00009898687,0.0031479553,0.0020572213],"study_design_scores_gemma":[0.00079241453,0.00032108228,0.00008585631,0.0005708537,0.0018909258,0.00004079869,0.0020657033,0.07256015,0.91799456,0.00040776198,0.0018667988,0.0014030983],"about_ca_topic_score_codex":0.000034208595,"about_ca_topic_score_gemma":0.0000027674378,"teacher_disagreement_score":0.7892315,"about_ca_system_score_codex":0.000049189886,"about_ca_system_score_gemma":0.00020811547,"threshold_uncertainty_score":0.99988973},"labels":[],"label_agreement":null},{"id":"W4240370728","doi":"10.32920/ryerson.14648274","title":"An Efficient Tau-Leaping Simulation Method for Stochastic Biochemical Kinetics","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Toronto Metropolitan University","funders":"","keywords":"Stochastic simulation; Computer science; Stochastic modelling; Stochastic process; Statistical physics; Biological system; Mathematical optimization; Mathematics; Biology; Physics","score_opus":0.018378743472871835,"score_gpt":0.3234674294380264,"score_spread":0.3050886859651546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4240370728","genre_codex":"methods","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":[0.3115705,0.0008428776,0.6869119,0.000038243714,0.00020341571,0.00036277296,0.000020211128,0.000024968673,0.000025097323],"genre_scores_gemma":[0.8502246,0.000010255314,0.14613597,0.00011814873,0.0007148596,0.000076212986,0.0025350591,0.00006333449,0.00012154928],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977082,0.00014661807,0.00044327276,0.001112818,0.00022656684,0.0003625346],"domain_scores_gemma":[0.9980573,0.00005744949,0.00021017136,0.001093405,0.00041015144,0.00017150317],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00035006704,0.000378676,0.00042374537,0.00008962773,0.000071902025,0.000100027086,0.00035020057,0.000717693,0.000035821395],"category_scores_gemma":[0.00016134807,0.0003987037,0.0004445503,0.00011890251,0.000046574492,0.0000010793103,0.0005009914,0.00018760377,0.0000015220513],"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":[0.000025120278,0.00009380062,0.0000069676094,0.000052754647,0.00015407077,4.2475233e-7,0.000020527,0.67802846,0.32040468,0.000010142218,0.00013763802,0.0010654418],"study_design_scores_gemma":[0.00025918888,0.000106104606,0.00005568827,0.000033321863,0.00029133647,0.0000025579059,0.00007357497,0.8345865,0.16382542,0.00005298116,0.0002937925,0.00041951344],"about_ca_topic_score_codex":0.000009907833,"about_ca_topic_score_gemma":0.0000143546,"teacher_disagreement_score":0.54077595,"about_ca_system_score_codex":0.000050767885,"about_ca_system_score_gemma":0.00014455628,"threshold_uncertainty_score":0.99984646},"labels":[],"label_agreement":null},{"id":"W4240499484","doi":"10.32920/14650038.v1","title":"Adaptive Methods For Stochastic Simulation Of Biochemical Systems","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Key (lock); Scale (ratio); Noise (video); Stochastic simulation; Mathematical optimization; Stochastic process; Stochastic modelling; Mathematics; Artificial intelligence","score_opus":0.03167196576424023,"score_gpt":0.3477356095726567,"score_spread":0.31606364380841645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4240499484","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":[0.07561052,0.0063068327,0.9171958,0.000009365525,0.00029035623,0.0004822686,0.000028362754,0.000009768627,0.00006670597],"genre_scores_gemma":[0.91889274,0.000023456401,0.07950352,0.0000118847975,0.00031992266,0.00010566472,0.0008007867,0.00003394358,0.00030807406],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984789,0.000181038,0.00043119336,0.00060918793,0.0001145484,0.00018516515],"domain_scores_gemma":[0.9983702,0.00009186117,0.00029686975,0.0006590206,0.00051260524,0.000069449954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038571205,0.0002413632,0.0004903724,0.00006312378,0.00002595466,0.000023203114,0.00021012394,0.00057701557,0.000010785199],"category_scores_gemma":[0.0001841487,0.00024034239,0.00044231536,0.00008470457,0.000057269328,8.4288183e-7,0.00044164414,0.00010792318,3.5896366e-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":[0.000048312595,0.000031238018,0.000007668214,0.00012901699,0.00051760307,1.0630989e-7,0.0000132921705,0.82651967,0.17153782,0.00002783585,0.00018719517,0.0009802711],"study_design_scores_gemma":[0.00022287613,0.000089271976,0.000020239695,0.00007254292,0.0003801199,0.0000015056287,0.00013978902,0.85938835,0.13899253,0.000109532804,0.0002981994,0.0002850315],"about_ca_topic_score_codex":0.000019311388,"about_ca_topic_score_gemma":0.0000033343276,"teacher_disagreement_score":0.8432822,"about_ca_system_score_codex":0.000026871212,"about_ca_system_score_gemma":0.00018540883,"threshold_uncertainty_score":0.9800878},"labels":[],"label_agreement":null},{"id":"W4240637682","doi":"10.1515/jib-2016-289","title":"Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2016","year":2016,"lang":"en","type":"article","venue":"Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"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":"Computer science; Synthetic biology; Data science; Engineering management; Management science; Biology; Computational biology; Engineering","score_opus":0.014916126587391134,"score_gpt":0.2719761920514411,"score_spread":0.25706006546404997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4240637682","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":[0.9600292,0.008879063,0.024172772,0.00019290007,0.00039549908,0.0008129791,0.00033413453,0.000013943506,0.0051695406],"genre_scores_gemma":[0.9751465,0.008427545,0.016152686,0.0000769941,0.000046769615,0.000018595501,0.0000478898,0.00001931896,0.00006371345],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99590886,0.00010492731,0.0028115094,0.00014958283,0.00050887227,0.0005162229],"domain_scores_gemma":[0.99652547,0.0001599949,0.0018263521,0.00034347438,0.000883079,0.00026162056],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0015847777,0.00042492256,0.0008205535,0.0009071701,0.00006123053,0.0000696844,0.0003583553,0.00028902187,0.000010484107],"category_scores_gemma":[0.0006772239,0.00025165142,0.00011030309,0.000608171,0.000534682,0.0003013195,0.0002203908,0.00023919618,0.0000049834925],"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":[0.002625703,0.0007311979,0.44501343,0.00304836,0.005425819,0.000024101078,0.078261524,0.0009308139,0.032510556,0.014968676,0.0075847395,0.40887508],"study_design_scores_gemma":[0.03579595,0.008655913,0.21806043,0.01342955,0.0013395571,0.0016124657,0.13205191,0.019140733,0.09588998,0.0013079299,0.4667116,0.006003961],"about_ca_topic_score_codex":0.000022027987,"about_ca_topic_score_gemma":0.00005520163,"teacher_disagreement_score":0.4591269,"about_ca_system_score_codex":0.00016406892,"about_ca_system_score_gemma":0.0008364151,"threshold_uncertainty_score":0.99999356},"labels":[],"label_agreement":null},{"id":"W4241405951","doi":"10.32920/ryerson.14657604.v1","title":"Accurate Stochastic Simulation Methods for Homogeneous Biochemical Networks","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Toronto Metropolitan University","funders":"","keywords":"Stochastic simulation; Master equation; Representation (politics); Homogeneous; Stochastic process; Computer science; Stochastic modelling; Continuous-time stochastic process; Applied mathematics; Mathematics; Mathematical optimization; Statistical physics; Stochastic differential equation; Statistics; Physics","score_opus":0.02425746526527309,"score_gpt":0.3511273006973368,"score_spread":0.32686983543206366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4241405951","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":[0.0745599,0.008339853,0.91586953,0.000038805636,0.00052919314,0.00055921345,0.000016320877,0.000037081638,0.00005009523],"genre_scores_gemma":[0.88225454,0.00013911293,0.112254426,0.00016513433,0.0011974174,0.00018869394,0.003084872,0.00008491692,0.0006308815],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975477,0.00022553382,0.0005049173,0.0011462021,0.00012774157,0.00044794127],"domain_scores_gemma":[0.9979194,0.0001233009,0.00026753874,0.0011071708,0.00041730813,0.00016531571],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004617409,0.00045990894,0.0005429246,0.000072245915,0.000099048215,0.000118234944,0.00040137442,0.0010644587,0.000054475768],"category_scores_gemma":[0.00026762503,0.00047444977,0.00071653374,0.0001445356,0.000069183036,0.0000016480014,0.00095073757,0.00025961048,0.0000015613755],"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":[0.000053896314,0.00003992879,0.000011449372,0.000045465844,0.00053667865,0.0000010186864,0.000008267864,0.94875914,0.0425098,0.000005480148,0.000803532,0.0072253165],"study_design_scores_gemma":[0.00027978237,0.000057900903,0.000036848454,0.00003062843,0.00045167893,0.0000073155015,0.000022546275,0.9602994,0.036251232,0.00014361698,0.0018446036,0.0005744745],"about_ca_topic_score_codex":0.0000073216897,"about_ca_topic_score_gemma":0.000013804807,"teacher_disagreement_score":0.8076947,"about_ca_system_score_codex":0.000044537937,"about_ca_system_score_gemma":0.0002146282,"threshold_uncertainty_score":0.9997707},"labels":[],"label_agreement":null},{"id":"W4241707166","doi":"10.1007/978-981-10-8046-3_1","title":"Motivating Examples","year":2018,"lang":"en","type":"book-chapter","venue":"Nonlinear physical science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Cognitive science; Psychology","score_opus":0.016962511204382115,"score_gpt":0.26094222853641286,"score_spread":0.24397971733203075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4241707166","genre_codex":"empirical","genre_gemma":"other","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":[0.51139295,0.0003598609,0.0008126869,0.000085509215,0.00035324282,0.00032232067,0.000065601525,0.000065481785,0.4865423],"genre_scores_gemma":[0.48535007,0.000090342735,0.009684207,0.00037807907,0.015225673,0.000009973594,0.0002928097,0.00016165189,0.48880717],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982102,0.0000102251615,0.00017273627,0.00078192353,0.00048409944,0.00034083604],"domain_scores_gemma":[0.99878114,0.0000131408315,0.00014915872,0.0006661201,0.0002293533,0.00016105728],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022061256,0.00026050807,0.00024680755,0.00006148693,0.00020225809,0.000050046103,0.0006083243,0.00014998435,0.00015531028],"category_scores_gemma":[0.00006793566,0.00023127058,0.00020089162,0.00010901455,0.0010984642,0.000004474483,0.0004256497,0.00014277692,0.00025784527],"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":[0.00002600367,0.00011731526,0.00011674654,0.000033703713,0.00018485276,0.00000689626,0.00013316098,0.00032485242,0.9541718,0.0065689418,0.0062777833,0.032037955],"study_design_scores_gemma":[0.00026627711,0.00056078617,0.00032029903,0.000113090595,0.00015917871,0.000011797674,0.00001900927,0.007350454,0.17308131,0.0075787795,0.80925244,0.0012865699],"about_ca_topic_score_codex":0.0000030782176,"about_ca_topic_score_gemma":0.0000075242356,"teacher_disagreement_score":0.80297464,"about_ca_system_score_codex":0.00003074254,"about_ca_system_score_gemma":0.00022372155,"threshold_uncertainty_score":0.9430941},"labels":[],"label_agreement":null},{"id":"W4242505789","doi":"10.1177/117762500700100010","title":"Computational Systems Biology in Cancer: Modeling Methods and Applications","year":2007,"lang":"en","type":"article","venue":"Gene Regulation and Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":31,"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 Alberta; National Institute for Nanotechnology","funders":"","keywords":"Rotation formalisms in three dimensions; Systems biology; Computer science; Petri net; Cellular automaton; Modelling biological systems; Process (computing); Computational biology; Data science; Bioinformatics; Biology; Artificial intelligence; Distributed computing; Mathematics; Programming language","score_opus":0.025546546589868616,"score_gpt":0.34420539109133746,"score_spread":0.31865884450146886,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4242505789","genre_codex":"methods","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":[0.44867256,0.01638659,0.5343549,0.00003299595,0.00014286475,0.0003036525,0.000013633425,0.00001217635,0.0000806004],"genre_scores_gemma":[0.9946766,0.0005809333,0.0037312391,0.000033581364,0.00042192836,0.00010161267,0.00033041046,0.000015556187,0.00010813099],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99838275,0.00031215235,0.0004965721,0.0004893252,0.000050166916,0.00026901512],"domain_scores_gemma":[0.9993742,0.000048368347,0.00015219078,0.00020921823,0.0001206799,0.00009530868],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011440495,0.0001641591,0.000301735,0.0001894063,0.000109285174,0.000021802474,0.00008027277,0.00031991923,0.0000030148335],"category_scores_gemma":[0.000014766615,0.00015703961,0.00004118569,0.00019063673,0.00010625261,0.0000040960867,0.00006804258,0.000063807965,0.0000013450662],"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":[0.000052150783,0.0000334073,0.07731047,0.000078109,0.00018361874,5.5418786e-7,0.000065866494,0.5443655,0.33672422,0.014516018,0.000044296336,0.026625754],"study_design_scores_gemma":[0.00089938444,0.00012166314,0.014368353,0.000025451773,0.00005871839,0.00009487693,0.00025146134,0.952967,0.0019614038,0.0016425434,0.027159952,0.0004492149],"about_ca_topic_score_codex":0.00027356163,"about_ca_topic_score_gemma":0.000099693185,"teacher_disagreement_score":0.54600406,"about_ca_system_score_codex":0.000033144763,"about_ca_system_score_gemma":0.00004541119,"threshold_uncertainty_score":0.64038897},"labels":[],"label_agreement":null},{"id":"W4243207516","doi":"10.1371/journal.pcbi.0030024.eor","title":"Dose Response Relationship in Anti-Stress Gene Regulatory Networks","year":2005,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"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":"American Chemistry Council","keywords":"Gene regulatory network; Fight-or-flight response; Computational biology; Regulation of gene expression; Gene; Biology; Gene expression; Genetics","score_opus":0.015220823813495406,"score_gpt":0.2546068226191734,"score_spread":0.23938599880567799,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4243207516","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":[0.990297,0.0014848922,0.0073199132,0.0005459468,0.00006924735,0.00014682913,0.000020204445,0.000024644312,0.000091300375],"genre_scores_gemma":[0.99243796,0.000031808642,0.005590437,0.00035850663,0.00047371903,0.000025276971,0.0008891449,0.000024673827,0.00016849094],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99822056,0.00046555343,0.00039413996,0.00048640225,0.00011781489,0.00031549743],"domain_scores_gemma":[0.9991782,0.00016761462,0.00012873174,0.00032588444,0.00011039361,0.00008921148],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004061288,0.00018758565,0.00022413277,0.00018039186,0.00009642527,0.000013431779,0.00021061447,0.00029255354,0.00003346547],"category_scores_gemma":[0.00012931744,0.00019845608,0.000107483436,0.00027578304,0.00014106608,0.000006086237,0.0001077503,0.0001487837,0.0000336924],"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":[0.0002730648,0.00013054375,0.17462113,0.0000028949073,0.00008323563,0.0000035917617,0.000024234168,0.77548504,0.047329944,0.00050530967,0.0003745122,0.0011665231],"study_design_scores_gemma":[0.0010069605,0.0001368982,0.86779374,0.000015895963,0.000034820307,0.00002296166,0.00001369299,0.117604695,0.010351018,0.00081783306,0.0018353682,0.00036609446],"about_ca_topic_score_codex":0.0000031125187,"about_ca_topic_score_gemma":0.000033177857,"teacher_disagreement_score":0.69317263,"about_ca_system_score_codex":0.000051737326,"about_ca_system_score_gemma":0.00010471132,"threshold_uncertainty_score":0.8092804},"labels":[],"label_agreement":null},{"id":"W4244543028","doi":"10.32920/ryerson.14644161.v1","title":"Accurate parametric sensitivity of stochastic biochemical systems","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Toronto Metropolitan University","funders":"","keywords":"Parametric statistics; Robustness (evolution); Sensitivity (control systems); Computer science; Stochastic modelling; Stochastic process; Systems biology; Parametric model; Key (lock); Biological system; Statistical physics; Mathematical optimization; Mathematics; Bioinformatics; Biology; Physics; Engineering; Statistics","score_opus":0.015511148097744685,"score_gpt":0.2535872038718419,"score_spread":0.23807605577409724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244543028","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":[0.83796287,0.0055936407,0.155675,0.000018795385,0.00035720435,0.00022070864,0.000025953575,0.000015585814,0.0001302865],"genre_scores_gemma":[0.9977821,0.0001232194,0.00061368576,0.000020980187,0.0003135027,0.000023330042,0.00073255145,0.00003564871,0.00035494388],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9978365,0.0003196758,0.00048516324,0.0007981028,0.00027658127,0.00028400603],"domain_scores_gemma":[0.99795055,0.000054130367,0.00034710864,0.0011425873,0.0003792833,0.00012635012],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004883065,0.00033627747,0.00064589735,0.00013774424,0.000027902488,0.00005213504,0.00022089835,0.000698594,0.000018801413],"category_scores_gemma":[0.0002882997,0.00033185957,0.0004485812,0.00031766674,0.00010600729,0.0000010943152,0.0010662234,0.00025558227,0.000003970034],"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":[0.000030801326,0.00012875484,0.00037192658,0.00031877554,0.0010234974,0.000014840259,0.000011237628,0.5299911,0.4659142,0.000021616792,0.0019796614,0.00019359162],"study_design_scores_gemma":[0.00070061494,0.0001542631,0.0025091744,0.00039655328,0.001295564,0.00014274735,0.00040004475,0.36100224,0.6312282,0.00004628293,0.00031032058,0.0018139964],"about_ca_topic_score_codex":0.00015185733,"about_ca_topic_score_gemma":0.00002427191,"teacher_disagreement_score":0.16898888,"about_ca_system_score_codex":0.00003005322,"about_ca_system_score_gemma":0.00027655295,"threshold_uncertainty_score":0.99991333},"labels":[],"label_agreement":null},{"id":"W4245522993","doi":"10.1007/978-3-030-64533-5_1","title":"Introduction","year":2020,"lang":"en","type":"book-chapter","venue":"IFSR international series on systems science and engineering","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; McGill University","funders":"","keywords":"Nonlinear system; Population; Computer science; Hodgkin–Huxley model; Action (physics); Formalism (music); Dynamical systems theory; Dynamics (music); Artificial intelligence; Statistical physics; Physics; Neuroscience; Biology","score_opus":0.006173149593005038,"score_gpt":0.1900357124052665,"score_spread":0.18386256281226146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245522993","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06542945,0.01241368,0.0069098524,0.015639784,0.035156526,0.0018202241,0.0002976583,0.0005167211,0.8618161],"genre_scores_gemma":[0.7808632,0.00067854644,0.00024474956,0.00014569383,0.009348873,0.000020642023,0.00015022092,0.00006881938,0.20847923],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988963,0.0000024592346,0.00016643966,0.00042588962,0.00039310532,0.00011581065],"domain_scores_gemma":[0.99947387,0.0000027409344,0.00007294507,0.0001871085,0.00017948735,0.00008385094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016212794,0.00016491555,0.00013913518,0.00012034737,0.00006249076,0.00009926716,0.00023095596,0.00010011169,0.000016728716],"category_scores_gemma":[0.00004857922,0.00016543952,0.000046180452,0.000045419136,0.00010195748,0.00001234205,0.000107105225,0.000090337184,0.000024072202],"study_design_candidate":"not_applicable","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":[0.00012823842,0.000016034583,0.00007414349,0.00018606812,0.00078581285,0.000027715789,0.00009897827,0.10495317,0.4889734,0.36074895,0.04018009,0.003827399],"study_design_scores_gemma":[0.00005156085,0.00008587989,0.00004363985,0.000041967258,0.000014355712,0.000050800998,0.000013887163,0.0021399003,0.002939764,0.000029416939,0.9943809,0.00020793242],"about_ca_topic_score_codex":0.0000024495096,"about_ca_topic_score_gemma":0.0000012728941,"teacher_disagreement_score":0.9542008,"about_ca_system_score_codex":0.000059868456,"about_ca_system_score_gemma":0.000050861676,"threshold_uncertainty_score":0.6746428},"labels":[],"label_agreement":null},{"id":"W4245597395","doi":"10.32920/ryerson.14644161","title":"Accurate parametric sensitivity of stochastic biochemical systems","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Toronto Metropolitan University","funders":"","keywords":"Parametric statistics; Robustness (evolution); Sensitivity (control systems); Computer science; Stochastic modelling; Systems biology; Stochastic process; Parametric model; Key (lock); Biological system; Statistical physics; Mathematical optimization; Mathematics; Bioinformatics; Biology; Engineering; Physics; Statistics","score_opus":0.015511148097744685,"score_gpt":0.2535872038718419,"score_spread":0.23807605577409724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245597395","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":[0.83796287,0.0055936407,0.155675,0.000018795385,0.00035720435,0.00022070864,0.000025953575,0.000015585814,0.0001302865],"genre_scores_gemma":[0.9977821,0.0001232194,0.00061368576,0.000020980187,0.0003135027,0.000023330042,0.00073255145,0.00003564871,0.00035494388],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9978365,0.0003196758,0.00048516324,0.0007981028,0.00027658127,0.00028400603],"domain_scores_gemma":[0.99795055,0.000054130367,0.00034710864,0.0011425873,0.0003792833,0.00012635012],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004883065,0.00033627747,0.00064589735,0.00013774424,0.000027902488,0.00005213504,0.00022089835,0.000698594,0.000018801413],"category_scores_gemma":[0.0002882997,0.00033185957,0.0004485812,0.00031766674,0.00010600729,0.0000010943152,0.0010662234,0.00025558227,0.000003970034],"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":[0.000030801326,0.00012875484,0.00037192658,0.00031877554,0.0010234974,0.000014840259,0.000011237628,0.5299911,0.4659142,0.000021616792,0.0019796614,0.00019359162],"study_design_scores_gemma":[0.00070061494,0.0001542631,0.0025091744,0.00039655328,0.001295564,0.00014274735,0.00040004475,0.36100224,0.6312282,0.00004628293,0.00031032058,0.0018139964],"about_ca_topic_score_codex":0.00015185733,"about_ca_topic_score_gemma":0.00002427191,"teacher_disagreement_score":0.16898888,"about_ca_system_score_codex":0.00003005322,"about_ca_system_score_gemma":0.00027655295,"threshold_uncertainty_score":0.99991333},"labels":[],"label_agreement":null},{"id":"W4247361554","doi":"10.1093/nar/gkv1181","title":"A predictive modeling approach for cell line-specific long-range regulatory interactions","year":2015,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"U.S. National Library of Medicine","keywords":"Biology; Computational biology; Range (aeronautics); Genetics","score_opus":0.08901807580154224,"score_gpt":0.33535725400248995,"score_spread":0.2463391782009477,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247361554","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":[0.75427973,0.0028975783,0.23585887,0.000112707414,0.00016939544,0.0007336129,0.000031407715,0.000039805203,0.005876855],"genre_scores_gemma":[0.9870541,0.0001370125,0.007247745,0.000026680893,0.0011764194,0.00022649713,0.00024796018,0.00007291606,0.0038106318],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99758583,0.00023800836,0.0002870239,0.0007003808,0.000586794,0.00060194987],"domain_scores_gemma":[0.99778014,0.000029942537,0.000056293768,0.0008387813,0.0009666697,0.00032819016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013738003,0.00019637491,0.00022061702,0.00021990592,0.00026838353,0.00006883931,0.0004656402,0.00023270742,0.000021498889],"category_scores_gemma":[0.00010343948,0.00019447113,0.00020987832,0.00039730663,0.00017536136,0.000013215031,0.00029698835,0.00034287493,0.000031823856],"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":[0.0037848474,0.0019892056,0.011950959,0.00029849028,0.000955012,0.000016328497,0.0022022808,0.4588025,0.29459643,0.0003206538,0.21587928,0.009204017],"study_design_scores_gemma":[0.002174945,0.001112246,0.0003991163,0.00002551663,0.000074312506,0.000015951407,0.002646837,0.9055282,0.02882712,0.00039800646,0.05825189,0.00054584217],"about_ca_topic_score_codex":0.000012608683,"about_ca_topic_score_gemma":0.000012420087,"teacher_disagreement_score":0.44672573,"about_ca_system_score_codex":0.00013996797,"about_ca_system_score_gemma":0.00023125131,"threshold_uncertainty_score":0.7930302},"labels":[],"label_agreement":null},{"id":"W4247506026","doi":"10.1515/iupac.79.2094","title":"Systems Biology","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Glossary; Chemical nomenclature; Computer science; Toxicology; Chemistry; Biology; Philosophy; Linguistics","score_opus":0.008904584051264328,"score_gpt":0.3594597942768659,"score_spread":0.3505552102256016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247506026","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007208253,0.009264237,0.0006163188,0.00010204164,0.0009989231,0.00021125967,0.98803747,0.000020049658,0.000028870098],"genre_scores_gemma":[0.0005866121,0.003078791,0.000019073188,0.00011983748,0.0032949867,0.000024714072,0.9918238,0.00005153989,0.0010006562],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976171,0.0002036668,0.00048639084,0.00080122345,0.00038613318,0.00050544407],"domain_scores_gemma":[0.99759686,0.000017186014,0.00032510704,0.0014445678,0.00043545393,0.00018085248],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00046742792,0.00047924148,0.00064800837,0.0001547299,0.00009019369,0.00003674822,0.0005860146,0.0008974039,0.00038632905],"category_scores_gemma":[0.00018477795,0.00036757905,0.00031334933,0.00013676548,0.00018671212,0.0000016092764,0.0003103264,0.00020090824,0.0000038046458],"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":[0.000065567554,0.000059262024,0.00003907632,0.000058614103,0.00047555345,0.000009184455,5.353498e-7,0.000034516594,0.0018003026,0.0000058944825,0.99672854,0.00072296127],"study_design_scores_gemma":[0.00046925823,0.00026621678,0.000008905382,0.000082136714,0.00020632346,0.000022518114,0.0000061861483,0.000007809201,0.00024557483,0.000020668353,0.99820364,0.00046077464],"about_ca_topic_score_codex":0.00006751354,"about_ca_topic_score_gemma":0.00031164143,"teacher_disagreement_score":0.0061854464,"about_ca_system_score_codex":0.00011515848,"about_ca_system_score_gemma":0.00057206803,"threshold_uncertainty_score":0.99987763},"labels":[],"label_agreement":null},{"id":"W4247911373","doi":"10.32920/ryerson.14663355.v1","title":"Numerical studies of Implicit Tau Leaping methods for stochastic biochemical systems","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Toronto Metropolitan University","funders":"","keywords":"Randomness; Computer science; Population; Statistical physics; Key (lock); Applied mathematics; Mathematical optimization; Algorithm; Mathematics; Statistics; Physics","score_opus":0.04412917166856525,"score_gpt":0.38147800565509166,"score_spread":0.33734883398652643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247911373","genre_codex":"methods","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":[0.13012819,0.055861056,0.81284994,0.00005885241,0.0005328632,0.00049229735,0.000017559483,0.000018206129,0.000041042167],"genre_scores_gemma":[0.9193596,0.0003692024,0.07855339,0.00004589776,0.0005849697,0.00028549918,0.00040904252,0.000059910275,0.0003324517],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9976714,0.00022906005,0.000683603,0.00091304985,0.0001525251,0.00035031058],"domain_scores_gemma":[0.9978977,0.00012505385,0.00036672287,0.00091346924,0.0005922911,0.000104795006],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005949408,0.0003829303,0.0010598436,0.00007889463,0.000056731576,0.000034238914,0.00036537444,0.00055992714,0.0000071541795],"category_scores_gemma":[0.0004472789,0.00035547357,0.00068799267,0.00013714416,0.00012619652,0.0000010774461,0.0009494852,0.00018420526,5.536997e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000053393054,0.000080839694,0.000058929672,0.0012294375,0.0039986656,8.529552e-7,0.000073059695,0.1220659,0.86713475,0.00009898687,0.0031479553,0.0020572213],"study_design_scores_gemma":[0.00079241453,0.00032108228,0.00008585631,0.0005708537,0.0018909258,0.00004079869,0.0020657033,0.07256015,0.91799456,0.00040776198,0.0018667988,0.0014030983],"about_ca_topic_score_codex":0.000034208595,"about_ca_topic_score_gemma":0.0000027674378,"teacher_disagreement_score":0.7892315,"about_ca_system_score_codex":0.000049189886,"about_ca_system_score_gemma":0.00020811547,"threshold_uncertainty_score":0.99988973},"labels":[],"label_agreement":null},{"id":"W4248985427","doi":"10.32920/ryerson.14657604","title":"Accurate Stochastic Simulation Methods for Homogeneous Biochemical Networks","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Toronto Metropolitan University","funders":"","keywords":"Master equation; Stochastic simulation; Representation (politics); Homogeneous; Stochastic process; Computer science; Stochastic modelling; Continuous-time stochastic process; Applied mathematics; Statistical physics; Mathematics; Mathematical optimization; Statistics; Physics","score_opus":0.02425746526527309,"score_gpt":0.3511273006973368,"score_spread":0.32686983543206366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4248985427","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":[0.0745599,0.008339853,0.91586953,0.000038805636,0.00052919314,0.00055921345,0.000016320877,0.000037081638,0.00005009523],"genre_scores_gemma":[0.88225454,0.00013911293,0.112254426,0.00016513433,0.0011974174,0.00018869394,0.003084872,0.00008491692,0.0006308815],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975477,0.00022553382,0.0005049173,0.0011462021,0.00012774157,0.00044794127],"domain_scores_gemma":[0.9979194,0.0001233009,0.00026753874,0.0011071708,0.00041730813,0.00016531571],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004617409,0.00045990894,0.0005429246,0.000072245915,0.000099048215,0.000118234944,0.00040137442,0.0010644587,0.000054475768],"category_scores_gemma":[0.00026762503,0.00047444977,0.00071653374,0.0001445356,0.000069183036,0.0000016480014,0.00095073757,0.00025961048,0.0000015613755],"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":[0.000053896314,0.00003992879,0.000011449372,0.000045465844,0.00053667865,0.0000010186864,0.000008267864,0.94875914,0.0425098,0.000005480148,0.000803532,0.0072253165],"study_design_scores_gemma":[0.00027978237,0.000057900903,0.000036848454,0.00003062843,0.00045167893,0.0000073155015,0.000022546275,0.9602994,0.036251232,0.00014361698,0.0018446036,0.0005744745],"about_ca_topic_score_codex":0.0000073216897,"about_ca_topic_score_gemma":0.000013804807,"teacher_disagreement_score":0.8076947,"about_ca_system_score_codex":0.000044537937,"about_ca_system_score_gemma":0.0002146282,"threshold_uncertainty_score":0.9997707},"labels":[],"label_agreement":null},{"id":"W4249051267","doi":"10.32920/ryerson.14648274.v1","title":"An Efficient Tau-Leaping Simulation Method for Stochastic Biochemical Kinetics","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Toronto Metropolitan University","funders":"","keywords":"Stochastic simulation; Computer science; Stochastic modelling; Stochastic process; Statistical physics; Mathematical optimization; Biological system; Mathematics; Biology; Physics; Statistics","score_opus":0.018378743472871835,"score_gpt":0.3234674294380264,"score_spread":0.3050886859651546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4249051267","genre_codex":"methods","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":[0.3115705,0.0008428776,0.6869119,0.000038243714,0.00020341571,0.00036277296,0.000020211128,0.000024968673,0.000025097323],"genre_scores_gemma":[0.8502246,0.000010255314,0.14613597,0.00011814873,0.0007148596,0.000076212986,0.0025350591,0.00006333449,0.00012154928],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977082,0.00014661807,0.00044327276,0.001112818,0.00022656684,0.0003625346],"domain_scores_gemma":[0.9980573,0.00005744949,0.00021017136,0.001093405,0.00041015144,0.00017150317],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00035006704,0.000378676,0.00042374537,0.00008962773,0.000071902025,0.000100027086,0.00035020057,0.000717693,0.000035821395],"category_scores_gemma":[0.00016134807,0.0003987037,0.0004445503,0.00011890251,0.000046574492,0.0000010793103,0.0005009914,0.00018760377,0.0000015220513],"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":[0.000025120278,0.00009380062,0.0000069676094,0.000052754647,0.00015407077,4.2475233e-7,0.000020527,0.67802846,0.32040468,0.000010142218,0.00013763802,0.0010654418],"study_design_scores_gemma":[0.00025918888,0.000106104606,0.00005568827,0.000033321863,0.00029133647,0.0000025579059,0.00007357497,0.8345865,0.16382542,0.00005298116,0.0002937925,0.00041951344],"about_ca_topic_score_codex":0.000009907833,"about_ca_topic_score_gemma":0.0000143546,"teacher_disagreement_score":0.54077595,"about_ca_system_score_codex":0.000050767885,"about_ca_system_score_gemma":0.00014455628,"threshold_uncertainty_score":0.99984646},"labels":[],"label_agreement":null},{"id":"W4249253983","doi":"10.32920/14657436","title":"Adaptive time-stepping using control theory for the Chemical Langevin Equation","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"University of Waterloo; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Langevin equation; Stochastic differential equation; Multiplicative function; Applied mathematics; Multiplicative noise; Constant (computer programming); Statistical physics; Computer science; Mathematics; Mathematical optimization; Physics; Mathematical analysis","score_opus":0.027169180032900243,"score_gpt":0.25901355153111194,"score_spread":0.2318443714982117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4249253983","genre_codex":"methods","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":[0.13799007,0.005994839,0.8546345,0.00015125604,0.00016773814,0.000658553,0.000031366828,0.00001785714,0.0003537668],"genre_scores_gemma":[0.9912066,0.000053054417,0.006081155,0.00031202077,0.0008899167,0.00009853539,0.00045522326,0.000038965667,0.0008645244],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987452,0.00017058158,0.00024052375,0.0004923603,0.0001320294,0.00021931778],"domain_scores_gemma":[0.9988601,0.0001217992,0.0001730312,0.0005914315,0.00020923573,0.000044374076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000564918,0.0002227211,0.00028035618,0.00002570214,0.000088604495,0.000059174723,0.00026572813,0.00037060812,0.00007093396],"category_scores_gemma":[0.00013012717,0.00017025587,0.00040085314,0.000053530468,0.00006366709,0.0000013955723,0.000352224,0.00015059714,0.0000033121087],"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":[0.00019363595,0.000040547333,0.00007045353,0.000047913323,0.0021061762,0.0000011666392,0.000056417684,0.112001546,0.8788707,0.00025145247,0.0010188186,0.0053411652],"study_design_scores_gemma":[0.0008629601,0.000054649776,0.00007393596,0.0000894917,0.0015734917,0.000008160729,0.0004022332,0.78618556,0.20768283,0.000807539,0.0016364461,0.00062269514],"about_ca_topic_score_codex":0.000014891242,"about_ca_topic_score_gemma":0.000010470155,"teacher_disagreement_score":0.8532165,"about_ca_system_score_codex":0.00004339711,"about_ca_system_score_gemma":0.00018213785,"threshold_uncertainty_score":0.69428325},"labels":[],"label_agreement":null},{"id":"W4249696923","doi":"10.32920/14657436.v1","title":"Adaptive time-stepping using control theory for the Chemical Langevin Equation","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"University of Waterloo; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Langevin equation; Stochastic differential equation; Multiplicative function; Statistical physics; Applied mathematics; Multiplicative noise; Computer science; Constant (computer programming); Langevin dynamics; Mathematics; Mathematical optimization; Physics; Mathematical analysis","score_opus":0.027169180032900243,"score_gpt":0.25901355153111194,"score_spread":0.2318443714982117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4249696923","genre_codex":"methods","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":[0.13799007,0.005994839,0.8546345,0.00015125604,0.00016773814,0.000658553,0.000031366828,0.00001785714,0.0003537668],"genre_scores_gemma":[0.9912066,0.000053054417,0.006081155,0.00031202077,0.0008899167,0.00009853539,0.00045522326,0.000038965667,0.0008645244],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987452,0.00017058158,0.00024052375,0.0004923603,0.0001320294,0.00021931778],"domain_scores_gemma":[0.9988601,0.0001217992,0.0001730312,0.0005914315,0.00020923573,0.000044374076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000564918,0.0002227211,0.00028035618,0.00002570214,0.000088604495,0.000059174723,0.00026572813,0.00037060812,0.00007093396],"category_scores_gemma":[0.00013012717,0.00017025587,0.00040085314,0.000053530468,0.00006366709,0.0000013955723,0.000352224,0.00015059714,0.0000033121087],"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":[0.00019363595,0.000040547333,0.00007045353,0.000047913323,0.0021061762,0.0000011666392,0.000056417684,0.112001546,0.8788707,0.00025145247,0.0010188186,0.0053411652],"study_design_scores_gemma":[0.0008629601,0.000054649776,0.00007393596,0.0000894917,0.0015734917,0.000008160729,0.0004022332,0.78618556,0.20768283,0.000807539,0.0016364461,0.00062269514],"about_ca_topic_score_codex":0.000014891242,"about_ca_topic_score_gemma":0.000010470155,"teacher_disagreement_score":0.8532165,"about_ca_system_score_codex":0.00004339711,"about_ca_system_score_gemma":0.00018213785,"threshold_uncertainty_score":0.69428325},"labels":[],"label_agreement":null},{"id":"W4249872335","doi":"10.32920/ryerson.14644779","title":"Adaptive time-stepping in the numerical solution of the reaction-diffusion master equation","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Time stepping; Master equation; Computer science; Reaction–diffusion system; Diffusion; Computer simulation; Stochastic simulation; Applied mathematics; Scheme (mathematics); Numerical analysis; Mathematical optimization; Statistical physics; Algorithm; Mathematics; Simulation; Mathematical analysis; Physics","score_opus":0.024568505154887635,"score_gpt":0.23504387890389053,"score_spread":0.21047537374900288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4249872335","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":[0.96093273,0.0005080768,0.03596977,0.0005413418,0.00019077928,0.0003397526,0.00000335165,0.0000050234544,0.0015091541],"genre_scores_gemma":[0.99835056,0.000058028363,0.0005594197,0.00012549276,0.0001634052,0.000025954938,0.00016867684,0.0000117245445,0.0005367302],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985775,0.00040232524,0.00029411027,0.00035040907,0.00024130296,0.00013436403],"domain_scores_gemma":[0.99895793,0.00001989906,0.00023706055,0.0006608107,0.00010769613,0.000016574384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036370388,0.00014975305,0.00018385438,0.00003846435,0.00005611934,0.0000192294,0.0002774641,0.0002835633,0.000034232373],"category_scores_gemma":[0.000045350986,0.00009456543,0.00024802992,0.0001752239,0.000044955803,0.0000021210187,0.00053402747,0.00022363084,0.0000034493846],"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":[0.00005875134,0.00015067529,0.00304182,0.000034603614,0.0002114748,0.0000011212895,0.00036874038,0.02698382,0.96457034,0.000041452935,0.00084113283,0.0036960396],"study_design_scores_gemma":[0.0014229877,0.00032577827,0.21052778,0.00067027967,0.0009770623,0.000043136348,0.003913916,0.49464107,0.28129908,0.0008225097,0.0039023717,0.0014540051],"about_ca_topic_score_codex":0.00015610804,"about_ca_topic_score_gemma":0.00013177523,"teacher_disagreement_score":0.6832713,"about_ca_system_score_codex":0.00004018776,"about_ca_system_score_gemma":0.00011178949,"threshold_uncertainty_score":0.38562664},"labels":[],"label_agreement":null},{"id":"W4250015208","doi":"10.1137/1.9781611974713.ch1","title":"CHAPTER 1: Stochastic Processes","year":2018,"lang":"en","type":"book-chapter","venue":"Society for Industrial and Applied Mathematics eBooks","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"McGill University","funders":"","keywords":"Predictability; Stochastic process; Probability theory; Computer science; State (computer science); Mathematical economics; Mathematics; Algorithm","score_opus":0.03706956541858571,"score_gpt":0.23323325730271915,"score_spread":0.19616369188413343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4250015208","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0194268,0.0029824253,0.05135137,0.00018867792,0.000908878,0.008673473,0.0009910165,0.00026214914,0.9152152],"genre_scores_gemma":[0.037636094,0.00017383955,0.018160941,0.00041885776,0.009972541,0.0004646683,0.0007813847,0.00054576097,0.9318459],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99853384,0.0000016627873,0.00040805433,0.00055620633,0.00020442122,0.00029582772],"domain_scores_gemma":[0.9989326,0.000038681763,0.00035722618,0.0003956413,0.0001513286,0.00012451773],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022018961,0.00046436497,0.00051033753,0.000029300154,0.00020955373,0.0000525666,0.00020134199,0.000995768,0.000057259633],"category_scores_gemma":[0.000020968379,0.0004264024,0.00047551177,0.00001247321,0.00034020332,0.0000011676173,0.00018173138,0.00019963698,0.000011375614],"study_design_candidate":"theoretical_or_conceptual","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":[0.00076986034,0.0002599952,0.0000014343897,0.0049296464,0.014989529,0.000002363069,0.0045793625,0.000192349,0.0530682,0.686992,0.17974627,0.05446903],"study_design_scores_gemma":[0.004086759,0.00084830384,1.0650343e-7,0.0006168039,0.0035446058,0.00003155957,0.0006447743,0.00028299805,0.024101539,0.2799093,0.6831593,0.0027739622],"about_ca_topic_score_codex":2.889913e-7,"about_ca_topic_score_gemma":0.0000041137196,"teacher_disagreement_score":0.503413,"about_ca_system_score_codex":0.000015924717,"about_ca_system_score_gemma":0.00014188324,"threshold_uncertainty_score":0.9998188},"labels":[],"label_agreement":null},{"id":"W4250494250","doi":"10.1038/sj.cr.7310129","title":"Gene Regulation","year":2006,"lang":"en","type":"article","venue":"Cell Research","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Biology; Computational biology; Gene; Genetics","score_opus":0.023527165927810675,"score_gpt":0.303233269060006,"score_spread":0.27970610313219535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4250494250","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":[0.9725421,0.0015356669,0.00071321,0.000078465266,0.000031771535,0.00009567994,0.000001428282,0.000008304887,0.024993375],"genre_scores_gemma":[0.97029614,0.00005932821,0.0005596722,0.000011879789,0.0005800958,0.000011782093,0.00015027322,0.00001701219,0.028313812],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988584,0.00013384238,0.00011698786,0.00028138692,0.00030180867,0.0003075685],"domain_scores_gemma":[0.99930453,0.0000110915325,0.000022259172,0.0004216812,0.00018554565,0.00005488692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055899215,0.00006846122,0.000065672735,0.00008736693,0.00012791045,0.000026891705,0.00016418859,0.000104446655,0.00010115688],"category_scores_gemma":[0.000013630463,0.00006828662,0.00006449329,0.0002645557,0.0000851317,0.000001320256,0.000105919244,0.00008357027,0.000121550176],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001342229,0.00003331949,0.0026063698,0.0000052128,0.0000072958746,0.0000016870268,0.0000026786438,0.001558186,0.9607472,0.000060213006,0.033714164,0.0012502731],"study_design_scores_gemma":[0.00015352771,0.000049696235,0.010497957,0.0000013371583,0.000004804436,0.0000019097236,0.000009031133,0.00044251798,0.90023094,0.0005206613,0.088005416,0.00008221984],"about_ca_topic_score_codex":0.000043544067,"about_ca_topic_score_gemma":0.000038137783,"teacher_disagreement_score":0.060516253,"about_ca_system_score_codex":0.00002113545,"about_ca_system_score_gemma":0.000058357004,"threshold_uncertainty_score":0.27846476},"labels":[],"label_agreement":null},{"id":"W4250970967","doi":"10.1515/jib-2015-258","title":"Specifications of Standards in Systems and Synthetic Biology","year":2015,"lang":"en","type":"article","venue":"Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"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":"Computer science; Community standards; Open standard; Documentation; Data science; Modelling biological systems; Engineering management; Interoperability; World Wide Web; Systems biology; Engineering","score_opus":0.028664356998764476,"score_gpt":0.2932728727995226,"score_spread":0.2646085158007581,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4250970967","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":[0.7655386,0.02393058,0.16752405,0.0004584945,0.0019897826,0.0018786241,0.00070310035,0.000053273834,0.03792351],"genre_scores_gemma":[0.96742225,0.0016493158,0.030289877,0.00015042689,0.00019294849,0.000019366626,0.00016471291,0.000029143739,0.0000819774],"study_design_codex":"qualitative","study_design_gemma":"not_applicable","domain_scores_codex":[0.9953299,0.00013525835,0.0031314285,0.00014180635,0.00079729833,0.00046429658],"domain_scores_gemma":[0.9941052,0.00010448235,0.0025332866,0.00052286417,0.0023316382,0.00040253316],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0023764467,0.00047715232,0.0009773349,0.00080010056,0.000068337264,0.00010453036,0.00061734323,0.0003466038,0.000011544666],"category_scores_gemma":[0.0010551627,0.00033398918,0.00021821744,0.0008409961,0.00055427785,0.0002672277,0.00023305838,0.00038159898,0.000010599751],"study_design_candidate":"not_applicable","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":[0.007783639,0.0025810832,0.11676663,0.0074917935,0.02104885,0.00008089119,0.31395522,0.05045597,0.02480689,0.06691102,0.16306663,0.2250514],"study_design_scores_gemma":[0.0150971515,0.010004677,0.004569225,0.0023044134,0.0016624243,0.0021811202,0.19925413,0.116144635,0.046647605,0.0010414526,0.5976958,0.003397323],"about_ca_topic_score_codex":0.000023407028,"about_ca_topic_score_gemma":0.000026806625,"teacher_disagreement_score":0.43462923,"about_ca_system_score_codex":0.00015298177,"about_ca_system_score_gemma":0.0011340589,"threshold_uncertainty_score":0.9999112},"labels":[],"label_agreement":null},{"id":"W4251023000","doi":"10.4056/sigs.2034671","title":"Meeting report from the first meetings of the Computational Modeling in Biology Network (COMBINE)","year":2011,"lang":"en","type":"article","venue":"Standards in Genomic Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"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":"National Institute of General Medical Sciences; Biotechnology and Biological Sciences Research Council; Directorate for Biological Sciences; National Institutes of Health; Memorial Sloan-Kettering Cancer Center","keywords":"SBML; Interoperability; Computer science; Field (mathematics); Software; Data science; World Wide Web; Markup language; XML","score_opus":0.028707958800734464,"score_gpt":0.2742888446533571,"score_spread":0.24558088585262267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251023000","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":[0.9952193,0.0016720631,0.001313897,0.00015690034,0.00017574182,0.00010046144,0.000015053237,0.000002526231,0.0013440873],"genre_scores_gemma":[0.9971547,0.00004348722,0.0025779537,0.000092001945,0.00010694127,0.0000054666148,0.0000073332767,0.000005701123,0.0000064017927],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99871206,0.000120970384,0.0003986742,0.00033962025,0.00020204445,0.0002266244],"domain_scores_gemma":[0.9993964,0.000047849328,0.00019402216,0.0002673258,0.00007721847,0.000017225964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002425514,0.00009532539,0.0001521747,0.00003165357,0.00017874093,0.000011722957,0.00055494055,0.00006707785,0.000013237269],"category_scores_gemma":[0.00015947453,0.000060313152,0.00007867418,0.00035347347,0.00041255215,0.0000031289399,0.00025670897,0.00007229138,2.3695299e-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":[0.000018038038,0.000012696207,0.4688836,0.0000015376203,0.000020306088,0.0000010833621,0.00035508614,0.52850336,0.0016490221,0.00013936884,0.00017656932,0.00023931704],"study_design_scores_gemma":[0.0015902397,0.00026416892,0.37955046,0.00033584886,0.00009934588,0.00003774111,0.0025192576,0.5141395,0.009592184,0.08505824,0.0059619895,0.00085105276],"about_ca_topic_score_codex":0.00093251176,"about_ca_topic_score_gemma":0.0033872155,"teacher_disagreement_score":0.08933314,"about_ca_system_score_codex":0.000040373823,"about_ca_system_score_gemma":0.00027139048,"threshold_uncertainty_score":0.2459499},"labels":[],"label_agreement":null},{"id":"W4251854178","doi":"10.1007/s11012-007-9104-4","title":"Convex fung-type potentials for biological tissues","year":2007,"lang":"en","type":"article","venue":"Meccanica","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Type (biology); Regular polygon; Computer science; Mathematics; Mathematical economics; Applied mathematics; Geometry; Biology; Ecology","score_opus":0.021560556359754006,"score_gpt":0.2859537696728981,"score_spread":0.2643932133131441,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251854178","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":[0.97524536,0.0030048233,0.019866688,0.00024139116,0.00033714648,0.0002643028,0.000010966245,0.000031124862,0.0009982234],"genre_scores_gemma":[0.99494016,0.00018077789,0.0025413225,0.00028435537,0.0005995414,0.000008160858,0.00015655806,0.000019009578,0.0012701004],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99899393,0.000035301626,0.00022287315,0.00033923856,0.00008659579,0.00032205103],"domain_scores_gemma":[0.9993546,0.000023374821,0.000071726936,0.00033401052,0.00011426712,0.000102018916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047072658,0.00013050108,0.00018984558,0.00002836201,0.00007076758,0.000013494447,0.00019287289,0.00019802283,0.00012294314],"category_scores_gemma":[0.00009441338,0.0001128068,0.00014939517,0.00010536184,0.00006203574,0.0000011596659,0.00007734906,0.00004023483,0.00003344309],"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":[0.00016722572,0.00004588214,0.0031722283,0.0000075383014,0.00017102886,0.000003501234,0.000012525659,0.000042681182,0.97908443,0.00020839968,0.011173352,0.0059112264],"study_design_scores_gemma":[0.00040593237,0.00047730116,0.005645972,0.000004222006,0.00007118066,0.000010682458,0.00005112865,0.00006569845,0.48592523,0.00026789206,0.5068156,0.00025916012],"about_ca_topic_score_codex":0.000005123486,"about_ca_topic_score_gemma":0.00002894049,"teacher_disagreement_score":0.49564224,"about_ca_system_score_codex":0.000010116402,"about_ca_system_score_gemma":0.000032281645,"threshold_uncertainty_score":0.4600128},"labels":[],"label_agreement":null},{"id":"W4252154226","doi":"10.1109/csb.2004.1332458","title":"State-space model for gene regulatory networks with time delays","year":2004,"lang":"en","type":"article","venue":"Proceedings. 2004 IEEE Computational Systems Bioinformatics Conference, 2004. CSB 2004.","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Saskatchewan","funders":"","keywords":"Expression (computer science); Gene regulatory network; Computer science; Dynamic Bayesian network; Principal component analysis; Bayesian network; State space; State-space representation; Probabilistic logic; State (computer science); Component (thermodynamics); Bayesian information criterion; State variable; Data mining; Gene; Gene expression; Mathematics; Artificial intelligence; Algorithm; Statistics; Genetics; Biology","score_opus":0.011312054212305299,"score_gpt":0.21294949186901718,"score_spread":0.20163743765671188,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252154226","genre_codex":"methods","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":[0.10046715,0.0013323509,0.8953412,0.0000825032,0.00020536907,0.0013812154,0.00015652498,0.000129347,0.00090431934],"genre_scores_gemma":[0.9285922,0.000051961146,0.06710542,0.00018968749,0.00046885206,0.00022533932,0.0008822373,0.00011403262,0.002370288],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9963727,0.000020309593,0.0011573567,0.00071176735,0.00079290953,0.0009449656],"domain_scores_gemma":[0.99641204,0.000024717883,0.00085068995,0.00039541224,0.0018950085,0.0004221079],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00058240147,0.00071862363,0.0007128333,0.00028565575,0.00042479977,0.00034996215,0.0005708719,0.00043712478,0.000008527162],"category_scores_gemma":[0.00003227005,0.00066988135,0.0002629427,0.000533465,0.00025165614,0.00009409787,0.00008746762,0.00024401263,0.000055531687],"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":[0.00016577574,0.000094997966,0.00015468756,0.00019168892,0.00038038072,0.0000015906244,0.00027226418,0.98737746,0.0019640238,0.0010432063,0.0080647785,0.00028914018],"study_design_scores_gemma":[0.002242263,0.0003763105,0.00009477994,0.00020809236,0.00016571967,0.00011573553,0.0001406856,0.99174035,0.0023118944,0.0009374403,0.00075740874,0.0009093369],"about_ca_topic_score_codex":0.000018996161,"about_ca_topic_score_gemma":0.000020337104,"teacher_disagreement_score":0.8282358,"about_ca_system_score_codex":0.00028452167,"about_ca_system_score_gemma":0.0009704525,"threshold_uncertainty_score":0.99957526},"labels":[],"label_agreement":null},{"id":"W4252345943","doi":"10.1515/iupac.68.0155","title":"Reaction Dynamics","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Ottawa","funders":"","keywords":"Glossary; Terminology; Field (mathematics); Computer science; Dynamics (music); Linguistics; Philosophy; Sociology; Mathematics; Pedagogy","score_opus":0.0063447887283292,"score_gpt":0.3413813164770759,"score_spread":0.3350365277487467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252345943","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016041292,0.0009849572,0.0005372837,0.00020051331,0.0004924287,0.00013255353,0.99599296,0.000017943808,0.000037236892],"genre_scores_gemma":[0.0003067077,0.0023674963,0.000035867502,0.000124353,0.0019261984,0.000010043476,0.99387926,0.000048072143,0.0013019886],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980554,0.00008711213,0.00035056102,0.00062214833,0.0005356631,0.00034910018],"domain_scores_gemma":[0.99803793,0.000009221757,0.0002730876,0.0011744647,0.00036805545,0.00013721541],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00032616415,0.00037938345,0.00039742567,0.00012366708,0.00008582309,0.00002647395,0.00035809536,0.0006474123,0.00025928023],"category_scores_gemma":[0.00015169487,0.00031733722,0.00028957735,0.00013063847,0.000103032966,0.0000024622889,0.00019610966,0.00020706895,0.0000022559482],"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":[0.000092906645,0.000068770736,0.000021282167,0.000031299707,0.00028395333,0.000008728531,4.443102e-7,0.0000109549455,0.0014038208,0.0000018208808,0.99444854,0.0036274872],"study_design_scores_gemma":[0.00037330884,0.00016588833,0.000042886957,0.000059001275,0.00022708751,0.00001907317,0.000006939599,0.000024853467,0.0003723525,0.000030104771,0.9982899,0.00038862377],"about_ca_topic_score_codex":0.000047900983,"about_ca_topic_score_gemma":0.0029945413,"teacher_disagreement_score":0.0038413492,"about_ca_system_score_codex":0.00027518827,"about_ca_system_score_gemma":0.00045304024,"threshold_uncertainty_score":0.9999279},"labels":[],"label_agreement":null},{"id":"W4252648860","doi":"10.24908/iqurcp.9168","title":"QGEM 2012: Building a Chimeric Flagellar Scaffold for Enhanced Bioremediation and Biosynthesis","year":2018,"lang":"en","type":"article","venue":"Inquiry Queen s Undergraduate Research Conference Proceedings","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Flagellum; Bioremediation; Synthetic biology; Flagellin; Function (biology); Computational biology; Biochemical engineering; Biotechnology; Chemistry; Biology; Biochemistry; Cell biology; Gene; Engineering; Genetics; Bacteria","score_opus":0.04648230065837174,"score_gpt":0.3410888300325167,"score_spread":0.294606529374145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252648860","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":[0.97338325,0.00041393572,0.021889862,0.0029846167,0.00012835137,0.00069301843,0.000009421095,0.000047267116,0.00045026827],"genre_scores_gemma":[0.99239445,0.0012430057,0.0041322964,0.0000627671,0.0012670846,0.00016684625,0.00003694362,0.00005616749,0.0006404306],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9972285,0.00008203306,0.00035096367,0.0009429136,0.00054164784,0.0008539477],"domain_scores_gemma":[0.9974401,0.000077978315,0.00016439048,0.00029266643,0.0017474298,0.00027743104],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0014845683,0.000292581,0.00030724076,0.00037304717,0.0004954473,0.00025517523,0.00042420038,0.00026839555,0.00001834342],"category_scores_gemma":[0.00054243597,0.00028626164,0.0001139194,0.0006624321,0.0009561918,0.00004430919,0.00032597777,0.00016380011,0.000025298716],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014578566,0.00003738808,0.00055351976,0.000084666586,0.00015037293,3.6306977e-7,0.00031664482,0.000001977334,0.9853206,0.0014325682,0.00460922,0.0073468774],"study_design_scores_gemma":[0.0005070118,0.00071970484,0.0005203885,0.00009013535,0.000062176485,0.0000052135156,0.00062399794,0.0018518538,0.97597444,0.006569511,0.012665966,0.0004096005],"about_ca_topic_score_codex":0.000026270194,"about_ca_topic_score_gemma":0.000028171578,"teacher_disagreement_score":0.019011198,"about_ca_system_score_codex":0.000060322818,"about_ca_system_score_gemma":0.00022404085,"threshold_uncertainty_score":0.99995893},"labels":[],"label_agreement":null},{"id":"W4253203605","doi":"10.1007/978-1-61779-276-2_7","title":"Array-Based Synthetic Genetic Screens to Map Bacterial Pathways and Functional Networks in Escherichia coli","year":2011,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Epistasis; Genetic Fitness; Mutant; Biology; Gene; Phenotype; Genetic screen; Computational biology; Genetics; Function (biology); Mutation; Model organism","score_opus":0.023117125593077218,"score_gpt":0.28227603036319865,"score_spread":0.25915890477012143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4253203605","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4391808,0.0006499313,0.5596422,0.000036470115,0.00018670883,0.00019256031,0.0000044101944,0.000008120952,0.00009884073],"genre_scores_gemma":[0.48524734,0.000026677766,0.51393867,0.00047410233,0.00011346423,0.00008814574,0.00005798775,0.000035620556,0.000017991939],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99679184,0.001354436,0.00044144513,0.00080941804,0.000074749856,0.00052810746],"domain_scores_gemma":[0.9990819,0.00004666529,0.000100176025,0.00055263424,0.000055192195,0.00016341657],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00093815423,0.00030360703,0.00040808474,0.00022945748,0.00004538474,0.000013307794,0.00022653156,0.00044186544,0.00008643403],"category_scores_gemma":[0.00014887609,0.00031491375,0.00012797673,0.00034465294,0.0001825947,0.0000020054463,0.00016395649,0.00018535332,0.0000050551585],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023211152,0.00007413148,0.012784741,0.000008779492,0.000055997887,0.000016875822,0.000027999726,0.00490897,0.97814465,0.00013808561,0.000028062157,0.0035795993],"study_design_scores_gemma":[0.002026276,0.0010681023,0.087477975,0.000047862508,0.0001192703,0.000022258473,0.000065712586,0.0067957975,0.89237475,0.0019290954,0.0069589075,0.0011139815],"about_ca_topic_score_codex":0.00006051325,"about_ca_topic_score_gemma":0.00016874737,"teacher_disagreement_score":0.085769884,"about_ca_system_score_codex":0.000031392807,"about_ca_system_score_gemma":0.00008712348,"threshold_uncertainty_score":0.9999303},"labels":[],"label_agreement":null},{"id":"W4255013158","doi":"10.1007/978-1-4939-7131-2_100738","title":"Network Models","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Psychology","score_opus":0.01598790537803725,"score_gpt":0.21340031553993322,"score_spread":0.19741241016189598,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255013158","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00023889857,0.0037320654,0.0047019096,0.000037948696,0.00020749625,0.0001270423,0.000008455931,0.00002782088,0.99091834],"genre_scores_gemma":[0.0067391936,0.00051238254,0.0015534582,0.0005669265,0.0039566383,0.0000052515115,0.00035454385,0.000100649166,0.98621094],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99872655,0.000011867167,0.00024696576,0.00056016725,0.00016871543,0.00028575308],"domain_scores_gemma":[0.9987887,0.000003436257,0.00013057295,0.0008427052,0.00012781411,0.000106737294],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00011995751,0.0003312595,0.00029235036,0.000036607966,0.00006855969,0.00001918336,0.00027061906,0.00062973425,0.0019784523],"category_scores_gemma":[0.000002241546,0.0003152853,0.00030277605,0.000018779097,0.000113067945,9.754223e-7,0.0002287826,0.000102835234,0.00035429784],"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":[0.000032334392,0.0000072988405,0.0000091743805,0.000011946655,0.0006864558,0.0000048909606,0.0000054668703,0.012525771,0.00056310225,0.03187315,0.95289785,0.0013825343],"study_design_scores_gemma":[0.00010173361,0.000105361185,0.0000017056647,0.00002218804,0.00016839348,0.000008664479,0.0000012461913,0.0007808893,0.00037468417,0.06888854,0.9290851,0.00046148992],"about_ca_topic_score_codex":0.0000017407945,"about_ca_topic_score_gemma":0.000051061197,"teacher_disagreement_score":0.03701539,"about_ca_system_score_codex":0.000014320098,"about_ca_system_score_gemma":0.000071066665,"threshold_uncertainty_score":0.9999299},"labels":[],"label_agreement":null},{"id":"W4255193114","doi":"10.11145/texts.2017.12.163","title":"Collapsing chaos","year":2017,"lang":"en","type":"article","venue":"Texts in Biomathematics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Victoria; McGill University","funders":"Shahjalal University of Science and Technology","keywords":"Lyapunov exponent; Limit (mathematics); Trajectory; Statistical physics; CHAOS (operating system); Lyapunov function; Physics; Phase plane; Control theory (sociology); Function (biology); Plane (geometry); Dynamics (music); Computer science; Mathematics; Chaotic; Biology; Control (management); Nonlinear system; Mathematical analysis; Evolutionary biology; Artificial intelligence; Geometry","score_opus":0.01898363150245349,"score_gpt":0.2874105761786751,"score_spread":0.26842694467622163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255193114","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":[0.99366176,0.00032870407,0.0007639942,0.000118744,0.00010940111,0.00012069085,0.0000027260792,0.00001133075,0.004882627],"genre_scores_gemma":[0.9921873,0.000052993833,0.006269965,0.000037931,0.00014766495,0.000008888881,0.0000073789015,0.000021041562,0.0012668289],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992161,0.000023085759,0.00021514333,0.0002170181,0.00011678769,0.00021189191],"domain_scores_gemma":[0.99872947,0.000008909235,0.00017596947,0.0010018284,0.00003373133,0.00005006626],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025913352,0.00012490177,0.0001767504,0.000052303665,0.00018265123,0.00006599113,0.00040191555,0.00012012424,0.00002218152],"category_scores_gemma":[0.00015551558,0.000118808406,0.00007709536,0.000052759802,0.000112776266,0.000003174877,0.00018721522,0.000033709315,0.000031336327],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000053541233,0.0005437541,0.059752025,0.00034431677,0.00029690244,0.00005598666,0.0006784954,0.00047102285,0.8960367,0.0026691952,0.011779803,0.027318254],"study_design_scores_gemma":[0.0035527986,0.0003434099,0.07756241,0.00044899128,0.00023956092,0.00015394334,0.00044208817,0.014612062,0.8376281,0.029146334,0.03379731,0.0020729918],"about_ca_topic_score_codex":0.0000046742603,"about_ca_topic_score_gemma":0.00006815695,"teacher_disagreement_score":0.0584086,"about_ca_system_score_codex":0.000015041988,"about_ca_system_score_gemma":0.000030356809,"threshold_uncertainty_score":0.4844866},"labels":[],"label_agreement":null},{"id":"W4255284369","doi":"10.1109/wsc.2017.8247871","title":"Optimizations for Neuron Time Warp(NTW) for stochastic reaction-diffusion models of neurons","year":2017,"lang":"en","type":"article","venue":"2017 Winter Simulation Conference (WSC)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Algorithm; Event (particle physics); Discrete event simulation; Neuron; Computation; Stochastic simulation; Simulation; Mathematics; Physics; Neuroscience","score_opus":0.046519925657124025,"score_gpt":0.3037698977328906,"score_spread":0.25724997207576655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255284369","genre_codex":"methods","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":[0.18942362,0.000027237813,0.8090652,0.00020862465,0.00021102489,0.00060105143,0.00009246362,0.000015278443,0.00035546775],"genre_scores_gemma":[0.9947841,0.000013181951,0.0021306637,0.00004177403,0.00021526103,0.00006336344,0.00037425512,0.00003200735,0.002345373],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989072,0.000033912333,0.0003130036,0.00041636368,0.000117813834,0.00021171654],"domain_scores_gemma":[0.9980429,0.00006537094,0.00041915692,0.00084939064,0.0005453306,0.00007785407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012959164,0.00018166882,0.00023338593,0.00007169009,0.00035988467,0.00007317871,0.00035738607,0.00014643454,0.000026213436],"category_scores_gemma":[0.00025189656,0.00018741959,0.00021176827,0.000027715112,0.00009413823,0.000033078824,0.00011202749,0.000049171613,0.0000055765895],"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":[0.00015752151,0.000056514353,0.000090072266,0.000018460274,0.00007056413,1.04665666e-7,0.00004779228,0.89797646,0.09880984,0.00014859006,0.0008502219,0.0017738404],"study_design_scores_gemma":[0.0007930002,0.00020298187,0.0010732489,0.000024769237,0.00012278394,0.0000010844556,0.000010556338,0.99157584,0.0038088956,0.00062744145,0.0015737078,0.00018568017],"about_ca_topic_score_codex":0.000009661808,"about_ca_topic_score_gemma":0.000027374894,"teacher_disagreement_score":0.80693454,"about_ca_system_score_codex":0.0000119802435,"about_ca_system_score_gemma":0.000085478896,"threshold_uncertainty_score":0.7642749},"labels":[],"label_agreement":null},{"id":"W4280502018","doi":"10.48550/arxiv.2205.05622","title":"Computing control invariant sets of nonlinear systems: decomposition and distributed computing","year":2022,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Alberta","funders":"","keywords":"Invariant (physics); Nonlinear system; Computer science; Cascade; Graph; Exploit; Convergence (economics); Algorithm; Mathematical optimization; Control theory (sociology); Theoretical computer science; Mathematics; Control (management); Artificial intelligence; Engineering","score_opus":0.021020048422254058,"score_gpt":0.19672370887372392,"score_spread":0.17570366045146987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280502018","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":[0.8409936,0.0005258216,0.15776917,0.000011162266,0.00015149925,0.00024012811,0.00023393755,0.000019814106,0.000054891476],"genre_scores_gemma":[0.9981514,0.00010189428,0.0003327039,0.000021756541,0.00011260044,3.7628575e-7,0.0012241052,0.000022649438,0.000032506796],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983373,0.00032723008,0.00030570253,0.00071840244,0.000076404336,0.0002349313],"domain_scores_gemma":[0.9986952,0.000043808475,0.0004850037,0.000522749,0.00014956898,0.00010368197],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00034198107,0.000251206,0.0004421044,0.000107791326,0.00017715713,0.000028317303,0.00033028144,0.0002433702,0.000009864454],"category_scores_gemma":[0.000020229883,0.00031504137,0.00019281119,0.0002050867,0.000101543264,0.0000033261574,0.00110778,0.00025797525,9.084862e-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":[0.000078350706,0.00005748497,0.01970545,0.00014485995,0.00051407603,0.0000388069,0.00002361417,0.97530967,0.0036765498,0.00031051735,0.000078113924,0.00006248456],"study_design_scores_gemma":[0.00092129566,0.00010051374,0.0048968284,0.00008478178,0.00043188914,0.000014512501,0.0002356924,0.9921089,0.0004889146,0.00007880416,0.0002852397,0.0003526373],"about_ca_topic_score_codex":0.000117995565,"about_ca_topic_score_gemma":0.00001568232,"teacher_disagreement_score":0.15743648,"about_ca_system_score_codex":0.00007557166,"about_ca_system_score_gemma":0.000105961444,"threshold_uncertainty_score":0.99993014},"labels":[],"label_agreement":null},{"id":"W4280632784","doi":"10.1101/2022.05.09.491138","title":"Deep Reinforcement Learning for Optimal Experimental Design in Biology","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"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 Waterloo","funders":"","keywords":"Reinforcement learning; Computer science; Artificial intelligence; Design of experiments; Machine learning; Parametric statistics; Inference; Task (project management); Field (mathematics); Mathematics; Engineering","score_opus":0.015010817649601483,"score_gpt":0.2513206218324955,"score_spread":0.236309804182894,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280632784","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":[0.7945711,0.005841637,0.19752456,0.000039841892,0.00060939183,0.0013110483,0.000014267366,0.000080486876,0.000007631695],"genre_scores_gemma":[0.984223,0.00024390253,0.013405513,0.00009889361,0.0004359533,0.0014184321,0.000011234111,0.00013973063,0.000023335653],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99688506,0.00036023746,0.0005948002,0.0012598904,0.00020378252,0.00069624075],"domain_scores_gemma":[0.9982931,0.000035139576,0.00038987887,0.00096294377,0.00015155303,0.00016737083],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008709257,0.00054336706,0.0005515623,0.00026873077,0.00021563093,0.000065048655,0.0006303127,0.00056145113,0.00011711384],"category_scores_gemma":[0.00012895766,0.0006592117,0.0003110614,0.00027114415,0.000098212295,0.000005883804,0.001077763,0.00050802325,0.0000063066045],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000109463836,0.00006940019,0.002629952,0.000038077185,0.00018689422,0.0000056066115,0.000006572234,0.40531865,0.59146166,0.000060448263,0.00011206263,0.0000011963563],"study_design_scores_gemma":[0.0013363342,0.00069999625,0.0022671982,0.00004525542,0.00013764577,2.7297984e-8,0.000027450153,0.067927286,0.91171235,0.0000013788211,0.014650976,0.0011940886],"about_ca_topic_score_codex":0.000019794437,"about_ca_topic_score_gemma":0.0000020026853,"teacher_disagreement_score":0.33739135,"about_ca_system_score_codex":0.00032604346,"about_ca_system_score_gemma":0.00040983787,"threshold_uncertainty_score":0.9995859},"labels":[],"label_agreement":null},{"id":"W4281974954","doi":"10.1101/2022.06.01.494187","title":"The kinetic landscape of human transcription factors","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research; National Cancer Institute; Melanoma Research Alliance; National Institutes of Health; National Science Foundation","keywords":"Bursting; Transcription factor; Biology; Chromatin; Transcription (linguistics); Genetics; Gene; Computational biology; Gene regulatory network; Gene expression; Neuroscience","score_opus":0.011117315359388449,"score_gpt":0.21786201959315246,"score_spread":0.206744704233764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281974954","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":[0.9940266,0.004660663,0.0001996536,0.000049370963,0.000547145,0.0003431258,0.000109565044,0.000045899393,0.000017993918],"genre_scores_gemma":[0.99868906,0.00057377206,0.0001379666,0.00002637481,0.00033136262,0.000104342136,0.0000059814547,0.000096856915,0.000034276596],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9976871,0.00024820346,0.00053189107,0.0007442612,0.0003858064,0.0004027496],"domain_scores_gemma":[0.99757636,0.000019612158,0.00045140524,0.0015922888,0.00023035247,0.0001299852],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00051351456,0.0004195925,0.00041543553,0.00012575813,0.00035831655,0.00007169428,0.0008006035,0.00037220496,0.00008678493],"category_scores_gemma":[0.00005169469,0.00037191587,0.00040043503,0.00030667044,0.0001553372,0.0000034502616,0.0004754214,0.00041412536,0.0000027540837],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002059609,0.000059528116,0.021502014,0.00008152891,0.00033990602,0.0000022015197,0.000006174723,0.0009594497,0.9763438,0.00011905928,0.0005648148,9.444324e-7],"study_design_scores_gemma":[0.00039965185,0.00019744293,0.17973855,0.000046777182,0.00038073093,8.523902e-9,0.000020276411,0.00016155254,0.7926759,0.0000031572704,0.025694858,0.0006810829],"about_ca_topic_score_codex":0.000032650827,"about_ca_topic_score_gemma":0.000012961248,"teacher_disagreement_score":0.18366787,"about_ca_system_score_codex":0.000057096007,"about_ca_system_score_gemma":0.00022393886,"threshold_uncertainty_score":0.9998733},"labels":[],"label_agreement":null},{"id":"W4283278353","doi":"10.1371/journal.pcbi.1010183","title":"Quantifying biochemical reaction rates from static population variability within incompletely observed complex networks","year":2022,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Planning and Budgeting Committee of the Council for Higher Education of Israel; Natural Sciences and Engineering Research Council of Canada; Connaught Fund; Bundesministerium für Bildung und Forschung; University of Toronto; Council for Higher Education; Ben-Gurion University of the Negev","keywords":"Inference; Statistical inference; Systems biology; Computer science; Population; Complex system; Stochastic process; Computational biology; Biology; Artificial intelligence; Mathematics; Statistics","score_opus":0.0711223702447108,"score_gpt":0.2891913078985424,"score_spread":0.21806893765383162,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283278353","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":[0.9749739,0.0001652409,0.024003347,0.00020375314,0.0002225246,0.00022569501,0.00014311976,0.00004476244,0.00001761325],"genre_scores_gemma":[0.9654903,0.000005119598,0.009096601,0.00038877345,0.00027536,0.00006409553,0.024644217,0.000027181306,0.00000835694],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99736786,0.0009284176,0.00054416485,0.00068080786,0.00020871132,0.00027003043],"domain_scores_gemma":[0.99890685,0.00023414749,0.00032139043,0.00031594728,0.00013733594,0.000084326246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004915389,0.00022050063,0.00031343856,0.00007721515,0.00036642575,0.000022283682,0.00025519586,0.00014002383,0.00015630652],"category_scores_gemma":[0.00013200894,0.00024116284,0.00013628372,0.00027766445,0.00009926776,0.000006451684,0.0003059835,0.00021726899,0.000006408482],"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":[0.0001818123,0.00018090621,0.14987575,0.000008794821,0.0003204013,0.0000012602904,0.000034643093,0.502223,0.34578228,0.0005825889,0.0005206241,0.0002878999],"study_design_scores_gemma":[0.0006104697,0.0002133024,0.2795056,0.0000051085603,0.000101060476,0.000010532405,0.000065351895,0.7086291,0.002275473,0.0077058338,0.0004981766,0.0003800003],"about_ca_topic_score_codex":0.00019511346,"about_ca_topic_score_gemma":0.00004078076,"teacher_disagreement_score":0.3435068,"about_ca_system_score_codex":0.000106132706,"about_ca_system_score_gemma":0.00007061123,"threshold_uncertainty_score":0.9834335},"labels":[],"label_agreement":null},{"id":"W4285387008","doi":"10.1038/s41467-022-31819-x","title":"Auxotrophic and prototrophic conditional genetic networks reveal the rewiring of transcription factors in Escherichia coli","year":2022,"lang":"en","type":"article","venue":"Nature Communications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"Canadian Institutes of Health Research; Canada Foundation for Innovation; Natural Sciences and Engineering Research Council of Canada; Saskatchewan Health Research Foundation; Government of Canada","keywords":"Biology; Escherichia coli; Gene; Genetics; Auxotrophy; Transcription factor; Systems biology; Computational biology; Gene regulatory network; Adaptation (eye); Gene expression","score_opus":0.01236015075380165,"score_gpt":0.24988312811459146,"score_spread":0.2375229773607898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285387008","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":[0.98487157,0.013713674,0.00022182289,0.0006979966,0.0000397561,0.00037063335,0.000022106613,0.0000055952596,0.000056844652],"genre_scores_gemma":[0.9980346,0.0005638246,0.00064569694,0.00012788949,0.000037994843,0.00020642746,0.00032308706,0.0000136049375,0.000046854337],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9989735,0.00037340142,0.0002230818,0.00017257017,0.00013254215,0.00012492256],"domain_scores_gemma":[0.99891514,0.000034235254,0.0001462207,0.00081885915,0.000056549412,0.000028973],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022185194,0.000096485826,0.00012004154,0.000057040794,0.00032275787,0.000009248403,0.00052273023,0.0001260596,0.0000120793275],"category_scores_gemma":[0.000031452426,0.00008630955,0.00007240188,0.00032098553,0.00017092837,0.0000029852831,0.00028927255,0.00056507916,1.1803226e-7],"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":[0.00010177116,0.0002793352,0.14058894,0.000027761382,0.0002560198,0.0000011903066,0.0004307462,0.13689797,0.7170472,0.0025531733,0.0013223347,0.0004935235],"study_design_scores_gemma":[0.000708901,0.00021516062,0.95691544,0.00001605143,0.00013194408,0.000016966591,0.00045100137,0.019510685,0.003815741,0.00059906323,0.017311992,0.00030708592],"about_ca_topic_score_codex":0.00002187328,"about_ca_topic_score_gemma":0.00020723704,"teacher_disagreement_score":0.8163265,"about_ca_system_score_codex":0.000027875807,"about_ca_system_score_gemma":0.000054452084,"threshold_uncertainty_score":0.35196012},"labels":[],"label_agreement":null},{"id":"W4289388832","doi":"","title":"Bursting in gene expression model","year":2015,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"McGill University","funders":"","keywords":"Bursting; Computer science; Expression (computer science); Artificial intelligence; Neuroscience; Biology; Programming language","score_opus":0.017381796953089685,"score_gpt":0.2387808555172828,"score_spread":0.2213990585641931,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4289388832","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":[0.851197,0.0031989764,0.134667,0.0008579261,0.00009080692,0.00025181525,0.000027973061,0.000048726746,0.009659767],"genre_scores_gemma":[0.9351864,0.00043764335,0.05851017,0.00004232248,0.00005098473,0.00005052803,0.0010177465,0.00004902396,0.0046552126],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.995977,0.0021636907,0.00042929294,0.0008232765,0.00029034636,0.00031639184],"domain_scores_gemma":[0.9963009,0.00007106832,0.00033829262,0.0019793306,0.0011435249,0.00016693446],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0036312947,0.00028812073,0.0003093373,0.00013754987,0.00011002387,0.00010307746,0.000855273,0.0004373589,0.000014515807],"category_scores_gemma":[0.0006536927,0.00031959507,0.00018586576,0.00019541754,0.0001017176,0.0000057339785,0.0018300536,0.00035882456,0.0000082133965],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004473883,0.0005977733,0.010314754,0.00015054143,0.00015496902,0.00000825564,0.0030495615,0.1880256,0.77851796,0.0010220634,0.005938355,0.012175411],"study_design_scores_gemma":[0.000523862,3.5578003e-7,0.0005524216,0.00070029,0.000048145914,0.0000054696047,0.00005430568,0.26489398,0.72807723,0.002378851,0.0022241478,0.00054092944],"about_ca_topic_score_codex":0.00018291795,"about_ca_topic_score_gemma":0.0006673416,"teacher_disagreement_score":0.083989345,"about_ca_system_score_codex":0.00007942258,"about_ca_system_score_gemma":0.00037483132,"threshold_uncertainty_score":0.9999256},"labels":[],"label_agreement":null},{"id":"W4293864458","doi":"","title":"N-Synchronous Kahn Networks","year":2006,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Prevention of Organ Failure","funders":"","keywords":"Computer science","score_opus":0.006399991527802314,"score_gpt":0.20693151007978905,"score_spread":0.20053151855198673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293864458","genre_codex":"methods","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":[0.3733549,0.008665765,0.5731659,0.002197429,0.00035056443,0.00047556948,0.000049465194,0.0001506429,0.04158973],"genre_scores_gemma":[0.9527069,0.0009571133,0.029627409,0.00009953176,0.00023106126,0.000072914874,0.0031735182,0.00009109245,0.013040503],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9950056,0.002743155,0.0004998943,0.001014484,0.00028687186,0.0004500132],"domain_scores_gemma":[0.99516964,0.00012575946,0.0004596925,0.002757107,0.001317026,0.00017078251],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0023459587,0.00041492895,0.00039087958,0.00010865074,0.00025266397,0.00023353986,0.0011143843,0.0006343169,0.000077571676],"category_scores_gemma":[0.00025161888,0.000471086,0.00042618634,0.00023421054,0.00024263766,0.0000050530234,0.0016580418,0.0004545327,0.000026730557],"study_design_candidate":"not_applicable","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":[0.00016967265,0.004415599,0.04878226,0.00094487326,0.00399111,0.00006965635,0.0027484875,0.18490633,0.15983573,0.01781346,0.25532335,0.32099947],"study_design_scores_gemma":[0.0024352951,0.000003763709,0.03160892,0.002173268,0.00093950354,0.00007389906,0.000089810535,0.26821023,0.3719768,0.0035892942,0.31461266,0.0042865705],"about_ca_topic_score_codex":0.0006025012,"about_ca_topic_score_gemma":0.0022050433,"teacher_disagreement_score":0.57935196,"about_ca_system_score_codex":0.00007187762,"about_ca_system_score_gemma":0.00025845447,"threshold_uncertainty_score":0.9997741},"labels":[],"label_agreement":null},{"id":"W4296130880","doi":"10.1101/2022.09.12.507681","title":"PhysiPKPD: A pharmacokinetics and pharmacodynamics module for PhysiCell","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Open source; Key (lock); Pharmacodynamics; In silico; Pharmacokinetics; Computer science; Source code; Code (set theory); R package; Computational biology; Software engineering; Pharmacology; Programming language; Medicine; Chemistry; Biology; Software; Operating system","score_opus":0.009325799800936134,"score_gpt":0.23634568509984477,"score_spread":0.22701988529890862,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4296130880","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":[0.9862427,0.0044694482,0.0064999526,0.00010198309,0.0008103645,0.0010126219,0.0007489736,0.000105221035,0.000008753265],"genre_scores_gemma":[0.9909966,0.0015790516,0.004786903,0.00032160676,0.0013850143,0.0006338443,0.000013793599,0.00023721186,0.000045990284],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9970733,0.00013904143,0.00044158546,0.0014179804,0.00031416616,0.0006139064],"domain_scores_gemma":[0.9977669,0.00002465519,0.0004235385,0.0011989642,0.00031856535,0.00026738882],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00039327453,0.0006642219,0.00057096593,0.00015169104,0.00026602446,0.00011583205,0.0006268333,0.00034489657,0.000037509548],"category_scores_gemma":[0.000036612335,0.00081316155,0.0003670273,0.0002873298,0.00013429445,0.000007703854,0.0012455636,0.0004658022,0.0000044688927],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008115238,0.00016750097,0.0012231509,0.00034674778,0.0006858938,0.000005626425,0.0000032543405,0.008065258,0.9874688,0.00006487642,0.0018781043,0.000009675552],"study_design_scores_gemma":[0.0018434378,0.00019536092,0.005115431,0.00005535764,0.0011838074,3.3533784e-8,0.0000047954986,0.040641945,0.858789,0.000008618385,0.09042637,0.0017358086],"about_ca_topic_score_codex":0.0000095783325,"about_ca_topic_score_gemma":0.0000012993131,"teacher_disagreement_score":0.12867972,"about_ca_system_score_codex":0.00010648655,"about_ca_system_score_gemma":0.0002994426,"threshold_uncertainty_score":0.9994319},"labels":[],"label_agreement":null},{"id":"W4297086015","doi":"","title":"Stochastic self-regulated gene expression model","year":2011,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"McGill University","funders":"","keywords":"Computer science; Expression (computer science); Gene expression; Gene; Biology; Genetics; Programming language","score_opus":0.011769563267629596,"score_gpt":0.21437619232338168,"score_spread":0.20260662905575208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297086015","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":[0.5008184,0.0022245136,0.49083567,0.0003726414,0.00012618685,0.0003644781,0.000040045186,0.00014936483,0.0050687334],"genre_scores_gemma":[0.922536,0.00033760013,0.0694154,0.00004252844,0.000056214874,0.00007400415,0.001387635,0.00008362538,0.0060669575],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9955621,0.0021230036,0.0004909382,0.0010962354,0.00032641386,0.00040132034],"domain_scores_gemma":[0.9947595,0.0000716254,0.0004880655,0.003005344,0.0014411778,0.00023430896],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0019477581,0.00043569828,0.000393559,0.00013951698,0.00024555656,0.00011572506,0.0011723184,0.00063258345,0.000064622785],"category_scores_gemma":[0.00025860078,0.0004672527,0.0003571042,0.00018953737,0.00014738014,0.0000069488597,0.0020068754,0.0003800356,0.000024223074],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006600698,0.0010886585,0.00061104033,0.00017390834,0.00077722064,0.00000461797,0.0037608813,0.08357283,0.89715403,0.0024605086,0.0046707834,0.0056594983],"study_design_scores_gemma":[0.00047580435,6.77898e-7,0.00038187212,0.00047114943,0.00021837247,0.000009605607,0.000019223538,0.18105328,0.81319535,0.0025116415,0.00096253277,0.0007005134],"about_ca_topic_score_codex":0.00010589493,"about_ca_topic_score_gemma":0.00023838227,"teacher_disagreement_score":0.42171767,"about_ca_system_score_codex":0.000058611487,"about_ca_system_score_gemma":0.00034253692,"threshold_uncertainty_score":0.9997779},"labels":[],"label_agreement":null},{"id":"W4297977071","doi":"","title":"Bursting in gene expression","year":2015,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"McGill University","funders":"","keywords":"Bursting; Computer science; Expression (computer science); Gene expression; Gene; Computational biology; Artificial intelligence; Genetics; Biology; Neuroscience; Programming language","score_opus":0.014217477143679423,"score_gpt":0.23206561799430406,"score_spread":0.21784814085062462,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297977071","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":[0.893978,0.0176509,0.05920126,0.004665091,0.00037740104,0.00044732494,0.000048969614,0.000054861557,0.023576178],"genre_scores_gemma":[0.9227446,0.0018442848,0.05456951,0.000060986997,0.00013637159,0.000061932136,0.0014390431,0.00007656318,0.019066766],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.98981655,0.0071298596,0.0007741151,0.0012669775,0.00042555816,0.00058691716],"domain_scores_gemma":[0.99406123,0.00025170404,0.00061748596,0.0026822456,0.0020506456,0.0003366633],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.007045879,0.00049025915,0.0005294693,0.00017813225,0.000223151,0.00018037786,0.0012405718,0.0007629714,0.00010384618],"category_scores_gemma":[0.0013934057,0.0005729112,0.00032742057,0.00045125763,0.00028702282,0.000013342014,0.0022056678,0.00058489654,0.000052296637],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000079563055,0.0015220358,0.046786383,0.00032191994,0.00037832902,0.000034506687,0.006185448,0.018643316,0.8516385,0.007284602,0.0073391423,0.059786238],"study_design_scores_gemma":[0.0010169568,0.0000010146234,0.004566653,0.0021153542,0.000120387835,0.000026419757,0.00019368138,0.023436116,0.9054144,0.0015930118,0.060599793,0.0009161829],"about_ca_topic_score_codex":0.0007745374,"about_ca_topic_score_gemma":0.002133582,"teacher_disagreement_score":0.058870055,"about_ca_system_score_codex":0.00020419799,"about_ca_system_score_gemma":0.000547584,"threshold_uncertainty_score":0.99967223},"labels":[],"label_agreement":null},{"id":"W4298042719","doi":"10.7554/elife.79919","title":"Evolution of cell size control is canalized towards adders or sizers by cell cycle structure and selective pressures","year":2022,"lang":"en","type":"article","venue":"eLife","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; National Institutes of Health; National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; Chan Zuckerberg Initiative","keywords":"Cell size; Adder; Control (management); Cell biology; Biology; Cell; Evolutionary biology; Computational biology; Computer science; Artificial intelligence; Genetics; Telecommunications","score_opus":0.0022042074430162093,"score_gpt":0.196304965792339,"score_spread":0.19410075834932278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4298042719","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":[0.99386716,0.004981604,0.00018275349,0.00007560925,0.000056380464,0.00018864659,0.0004197182,0.0000075589987,0.00022059752],"genre_scores_gemma":[0.99793667,0.00008196809,0.00017531605,0.00032580612,0.00006297758,0.000018759607,0.000051628067,0.0000196745,0.0013271943],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99887794,0.00015772258,0.00017991268,0.00032616092,0.00025515887,0.00020309119],"domain_scores_gemma":[0.9994224,0.000020930911,0.00015036433,0.00022406483,0.0000996455,0.00008260622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011132744,0.00014526908,0.00022203937,0.000029393068,0.00012777523,0.0000076107285,0.00014205684,0.000079000034,0.00025740598],"category_scores_gemma":[0.000036441328,0.00013610022,0.000091959024,0.00015712187,0.00007509298,0.000002547092,0.00009151969,0.000093949995,2.8963555e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036584123,0.000041641793,0.0026677565,0.00002383874,0.00021677633,0.0000011047786,0.00017066814,0.007082415,0.92696744,8.9323134e-7,0.06235752,0.000104098275],"study_design_scores_gemma":[0.0021640286,0.00035910003,0.004084295,0.0000019707093,0.00028422748,0.0000042909924,0.0005598816,0.0016854038,0.97170055,0.000024334073,0.018876024,0.00025587142],"about_ca_topic_score_codex":0.00046979217,"about_ca_topic_score_gemma":0.00014323735,"teacher_disagreement_score":0.044733126,"about_ca_system_score_codex":0.00004334377,"about_ca_system_score_gemma":0.00021556692,"threshold_uncertainty_score":0.5550006},"labels":[],"label_agreement":null},{"id":"W4298271050","doi":"10.17615/ktp3-6d25","title":"Guidelines for Genome-Scale Analysis of Biological Rhythms","year":2020,"lang":"en","type":"article","venue":"UNC Libraries","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"National Institute of Neurological Disorders and Stroke; National Institute of Arthritis and Musculoskeletal and Skin Diseases; National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of Allergy and Infectious Diseases; National Key Research and Development Program of China; Leibniz-Gemeinschaft; Medical Research Council; Washington University in St. Louis; Japan Society for the Promotion of Science; Directorate for Biological Sciences; Volkswagen Foundation; National Institutes of Health; Leibniz-Institut für Nutztierbiologie; Royal Society; Ministerio de Economía y Competitividad; National Natural Science Foundation of China; Canadian Institutes of Health Research; National Science Foundation; National Institute of General Medical Sciences; Francis Crick Institute; Cancer Research UK; Biotechnology and Biological Sciences Research Council; Wellcome Trust; Defense Advanced Research Projects Agency; University of Central Florida; Deutsche Forschungsgemeinschaft; Welch Foundation; Rensselaer Polytechnic Institute; Heart and Stroke Foundation of Canada","keywords":"Rhythm; Scale (ratio); Computational biology; Genome; Computer science; Biology; Evolutionary biology; Geography; Medicine; Genetics; Cartography; Internal medicine; Gene","score_opus":0.06458904483573742,"score_gpt":0.279446872206906,"score_spread":0.2148578273711686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4298271050","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":[0.9220575,0.003952756,0.070524625,0.0027930809,0.00004799736,0.00019049784,0.00014948907,0.000032765776,0.00025125573],"genre_scores_gemma":[0.93147755,0.00006712465,0.0643175,0.0019688786,0.0006178662,0.000024155426,0.0011222992,0.000021395354,0.000383236],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990577,0.000032336946,0.0003278985,0.00033009928,0.00008458438,0.00016739866],"domain_scores_gemma":[0.99933803,0.00001959871,0.00011473928,0.0002638662,0.00017236081,0.00009137564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000085634914,0.00013071088,0.0003441639,0.000062820596,0.000047729398,0.000019979261,0.00019636414,0.00012880808,0.00007177205],"category_scores_gemma":[0.00017177427,0.00010610373,0.00040093763,0.00044336397,0.00012020441,0.0000045225615,0.00012989504,0.000025959254,0.00000213572],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005105762,0.000092201735,0.054694396,0.000072949915,0.007187224,0.0000022258114,0.00031006604,0.035767432,0.85592574,0.012826436,0.030396841,0.0022138895],"study_design_scores_gemma":[0.0011065518,0.0011192932,0.022359727,0.000007835279,0.0032017012,0.0000021262736,0.0004550945,0.025156133,0.57201535,0.0062195617,0.3674493,0.00090734294],"about_ca_topic_score_codex":0.0000024470332,"about_ca_topic_score_gemma":0.0000067382502,"teacher_disagreement_score":0.33705246,"about_ca_system_score_codex":0.0000021763578,"about_ca_system_score_gemma":0.00004508227,"threshold_uncertainty_score":0.43267846},"labels":[],"label_agreement":null},{"id":"W4298280328","doi":"","title":"Towards nonlinear cell population model structured by molecular content","year":2014,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"McGill University","funders":"","keywords":"Nonlinear system; Computer science; Population; Physics; Medicine; Environmental health","score_opus":0.010069973035332995,"score_gpt":0.21676908782534443,"score_spread":0.20669911479001143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4298280328","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":[0.65596527,0.0019371152,0.33787036,0.00096090516,0.000099339195,0.00029671012,0.00012403385,0.000053883916,0.0026924075],"genre_scores_gemma":[0.9363288,0.0003392905,0.05215759,0.00016500565,0.00004717574,0.000058630383,0.0066905096,0.000077119694,0.004135868],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99556124,0.0021426855,0.00053391536,0.000996929,0.00040833655,0.00035686826],"domain_scores_gemma":[0.9955795,0.000042854575,0.0005356325,0.0023198551,0.0013150959,0.00020710239],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0017061087,0.00042821688,0.00042535487,0.00009794398,0.00016938613,0.00016679696,0.0009587775,0.0005860931,0.00003374416],"category_scores_gemma":[0.00027966185,0.0004681719,0.00039575572,0.00014344088,0.00011407795,0.0000058934893,0.0011130564,0.00036909393,0.000007777883],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004534724,0.00050581235,0.0023642688,0.00026384732,0.00043947852,0.000002629628,0.0007309058,0.07143368,0.8971757,0.0022372121,0.0067715454,0.018029563],"study_design_scores_gemma":[0.0005359766,8.8235106e-7,0.00077438215,0.00016679773,0.00015553796,0.000002955264,0.000014957217,0.30314672,0.6878581,0.0011534925,0.0055719917,0.00061818934],"about_ca_topic_score_codex":0.00058040454,"about_ca_topic_score_gemma":0.0004517717,"teacher_disagreement_score":0.28571278,"about_ca_system_score_codex":0.00007022512,"about_ca_system_score_gemma":0.00018856993,"threshold_uncertainty_score":0.999777},"labels":[],"label_agreement":null},{"id":"W4299419049","doi":"10.1007/978-1-4419-1428-6_1011","title":"Evolutionary Learning and Stochastic Process Algebra","year":2012,"lang":"en","type":"book-chapter","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Process (computing); Computer science; Stochastic process; Algebra over a field; Mathematics; Pure mathematics; Statistics; Programming language","score_opus":0.006819263733032706,"score_gpt":0.22104503872634929,"score_spread":0.21422577499331658,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4299419049","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027625253,0.1679359,0.011827235,0.0001533562,0.00037477294,0.0008409768,0.00002930328,0.00016110683,0.7910521],"genre_scores_gemma":[0.47829336,0.0005303027,0.00014901828,0.00004450005,0.00063621276,0.000008349498,0.0002663121,0.00006229471,0.52000964],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990462,0.000013392428,0.00017381419,0.00039554358,0.00015028237,0.00022073508],"domain_scores_gemma":[0.99945676,0.000007157411,0.00011686389,0.000205675,0.00008776729,0.00012577168],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000082690254,0.00026601076,0.00022240228,0.00006309947,0.00009408909,0.000011884884,0.00009355261,0.00039676798,0.00044976673],"category_scores_gemma":[0.000012965556,0.0002587441,0.00011380601,0.000015708114,0.0001026969,0.0000018755597,0.00013092511,0.00017761019,0.00005020977],"study_design_candidate":"not_applicable","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":[0.0014593861,0.0007347691,0.030034669,0.0034443308,0.026295332,0.00011011164,0.0009539294,0.055583023,0.12958357,0.23648584,0.13526274,0.3800523],"study_design_scores_gemma":[0.00087908417,0.0005367432,0.001158505,0.00021022015,0.0016353045,0.00026452713,0.000098069126,0.0017016156,0.0014122943,0.01017249,0.979078,0.0028531556],"about_ca_topic_score_codex":0.0000011140781,"about_ca_topic_score_gemma":0.0000050926956,"teacher_disagreement_score":0.84381527,"about_ca_system_score_codex":0.00001341324,"about_ca_system_score_gemma":0.00006098907,"threshold_uncertainty_score":0.99998647},"labels":[],"label_agreement":null},{"id":"W4300123266","doi":"10.22541/au.166004694.43718177/v1","title":"Coupled stochastic systems of Skorokhod type: well-posedness of a mathematical model and its applications","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Wilfrid Laurier University","funders":"","keywords":"Bounded function; Mathematics; Population; Representation (politics); Stochastic differential equation; Type (biology); Applied mathematics; Jump; Boundary (topology); Stochastic modelling; Statistical physics; Mathematical analysis; Physics","score_opus":0.015938866940774832,"score_gpt":0.2634993381121258,"score_spread":0.24756047117135094,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4300123266","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":[0.6671436,0.0071941093,0.32318172,0.000021714193,0.0000741261,0.0011418638,0.0000968788,0.000016278118,0.0011297668],"genre_scores_gemma":[0.99643904,0.0001762958,0.0009789872,0.000006639472,0.00004983608,0.00022003852,0.00022759101,0.000030228653,0.0018713372],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987018,0.000053842417,0.0004665245,0.00042105437,0.000217796,0.00013897764],"domain_scores_gemma":[0.99869114,0.000024770443,0.00031032917,0.0006759924,0.00022666603,0.00007107189],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023532311,0.00019732837,0.0004844834,0.00007247359,0.000037045396,0.000008601131,0.0002923614,0.00023864204,0.00007925787],"category_scores_gemma":[0.00002667589,0.00019165476,0.00013486261,0.00011512083,0.000066937035,8.045072e-7,0.00078294904,0.00012788162,0.000002143399],"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":[0.00003448819,0.0001338828,0.000028546765,0.0010090106,0.00042860224,2.8017303e-7,0.00003272524,0.91241455,0.08182124,0.0039085452,0.00015637334,0.000031730233],"study_design_scores_gemma":[0.00021108991,0.000061926316,0.00001698453,0.000042272466,0.0003855379,0.0000065943163,0.00013597187,0.9945899,0.0034186062,0.00080416386,0.00009715779,0.0002297613],"about_ca_topic_score_codex":0.000010939247,"about_ca_topic_score_gemma":0.000004176112,"teacher_disagreement_score":0.3292955,"about_ca_system_score_codex":0.000015841902,"about_ca_system_score_gemma":0.00019040304,"threshold_uncertainty_score":0.7815454},"labels":[],"label_agreement":null},{"id":"W4300881170","doi":"","title":"Stable, Unstable and Metastable States of Equilibrium: Definitions and Applications to Human Movement","year":2015,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Memorial University of Newfoundland","funders":"","keywords":"Metastability; Movement (music); Restitution; Economics; Statistical physics; Physics; Political science; Quantum mechanics; Law","score_opus":0.2054806004473687,"score_gpt":0.48550606933239576,"score_spread":0.28002546888502705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4300881170","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":[0.9690685,0.025498388,0.0029509624,0.00007826345,0.000033331915,0.0004677578,0.00013410201,0.000007349836,0.001761335],"genre_scores_gemma":[0.9923266,0.0052568545,0.001430824,0.00018113543,0.00007622643,0.00010245875,0.000117894066,0.00003474048,0.00047323745],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983846,0.000117429445,0.0005412141,0.00038970658,0.00029395067,0.00027311256],"domain_scores_gemma":[0.9983798,0.000033672964,0.00036922624,0.0004669934,0.0003887506,0.0003615006],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00079668075,0.00020234264,0.00046564013,0.0002963642,0.00013623678,0.00027948758,0.0006444185,0.0000683243,0.00029659914],"category_scores_gemma":[0.00004555447,0.0001984968,0.0000741086,0.0005415072,0.00012921367,0.00007364298,0.0009966401,0.00008134921,0.0000015740503],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006356563,0.00018522445,0.13134521,0.00006674756,0.00043730426,0.0000013522441,0.000057228757,0.004691448,0.8395032,0.00036103604,0.021954903,0.001332735],"study_design_scores_gemma":[0.0014111564,0.00013013449,0.08514304,0.00015065832,0.00062712084,0.000012367488,0.0006560238,0.00022423881,0.80375606,0.031021783,0.07600651,0.000860929],"about_ca_topic_score_codex":0.00049257226,"about_ca_topic_score_gemma":0.00014994536,"teacher_disagreement_score":0.054051608,"about_ca_system_score_codex":0.000025345355,"about_ca_system_score_gemma":0.000112456015,"threshold_uncertainty_score":0.80944645},"labels":[],"label_agreement":null},{"id":"W4306412453","doi":"10.1002/ece3.9396","title":"Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the <scp>WaRM</scp> Network","year":2022,"lang":"en","type":"article","venue":"Ecology and Evolution","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Saint Mary's University","funders":"Carlsbergfondet","keywords":"Computer science; Statistical analysis; Natural (archaeology); Biology; Statistics; Mathematics","score_opus":0.014302969361963519,"score_gpt":0.2360855900610592,"score_spread":0.22178262069909568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4306412453","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":[0.97790223,0.009883937,0.01170248,0.000028111679,0.00026513924,0.0001684413,0.00002411238,0.000011691338,0.000013844777],"genre_scores_gemma":[0.99684405,0.00007657748,0.0012079912,0.00013132203,0.00035190702,0.00010379413,0.001247475,0.000013394711,0.000023475011],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998368,0.00044804282,0.0002443372,0.00045699065,0.00009169079,0.00039094265],"domain_scores_gemma":[0.99952275,0.00009068839,0.00007964956,0.00021269222,0.000022148333,0.00007207015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004187786,0.00015642878,0.00018704453,0.000021794816,0.0006197636,0.000023667222,0.00013055098,0.00010030253,0.000014615811],"category_scores_gemma":[0.000038040824,0.00014075232,0.00003331293,0.00015296476,0.00010202738,0.000009355175,0.00029611585,0.00022685922,4.4600003e-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":[0.00022819151,0.00027340624,0.443281,0.00000691515,0.000415692,0.000016908687,0.003059414,0.51515555,0.020855375,0.0041767624,0.01147144,0.0010593089],"study_design_scores_gemma":[0.0013660602,0.00042982923,0.1597741,0.000010520545,0.00009416355,0.000026767335,0.007093658,0.8241887,0.00020281193,0.003879502,0.0027411624,0.00019270576],"about_ca_topic_score_codex":0.00076648564,"about_ca_topic_score_gemma":0.0016541189,"teacher_disagreement_score":0.30903316,"about_ca_system_score_codex":0.00007459822,"about_ca_system_score_gemma":0.000035664183,"threshold_uncertainty_score":0.57397133},"labels":[],"label_agreement":null},{"id":"W4309494734","doi":"10.1371/journal.pcbi.1010695","title":"Deep reinforcement learning for optimal experimental design in biology","year":2022,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"H2020 European Research Council; European Commission; Natural Sciences and Engineering Research Council of Canada; Wellcome Trust","keywords":"Reinforcement learning; Computer science; Artificial intelligence; Inference; Parametric statistics; Design of experiments; Machine learning; Task (project management); Reinforcement; Mathematics; Engineering; Statistics","score_opus":0.021370320155669264,"score_gpt":0.2795778878201643,"score_spread":0.25820756766449504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4309494734","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":[0.5121723,0.0009402698,0.48626378,0.00009746222,0.000094376555,0.00034980336,0.000004058432,0.000014473714,0.00006347101],"genre_scores_gemma":[0.98413616,0.0000070704846,0.01334374,0.00022478937,0.00011384165,0.000406531,0.0016642817,0.000017485263,0.000086111875],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99869055,0.00030657195,0.00026445606,0.00039311466,0.00006993315,0.0002754064],"domain_scores_gemma":[0.9996107,0.00008465594,0.000103734914,0.00010908413,0.00005025577,0.00004156729],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002467983,0.0001346466,0.00017980173,0.00011598853,0.00019709807,0.0000059138542,0.0001830742,0.00008055361,0.00013024297],"category_scores_gemma":[0.00004019227,0.00014921514,0.00009546012,0.00011992606,0.00006784685,0.0000019423087,0.00022373348,0.00010064504,0.000004246644],"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":[0.00016485174,0.00008071841,0.0027234827,0.0000021899943,0.000098272925,7.0817964e-7,0.000049670143,0.8738632,0.12175001,0.0008740886,0.00011748816,0.00027528225],"study_design_scores_gemma":[0.0013246707,0.00197085,0.00036332646,0.0000015376116,0.000021537693,0.000013683895,0.00021075847,0.96443474,0.025014212,0.0011004313,0.0052634515,0.00028080348],"about_ca_topic_score_codex":0.000004670223,"about_ca_topic_score_gemma":0.0000018047168,"teacher_disagreement_score":0.47292006,"about_ca_system_score_codex":0.00007443684,"about_ca_system_score_gemma":0.000078031386,"threshold_uncertainty_score":0.60848165},"labels":[],"label_agreement":null},{"id":"W4311580205","doi":"10.1038/s41467-022-35151-2","title":"Slowest possible replicative life at frigid temperatures for yeast","year":2022,"lang":"en","type":"article","venue":"Nature Communications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Institute for Advanced Research","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Yeast; Doubling time; Saccharomyces cerevisiae; Reactive oxygen species; Cell biology; Biology; Budding yeast; Gene; Cell; Genetics","score_opus":0.013655777465309401,"score_gpt":0.2888140712345219,"score_spread":0.2751582937692125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311580205","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":[0.86793196,0.1016395,0.00049677317,0.017171977,0.0005217832,0.0017496404,0.0014204493,0.0001394475,0.008928441],"genre_scores_gemma":[0.98969173,0.0003069688,0.0029564186,0.0010690301,0.00013238647,0.0005205672,0.0022931267,0.00002977166,0.002999967],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990217,0.00015843891,0.00017986204,0.00032750305,0.00013286335,0.0001796316],"domain_scores_gemma":[0.9970783,0.000040743456,0.00012263599,0.0025142832,0.00015761956,0.00008639761],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022722571,0.00012694583,0.00013430972,0.000055306034,0.0010597926,0.000021078917,0.0011349276,0.00014816044,0.000047137364],"category_scores_gemma":[0.00014362934,0.00013297226,0.00017691984,0.00027397936,0.00009739127,0.0000025702248,0.0011405768,0.00038246257,0.0000060082143],"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":[0.00022245146,0.0004514056,0.01263929,0.000016646181,0.0007134763,7.668938e-7,0.00022405751,0.002374849,0.40448174,0.009403004,0.56873775,0.00073455373],"study_design_scores_gemma":[0.00030508742,0.00011621569,0.0038657608,0.0000022309614,0.00006818245,0.000012761938,0.00015166488,0.00044488077,0.011106628,0.00010249139,0.9836237,0.00020041487],"about_ca_topic_score_codex":0.0000044225853,"about_ca_topic_score_gemma":0.00021992752,"teacher_disagreement_score":0.4148859,"about_ca_system_score_codex":0.000062936495,"about_ca_system_score_gemma":0.00012622104,"threshold_uncertainty_score":0.8151175},"labels":[],"label_agreement":null},{"id":"W4311700793","doi":"10.1021/acssynbio.2c00131","title":"NLoed: A Python Package for Nonlinear Optimal Experimental Design in Systems Biology","year":2022,"lang":"en","type":"article","venue":"ACS Synthetic Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Python (programming language); Workflow; Computer science; Modular design; Software; Variety (cybernetics); Systems biology; Experimental data; Synthetic biology; Bioinformatics; Artificial intelligence; Programming language; Biology","score_opus":0.018299831444382287,"score_gpt":0.27203086885645117,"score_spread":0.25373103741206887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311700793","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":[0.95973843,0.006680417,0.031800974,0.00018243236,0.0005177255,0.0007909312,0.00017128974,0.000029144454,0.00008867256],"genre_scores_gemma":[0.9941634,0.000056048702,0.0037506504,0.00014180115,0.00025502092,0.00082180987,0.0005510576,0.000049961454,0.00021028258],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9975422,0.00070427667,0.00040317525,0.0007247364,0.00006969205,0.00055592693],"domain_scores_gemma":[0.9990886,0.00009171875,0.00015257884,0.00054903224,0.00004087843,0.0000772089],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007260741,0.00025494074,0.00040029723,0.00014679636,0.00018002231,0.000012096072,0.00043429167,0.00026199606,0.000059753227],"category_scores_gemma":[0.00007256506,0.00025361616,0.0001653468,0.00018051856,0.00017794949,0.0000022453964,0.00036268518,0.00014373868,0.000008582018],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002847304,0.00020983956,0.0011545073,0.000009818834,0.00013646227,0.000004667986,0.00007653595,0.009561847,0.9863607,0.00057390216,0.0007833092,0.0008436593],"study_design_scores_gemma":[0.0030920308,0.0052606724,0.00012098779,0.000014905209,0.0001372137,0.0002593132,0.0017340691,0.022512047,0.7742915,0.00035435238,0.1910313,0.0011915781],"about_ca_topic_score_codex":0.000042153453,"about_ca_topic_score_gemma":0.00000767741,"teacher_disagreement_score":0.2120692,"about_ca_system_score_codex":0.00007384868,"about_ca_system_score_gemma":0.00010045303,"threshold_uncertainty_score":0.9999916},"labels":[],"label_agreement":null},{"id":"W4313023890","doi":"10.4236/am.2022.1311056","title":"Effective Finite-Difference Techniques for Estimating Sensitivities for Stochastic Biochemical Systems","year":2022,"lang":"en","type":"article","venue":"Applied Mathematics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Parametric statistics; Sensitivity (control systems); Estimator; Stochastic modelling; Variance (accounting); Computer science; Stochastic process; Parametric model; Biological system; Statistical physics; Mathematics; Applied mathematics; Statistics; Physics; Engineering; Biology","score_opus":0.010261781529585276,"score_gpt":0.24211399693606533,"score_spread":0.23185221540648004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313023890","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":[0.09367486,0.00014786755,0.904062,0.000014624809,0.00008683717,0.0017695958,0.000102652855,0.00005238495,0.00008917276],"genre_scores_gemma":[0.8133981,0.0000010046828,0.18160503,0.000040747134,0.00026586192,0.00426824,0.00022880344,0.000048805006,0.00014339539],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99894786,0.00002248103,0.0002688327,0.00033783162,0.00015212718,0.00027089263],"domain_scores_gemma":[0.998976,0.0003809467,0.00018677975,0.0003327914,0.00007590407,0.0000476015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039786779,0.00019925919,0.00030732524,0.000053426662,0.00026423472,0.00002831705,0.00017080674,0.00008953864,0.0000022381112],"category_scores_gemma":[0.00014411431,0.00020466726,0.00013968983,0.00008996975,0.000059068378,0.0000010841247,0.00017749718,0.00007569805,7.725214e-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":[0.00011756408,0.00019526159,0.0000030457693,0.0008259396,0.00033185876,5.937982e-7,0.00037916977,0.060819592,0.9236737,0.0064886035,0.0031326613,0.0040320237],"study_design_scores_gemma":[0.00074098894,0.0005056232,0.0000026190044,0.000054348064,0.00035689163,0.00003193421,0.0015783267,0.644176,0.34249845,0.008222063,0.0011751972,0.00065754086],"about_ca_topic_score_codex":0.0000012499635,"about_ca_topic_score_gemma":5.1036994e-7,"teacher_disagreement_score":0.722457,"about_ca_system_score_codex":0.000042424315,"about_ca_system_score_gemma":0.00003854985,"threshold_uncertainty_score":0.83460885},"labels":[],"label_agreement":null},{"id":"W4313535076","doi":"10.1109/tsp.2023.3234469","title":"Explicitly Solvable Continuous-Time Inference for Partially Observed Markov Processes","year":2022,"lang":"en","type":"preprint","venue":"IEEE Transactions on Signal Processing","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"York University","funders":"National Science Foundation of Sri Lanka; National Institutes of Health","keywords":"Conditional probability; Mathematics; Markov process; Regular conditional probability; Discrete time and continuous time; Markov chain; Inference; Hidden Markov model; Variable-order Markov model; Markov model; Applied mathematics; Conditional probability distribution; Algorithm; Markov property; Computer science; Random variable; Probability mass function; Artificial intelligence; Statistics","score_opus":0.030677737745652106,"score_gpt":0.2727955737205421,"score_spread":0.24211783597488998,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313535076","genre_codex":"methods","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":[0.10063473,0.0016692524,0.89592445,0.00011686081,0.00022604218,0.00086927204,0.00021104296,0.00010989147,0.00023843237],"genre_scores_gemma":[0.9900797,0.00016107809,0.0039403993,0.00019855214,0.00031293777,0.0013067732,0.00032024842,0.00012163806,0.0035586457],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99722177,0.00012550956,0.00058950594,0.0011303695,0.0003883132,0.0005445593],"domain_scores_gemma":[0.99831724,0.00007502609,0.00041224557,0.000558179,0.00048631357,0.0001509852],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00039021988,0.0005323049,0.00058078393,0.00015385204,0.0006254219,0.00020927834,0.00059610826,0.00043013075,0.00044947892],"category_scores_gemma":[0.000021720038,0.00058453984,0.0004189806,0.00029235551,0.0000982825,0.000015204468,0.000030141873,0.00051135477,0.000010918807],"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":[0.00075067166,0.00049522205,0.00009035571,0.0014610917,0.0006501141,0.0000053513418,0.00018073227,0.74437165,0.20188777,0.0000010363552,0.0008925673,0.049213417],"study_design_scores_gemma":[0.001784295,0.0012060486,0.000053867654,0.0006693253,0.001466378,0.000015643327,0.00034807858,0.08921512,0.88389736,0.0005629422,0.01836522,0.0024157495],"about_ca_topic_score_codex":0.000016205448,"about_ca_topic_score_gemma":0.000066459,"teacher_disagreement_score":0.89198405,"about_ca_system_score_codex":0.00008066431,"about_ca_system_score_gemma":0.0012879028,"threshold_uncertainty_score":0.9996606},"labels":[],"label_agreement":null},{"id":"W4317754467","doi":"10.3389/fendo.2023.1104746","title":"Editorial: Mechanistic, machine learning and hybrid models of the “other” endocrine regulatory systems in health &amp; disease","year":2023,"lang":"en","type":"editorial","venue":"Frontiers in Endocrinology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Disease; Endocrine system; Computational biology; Bioinformatics; Endocrine disease; Medicine; Computer science; Biology; Risk analysis (engineering); Hormone; Endocrinology; Internal medicine","score_opus":0.007509417102120759,"score_gpt":0.24156245164646195,"score_spread":0.2340530345443412,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317754467","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016868403,0.027476473,0.0013873014,0.00015173681,0.96840644,0.00050699373,0.00033452504,0.000032553788,0.000017153267],"genre_scores_gemma":[0.033456963,0.016907556,0.00047076022,0.00002487765,0.9439447,0.00020617597,0.0012446893,0.00024551633,0.0034987389],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9958686,0.0009358724,0.0009063778,0.0009352647,0.0005327088,0.0008211277],"domain_scores_gemma":[0.99810547,0.00012033284,0.00062495813,0.00085828354,0.00012880829,0.00016214701],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00059940806,0.0004680828,0.0010485859,0.00039659403,0.0000967363,0.000019467318,0.00057979533,0.0004025806,0.0000026262105],"category_scores_gemma":[0.00077119406,0.00039344357,0.00020581212,0.00029305616,0.00026982665,0.0000056122435,0.0005769112,0.00089957024,0.0000015113588],"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":[0.00020357652,0.000048443533,0.002623295,0.00037684938,0.00020530625,0.000013536975,0.000023299464,0.024326162,0.00023414743,0.000078499135,0.97148675,0.00038013575],"study_design_scores_gemma":[0.0009775523,0.00009469638,0.000068155925,0.0001797316,0.00007629553,0.0000042238457,0.000049381244,0.004107018,0.0000786936,0.0008986647,0.99311954,0.00034605124],"about_ca_topic_score_codex":0.001824521,"about_ca_topic_score_gemma":0.0009490576,"teacher_disagreement_score":0.031770125,"about_ca_system_score_codex":0.00018908273,"about_ca_system_score_gemma":0.0005633296,"threshold_uncertainty_score":0.99985176},"labels":[],"label_agreement":null},{"id":"W4319299128","doi":"10.1101/2023.02.05.525388","title":"Noise properties of adaptation-conferring biochemical control modules","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Connaught Fund; University of Toronto","keywords":"Robustness (evolution); Limit (mathematics); Adaptation (eye); Noise (video); Control theory (sociology); Synthetic biology; Computer science; Control (management); Biological system; Physics; Mathematics; Biology; Bioinformatics; Artificial intelligence; Mathematical analysis","score_opus":0.018911464434292174,"score_gpt":0.20708821391333862,"score_spread":0.18817674947904645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319299128","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":[0.9876406,0.004150017,0.006919284,0.0000987301,0.00042178063,0.00048859173,0.00014688798,0.00013184182,0.0000022605416],"genre_scores_gemma":[0.9967094,0.0003717725,0.0018598583,0.000055762688,0.0006240185,0.0001934106,0.0000025925922,0.00016653548,0.00001664573],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9972543,0.00014390431,0.0006876625,0.0010516405,0.00037579887,0.00048669474],"domain_scores_gemma":[0.9971735,0.000015393463,0.00049143634,0.0014584766,0.0006594217,0.00020178451],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00044970054,0.00053412816,0.0006771595,0.00022310624,0.00009225469,0.00006937874,0.00062263815,0.0006990871,0.000008132692],"category_scores_gemma":[0.0002490975,0.0005592187,0.00037845538,0.0002969551,0.00022311407,0.0000068896356,0.00053445407,0.00032599826,0.000024957939],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006252136,0.00006905642,0.0035042623,0.0003234326,0.0006300859,0.0000053736503,0.0000055876562,0.01005919,0.9849708,0.000040270144,0.0003281949,0.0000012231849],"study_design_scores_gemma":[0.0005209075,0.000045544737,0.01429279,0.00029843388,0.000294152,1.2231164e-8,0.0000071426985,0.007823591,0.97558063,0.0000016939246,0.00051061437,0.0006245088],"about_ca_topic_score_codex":0.000060376853,"about_ca_topic_score_gemma":0.000006369109,"teacher_disagreement_score":0.010788527,"about_ca_system_score_codex":0.000065186054,"about_ca_system_score_gemma":0.0004665213,"threshold_uncertainty_score":0.99968594},"labels":[],"label_agreement":null},{"id":"W4319792166","doi":"","title":"Stochastic single gene expression model: analytical results on bursting models","year":2018,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Bursting; Stochastic modelling; Computer science; Expression (computer science); Stochastic process; Computational biology; Artificial intelligence; Neuroscience; Biology; Mathematics; Statistics; Programming language","score_opus":0.02543292582893598,"score_gpt":0.2454892398291326,"score_spread":0.22005631400019662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319792166","genre_codex":"methods","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":[0.347336,0.00053307664,0.6402397,0.0009085667,0.00010501869,0.00026407168,0.0000909501,0.00007926066,0.010443323],"genre_scores_gemma":[0.95667565,0.0000981832,0.036898497,0.00007063432,0.00013605983,0.00003535288,0.0015266518,0.000074443116,0.004484508],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9947538,0.0024123476,0.0006113676,0.0013143787,0.00047071226,0.0004374293],"domain_scores_gemma":[0.9944825,0.0002647034,0.00051101495,0.002930424,0.0015672814,0.00024407195],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0034793066,0.0004228116,0.0003953694,0.00016078581,0.00029538153,0.00018078994,0.0010094263,0.00054672343,0.000014837459],"category_scores_gemma":[0.0013707614,0.0004429228,0.000329933,0.00020846674,0.0002465079,0.000008655396,0.001676267,0.000403105,0.000016087719],"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":[0.0002182986,0.0007354606,0.000046880064,0.000062613784,0.00023918036,0.0000033819213,0.0010362111,0.7883709,0.19932336,0.0015717606,0.0046146405,0.003777308],"study_design_scores_gemma":[0.0003681645,0.0000018153419,0.000031185566,0.0006182202,0.00008526473,0.000003471559,0.000013907493,0.6959917,0.3003773,0.0018356632,0.0002894184,0.00038390188],"about_ca_topic_score_codex":0.000057306388,"about_ca_topic_score_gemma":0.00012933531,"teacher_disagreement_score":0.60933965,"about_ca_system_score_codex":0.00009218948,"about_ca_system_score_gemma":0.00023479972,"threshold_uncertainty_score":0.99980223},"labels":[],"label_agreement":null},{"id":"W4319872356","doi":"10.1016/j.bpj.2022.11.390","title":"Laws: Local alignment of water sites—Describing allosteric water networks in enzymes","year":2023,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Allosteric regulation; Protein dynamics; Biological system; Molecular dynamics; Function (biology); Computer science; Chemistry; Computational biology; Biology; Enzyme; Computational chemistry; Biochemistry; Genetics","score_opus":0.015743018219054328,"score_gpt":0.22786658500319246,"score_spread":0.21212356678413813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319872356","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":[0.99702495,0.00011294917,0.0024149267,0.00021121022,0.00012565704,0.00005880921,0.0000017606235,0.000008955112,0.00004077189],"genre_scores_gemma":[0.9987819,0.00011626706,0.000064143365,0.000096666896,0.00062268967,0.0000049657874,0.00008914939,0.000024557809,0.00019964113],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99853384,0.00011527753,0.00036864894,0.0002534451,0.00022589866,0.0005028943],"domain_scores_gemma":[0.99952865,0.0000073045157,0.00005763501,0.00022835442,0.000056928326,0.000121104116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030284925,0.00017054183,0.00025678606,0.000095214484,0.000065017295,0.000029827142,0.00021119688,0.00012787999,0.000044515746],"category_scores_gemma":[0.0000045390207,0.00010895787,0.00023575155,0.00016457358,0.00009901406,0.000006358296,0.00022440316,0.00014723613,0.000046859972],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005501552,0.00006664578,0.0012329496,0.0000068829,0.00010529313,0.000036488087,0.00007136978,0.031308483,0.96493113,0.000010626085,0.00088930415,0.0012858313],"study_design_scores_gemma":[0.0004442897,0.00017855346,0.0013346995,0.000025412122,0.00004217837,0.000029361165,0.00009847313,0.011593091,0.9843394,0.000046752513,0.0016693776,0.00019837242],"about_ca_topic_score_codex":0.0000072864486,"about_ca_topic_score_gemma":0.0000080404525,"teacher_disagreement_score":0.019715393,"about_ca_system_score_codex":0.00002964338,"about_ca_system_score_gemma":0.000014898537,"threshold_uncertainty_score":0.4443173},"labels":[],"label_agreement":null},{"id":"W4320855101","doi":"","title":"Synchronism versus asynchronism in monotonic Boolean automata networks","year":2018,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Compute Canada","funders":"","keywords":"Synchronism; Monotonic function; Automaton; Computer science; Theoretical computer science; Mathematics; Computer network","score_opus":0.007243986950734294,"score_gpt":0.22057549838070842,"score_spread":0.2133315114299741,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4320855101","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":[0.8547712,0.0024625806,0.10603922,0.0018486568,0.0003098062,0.00030991525,0.000008140418,0.00011034264,0.034140144],"genre_scores_gemma":[0.99056554,0.00046183102,0.0059796683,0.000077202974,0.00010739159,0.000026026762,0.00018523505,0.00003910871,0.002557994],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.996886,0.0015474897,0.0003334552,0.00060510787,0.00020018619,0.00042777543],"domain_scores_gemma":[0.9974361,0.00013048704,0.00017237407,0.0016040321,0.00051662663,0.0001403934],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0020139706,0.00022003458,0.00020741543,0.000098867626,0.00023540022,0.000100227946,0.00068695325,0.00022059196,0.00009284741],"category_scores_gemma":[0.0002731851,0.0002463725,0.00014015689,0.00037253046,0.00033246336,0.000012094022,0.0004288748,0.00016899605,0.000049587605],"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":[0.00086970866,0.0029155447,0.030700067,0.00018264222,0.0018201959,0.00005821446,0.0066510714,0.016837755,0.29211527,0.0721404,0.03322911,0.54248],"study_design_scores_gemma":[0.0054995697,0.000014705831,0.021110792,0.00043967832,0.00014993847,0.000026854206,0.00017521986,0.44868103,0.40409493,0.0006487623,0.11780006,0.0013584709],"about_ca_topic_score_codex":0.00023721375,"about_ca_topic_score_gemma":0.0045496146,"teacher_disagreement_score":0.54112154,"about_ca_system_score_codex":0.0001074753,"about_ca_system_score_gemma":0.00019329833,"threshold_uncertainty_score":0.99999887},"labels":[],"label_agreement":null},{"id":"W4320857030","doi":"10.1007/7651_2022_465","title":"Inferring Gene Regulatory Networks and Predicting the Effect of Gene Perturbations via IQCELL","year":2023,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"","keywords":"Gene regulatory network; Computational biology; Gene; Boolean network; Computer science; Data mining; Biology; Boolean function; Theoretical computer science; Genetics; Gene expression; Algorithm","score_opus":0.009112959948269148,"score_gpt":0.3147128918060493,"score_spread":0.3055999318577801,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4320857030","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":[0.57741386,0.003006823,0.41918784,0.00004324274,0.00010959333,0.000174899,0.000002348474,0.00001605779,0.000045324156],"genre_scores_gemma":[0.9313262,0.0002910253,0.06781069,0.00008811893,0.00017100912,0.00007620698,0.000116662006,0.000042139684,0.000077950026],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9969187,0.0017659587,0.00038723243,0.00047876328,0.000081515514,0.00036784564],"domain_scores_gemma":[0.9988719,0.00024318794,0.00015571521,0.0006225618,0.00004563548,0.000060965936],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024520124,0.00021910743,0.00034890661,0.00015997111,0.00010106923,0.000009219862,0.00026628815,0.00031518075,0.000004431964],"category_scores_gemma":[0.00033562738,0.00017045092,0.00015937416,0.00053229375,0.00025379652,0.0000022105728,0.00029354426,0.0001771539,9.230022e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020371408,0.000005578424,0.03995802,0.000010796491,0.00011382723,0.0000036809695,0.000029492172,0.030052973,0.91664815,0.000032972475,0.000021573283,0.013102575],"study_design_scores_gemma":[0.00041162374,0.0002568948,0.01763321,0.000011460746,0.00010364941,0.000022702625,0.000017344842,0.051664438,0.92892754,0.0002649539,0.0004894469,0.00019672465],"about_ca_topic_score_codex":0.000021216509,"about_ca_topic_score_gemma":0.000011400059,"teacher_disagreement_score":0.35391235,"about_ca_system_score_codex":0.000014772136,"about_ca_system_score_gemma":0.000022574057,"threshold_uncertainty_score":0.6950787},"labels":[],"label_agreement":null},{"id":"W4321596276","doi":"10.1242/dev.201647","title":"New wave theory","year":2023,"lang":"en","type":"article","venue":"Development","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Morphogen; Biology; Mathematical and theoretical biology; Mechanism (biology); Turing; Cognitive science; Heterochrony; Computer science; Epistemology; Bioinformatics","score_opus":0.012812242987590284,"score_gpt":0.22382776193705856,"score_spread":0.21101551894946827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321596276","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":[0.9837674,0.0004325467,0.011357168,0.00017436048,0.00020375226,0.00009399169,8.844062e-7,0.00006477661,0.0039051317],"genre_scores_gemma":[0.9370506,0.000072110844,0.008277162,0.0002319084,0.0002729555,0.00001511288,0.00021210425,0.000024523211,0.05384352],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993658,0.000025006,0.00011356344,0.00020419671,0.0001038523,0.00018759388],"domain_scores_gemma":[0.99966747,0.0000044412964,0.000024309773,0.00020279548,0.000020716718,0.00008026454],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020873155,0.00008502309,0.00007060939,0.00004682611,0.000056504196,0.000009561215,0.00008950938,0.000057736168,0.0001079737],"category_scores_gemma":[0.0000143753705,0.00008006872,0.000046557256,0.00018350207,0.0000108448485,6.3036964e-7,0.00011425328,0.000024722196,0.00035407874],"study_design_candidate":"not_applicable","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":[0.000060045128,0.000029516183,0.00574724,0.000017252087,0.0006817103,0.0000313887,0.00063870667,0.0009831055,0.18614939,0.0012477511,0.3306632,0.47375068],"study_design_scores_gemma":[0.00020258143,0.000017612927,0.036563825,0.0000050448225,0.000013608987,0.0000048454617,0.00006820384,0.000048720714,0.20690313,0.000517182,0.75545025,0.00020500571],"about_ca_topic_score_codex":9.704623e-7,"about_ca_topic_score_gemma":0.000009222483,"teacher_disagreement_score":0.47354567,"about_ca_system_score_codex":0.000012461209,"about_ca_system_score_gemma":0.00015557918,"threshold_uncertainty_score":0.4551084},"labels":[],"label_agreement":null},{"id":"W4322628704","doi":"10.32614/rj-2023-018","title":"pCODE: Estimating Parameters of ODE Models","year":2023,"lang":"en","type":"article","venue":"The R Journal","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Simon Fraser University","funders":"","keywords":"Ode; Hessian matrix; Jacobian matrix and determinant; Ordinary differential equation; Computer science; Cascade; Applied mathematics; Mathematical optimization; Estimation theory; Dynamical systems theory; Algorithm; Mathematics; Differential equation; Mathematical analysis","score_opus":0.025500838565008076,"score_gpt":0.2606199628272761,"score_spread":0.23511912426226805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4322628704","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":[0.97165626,0.00039945796,0.027444812,0.00018619077,0.0000991278,0.0000300778,0.0000015871477,0.000006616417,0.00017588772],"genre_scores_gemma":[0.99355084,0.00018818027,0.0057856794,0.00004411884,0.00017583117,0.0000010502081,0.000005569226,0.000012052324,0.00023669921],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993478,0.000096565585,0.00018176876,0.000073957766,0.00013580082,0.0001640766],"domain_scores_gemma":[0.99952745,0.000019267598,0.0001272101,0.00022403475,0.00005655353,0.000045479785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006405525,0.00006753515,0.000096164724,0.000039011906,0.00011116346,0.00001137578,0.0002168347,0.00004155699,0.000007584111],"category_scores_gemma":[0.00004004723,0.00004613035,0.00010677946,0.0001602037,0.000051666695,0.000002235813,0.00007253435,0.000088902016,0.000007505387],"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":[0.000020605294,0.000007657997,0.00044448164,0.0000051969364,0.00015540993,0.0000020716382,0.000121463505,0.8824244,0.106743336,0.000018214247,0.0038417513,0.0062153875],"study_design_scores_gemma":[0.0004519156,0.00015254639,0.0013431652,0.000039099727,0.00022455373,0.00024589984,0.00039094206,0.90604544,0.083217606,0.0070879795,0.00057319424,0.00022766204],"about_ca_topic_score_codex":0.0000040994164,"about_ca_topic_score_gemma":0.0000037559396,"teacher_disagreement_score":0.023621015,"about_ca_system_score_codex":0.0000056050994,"about_ca_system_score_gemma":0.0000349532,"threshold_uncertainty_score":0.1881141},"labels":[],"label_agreement":null},{"id":"W4323657381","doi":"10.1021/acs.jpcb.2c08932","title":"Estimating and Assessing Differential Equation Models with Time-Course Data","year":2023,"lang":"en","type":"article","venue":"The Journal of Physical Chemistry B","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Ode; Ordinary differential equation; Inference; Context (archaeology); Computer science; Computation; Range (aeronautics); Numerical integration; Process (computing); Gaussian process; Algorithm; Applied mathematics; Differential equation; Mathematics; Gaussian; Artificial intelligence","score_opus":0.025973533166404113,"score_gpt":0.2841962312619223,"score_spread":0.2582226980955182,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323657381","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":[0.983159,0.00008571118,0.01653282,0.000106847394,0.000010752245,0.000022507906,0.000003930517,0.0000053682693,0.00007302897],"genre_scores_gemma":[0.99839544,0.00001010036,0.00057115004,0.000007549047,0.00082723325,4.376606e-7,0.00006529968,0.000013414941,0.00010937048],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99936336,0.000041356212,0.00014215097,0.00012528311,0.00020394962,0.00012389084],"domain_scores_gemma":[0.99929386,0.000037100817,0.00020027487,0.00033922255,0.00007290703,0.000056658562],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026407876,0.00009650639,0.00014192688,0.0000085096135,0.000081739556,0.00003637578,0.0002862497,0.000036805024,0.000004647768],"category_scores_gemma":[0.000030106045,0.000060534432,0.00004134766,0.00010424692,0.00007705894,0.000016131828,0.00018204092,0.000110089655,0.0000015453663],"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":[0.00003188984,0.000030767726,0.00005150489,0.000016152293,0.00013373117,0.0000020393625,0.000040466217,0.07884729,0.9190112,0.000001440082,0.00037257862,0.0014609443],"study_design_scores_gemma":[0.00025891012,0.000046561294,0.0003108135,0.00003521116,0.00029158936,0.000040559444,0.00006184175,0.88355637,0.11501522,0.00027085317,0.000019292762,0.000092804046],"about_ca_topic_score_codex":8.9561433e-7,"about_ca_topic_score_gemma":2.0585276e-7,"teacher_disagreement_score":0.8047091,"about_ca_system_score_codex":0.0000055582173,"about_ca_system_score_gemma":0.000054398613,"threshold_uncertainty_score":0.24685225},"labels":[],"label_agreement":null},{"id":"W4362559906","doi":"10.3390/e25040609","title":"Cell Decision Making through the Lens of Bayesian Learning","year":2023,"lang":"en","type":"article","venue":"Entropy","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Khalifa University of Science, Technology and Research; Volkswagen Foundation","keywords":"Bayesian probability; Principle of maximum entropy; Computer science; Statistical physics; Entropy (arrow of time); Mesoscopic physics; State variable; Artificial intelligence; Biological system; Physics; Biology","score_opus":0.008996203958036948,"score_gpt":0.25231150976237215,"score_spread":0.24331530580433522,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362559906","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":[0.97282904,0.0010085801,0.023710737,0.000150015,0.000112031244,0.00007370785,0.0000016287476,0.000020922787,0.0020933177],"genre_scores_gemma":[0.99795544,0.00023429454,0.00094993797,0.00005531539,0.000171472,0.0000034551701,0.000019067045,0.000016108308,0.00059490325],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99929947,0.00006835165,0.00014218752,0.00018012944,0.00013365503,0.00017620441],"domain_scores_gemma":[0.99955493,0.000029183677,0.00008110557,0.00028932453,0.000030849264,0.000014588089],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014503996,0.00007989894,0.000095908894,0.000024237876,0.000098481265,0.000009753151,0.00016182281,0.00006127781,0.000057475754],"category_scores_gemma":[0.00004309798,0.00005926849,0.00012329509,0.00022099876,0.000040665236,0.0000017538199,0.000114875955,0.0000661115,0.000036988877],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008978629,0.00004303952,0.016503753,0.000025003526,0.00017811298,0.000007487907,0.00047786173,0.118377924,0.83161676,0.0012218017,0.022875983,0.008582457],"study_design_scores_gemma":[0.0012632126,0.0004701939,0.023857418,0.000093756054,0.0002627936,0.000011434313,0.0015328977,0.024887992,0.51267064,0.0038944697,0.4303856,0.000669624],"about_ca_topic_score_codex":0.0000035925682,"about_ca_topic_score_gemma":0.000004389332,"teacher_disagreement_score":0.40750962,"about_ca_system_score_codex":0.0000058681017,"about_ca_system_score_gemma":0.000017349948,"threshold_uncertainty_score":0.24168988},"labels":[],"label_agreement":null},{"id":"W4362717777","doi":"10.1093/synbio/ysad006","title":"Functional Synthetic Biology","year":2023,"lang":"en","type":"review","venue":"Synthetic Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Synthetic biology; Modular design; Flexibility (engineering); Reuse; Computer science; Predictability; Variety (cybernetics); Function (biology); Systems engineering; Software engineering; Biochemical engineering; Risk analysis (engineering); Data science; Artificial intelligence; Engineering; Computational biology; Biology; Ecology","score_opus":0.043722383180891757,"score_gpt":0.31172376800728746,"score_spread":0.2680013848263957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362717777","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00007273365,0.99579966,0.0010178088,0.000069308735,0.001410164,0.0005193005,0.00021920932,0.00011181977,0.0007800025],"genre_scores_gemma":[0.0005013156,0.99098647,0.00015655263,0.000070490125,0.0013951831,0.00034989958,0.0028625117,0.00020367544,0.0034738865],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9953072,0.0009325945,0.001001578,0.0017102265,0.00012378121,0.00092460896],"domain_scores_gemma":[0.99737245,0.00020844932,0.00053080346,0.0015723569,0.00010814367,0.00020778997],"candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006802118,0.00087166345,0.0020959163,0.0004246771,0.00018084439,0.000023589033,0.0008113449,0.0020129706,0.00041737626],"category_scores_gemma":[0.00030426745,0.00071323477,0.0014559855,0.00054376485,0.0006410962,0.0000016203119,0.00059389824,0.000435124,0.0020520424],"study_design_candidate":"not_applicable","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":[0.000022768856,0.00010318421,0.000042133946,0.0023834258,0.0028514552,0.000011355029,0.0000059062186,0.000022355867,0.0009252221,0.0027108653,0.0077020647,0.98321927],"study_design_scores_gemma":[0.00013319004,0.00018376499,0.0000043585787,0.00064770295,0.0011730856,0.0001542105,0.0000065708787,0.000010280968,0.00007042471,0.00080692745,0.9960936,0.00071592],"about_ca_topic_score_codex":0.000016220469,"about_ca_topic_score_gemma":0.000026426767,"teacher_disagreement_score":0.9883915,"about_ca_system_score_codex":0.000069764916,"about_ca_system_score_gemma":0.00044450615,"threshold_uncertainty_score":0.99953187},"labels":[],"label_agreement":null},{"id":"W4377138263","doi":"10.1007/s11071-023-08547-y","title":"A confidence ellipse analysis for stochastic dynamics model of Alzheimer's disease","year":2023,"lang":"en","type":"article","venue":"Nonlinear Dynamics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Bistability; Ergodic theory; Statistical physics; Noise (video); Uniqueness; Mathematics; Applied mathematics; Computer science; Physics; Mathematical analysis; Artificial intelligence; Quantum mechanics","score_opus":0.019016476158950423,"score_gpt":0.2732150358806373,"score_spread":0.25419855972168687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4377138263","genre_codex":"methods","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":[0.41475296,0.00021792426,0.58373547,0.00010131563,0.000046788435,0.00021805851,0.00088185444,0.000027422122,0.000018208284],"genre_scores_gemma":[0.987099,0.00009085294,0.0064961826,0.000051542644,0.00010941394,0.00004167728,0.005456428,0.00004729159,0.0006076248],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99856704,0.000032465497,0.00037598782,0.0004705616,0.00022235436,0.0003315618],"domain_scores_gemma":[0.99863845,0.000031039966,0.00018910562,0.00070345536,0.0002611201,0.00017683905],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024518056,0.00021095067,0.00035836504,0.00024300494,0.00007698439,0.000015644975,0.000286727,0.00014621713,0.0000038532025],"category_scores_gemma":[0.00009744365,0.00022536081,0.0005367378,0.00084394444,0.000116855386,0.0000039252445,0.0001318451,0.0000660429,0.0000061888695],"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":[0.00008407312,0.000051330724,0.0014537948,0.000022846709,0.0012179494,0.0000010831868,0.00001301329,0.99443376,0.0014388793,0.0008110298,0.00008425766,0.0003879586],"study_design_scores_gemma":[0.00025337934,0.000052611824,0.00047168622,0.000007001376,0.0022046524,3.9087033e-7,0.00005154904,0.99545664,0.00047718888,0.00077514094,0.000021635895,0.00022811949],"about_ca_topic_score_codex":0.000014303309,"about_ca_topic_score_gemma":0.00066620304,"teacher_disagreement_score":0.5772393,"about_ca_system_score_codex":0.000034255045,"about_ca_system_score_gemma":0.00017641409,"threshold_uncertainty_score":0.9189947},"labels":[],"label_agreement":null},{"id":"W4379389544","doi":"10.46299/isg.p.2023.1.22","title":"MODERN THEORIES AND IMPROVEMENT OF WORLD METHODS","year":2023,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":31,"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":"Horizon 2020 Framework Programme; Universidad Nacional Agraria La Molina; Taras Shevchenko National University of Kyiv; Lviv Polytechnic National University; University of Alberta","keywords":"Computer science","score_opus":0.010357679845404186,"score_gpt":0.2990696216392403,"score_spread":0.2887119417938361,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4379389544","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":[0.96668637,0.0007194793,0.029417977,0.0001142736,0.000041731357,0.00006710962,0.000002477441,0.000017044818,0.002933532],"genre_scores_gemma":[0.9855017,0.00012504673,0.0060373275,0.000056513694,0.000042650205,0.0000068275212,0.000016069735,0.000008360901,0.008205485],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995532,0.000029507359,0.00010700258,0.00015665876,0.000050186434,0.0001034161],"domain_scores_gemma":[0.9996935,0.000010423924,0.000032057786,0.00020478813,0.000028778377,0.000030433095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002730762,0.00006171866,0.00009396704,0.00005001379,0.000022572536,0.0000050543,0.00005826243,0.000031203657,0.000020489288],"category_scores_gemma":[0.000013259989,0.000050775554,0.00004844489,0.00016538189,0.000050988543,6.819383e-7,0.00012091488,0.000015871958,0.0000015411287],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009014848,0.0000062620525,0.0017973522,0.00000992909,0.000094538096,1.8514878e-7,0.000022064229,0.00028010635,0.9443913,0.0011015433,0.00071419845,0.051573504],"study_design_scores_gemma":[0.0001344702,0.00006846383,0.0022774446,0.0000021549188,0.000033861335,5.10247e-7,0.000076376804,0.0030061456,0.9812945,0.006980208,0.0060331393,0.00009272964],"about_ca_topic_score_codex":0.0000063921984,"about_ca_topic_score_gemma":0.000043404314,"teacher_disagreement_score":0.051480774,"about_ca_system_score_codex":0.0000018421207,"about_ca_system_score_gemma":0.000011318976,"threshold_uncertainty_score":0.2070567},"labels":[],"label_agreement":null},{"id":"W4379512678","doi":"10.1017/nws.2023.11","title":"Exact recovery of Granger causality graphs with unconditional pairwise tests","year":2023,"lang":"en","type":"article","venue":"Network Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"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 Waterloo","funders":"","keywords":"Pairwise comparison; Granger causality; Causality (physics); Heuristics; Heuristic; Mathematics; Graph; Computer science; Theoretical computer science; Mathematical optimization; Artificial intelligence; Econometrics","score_opus":0.010503109158524485,"score_gpt":0.24564266366614398,"score_spread":0.2351395545076195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4379512678","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":[0.99844944,0.00022603478,0.0003479413,0.000069150694,0.00014461835,0.000093201495,0.000016710073,0.0000263963,0.00062650704],"genre_scores_gemma":[0.99838936,0.00008723343,0.00072329864,0.00008836474,0.0001948356,0.00001321943,0.00010466995,0.0000118357475,0.00038715414],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99847883,0.000049429258,0.00018274313,0.0004522412,0.00043338467,0.00040335167],"domain_scores_gemma":[0.9990695,0.00003104943,0.00012197364,0.0004822766,0.00018001969,0.000115191775],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085528544,0.00012794888,0.00015246992,0.000099946374,0.00018382375,0.000021091657,0.0003194445,0.00006459158,0.00003114425],"category_scores_gemma":[0.000063173946,0.00010700903,0.0000923739,0.0021345238,0.00063609285,0.000010536409,0.0001255949,0.000056706445,0.00001343912],"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":[0.00016482912,0.0001300835,0.42309573,0.00003992545,0.00021188188,0.00002206474,0.0000448501,0.30989763,0.18741183,0.0007658609,0.07254544,0.005669849],"study_design_scores_gemma":[0.000443367,0.00054766954,0.9617661,0.00007714281,0.00008491738,0.000024391245,0.00004099068,0.002509605,0.023022484,0.003863653,0.007112662,0.0005069852],"about_ca_topic_score_codex":0.000014808998,"about_ca_topic_score_gemma":0.00009748959,"teacher_disagreement_score":0.53867036,"about_ca_system_score_codex":0.000016349926,"about_ca_system_score_gemma":0.00024839657,"threshold_uncertainty_score":0.43637016},"labels":[],"label_agreement":null},{"id":"W4380085615","doi":"10.1063/5.0150292","title":"Parameter estimation for the reaction–diffusion master equation","year":2023,"lang":"en","type":"article","venue":"AIP Advances","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Iterated function; Master equation; Diffusion; Series (stratigraphy); Reaction–diffusion system; Computer science; Estimation theory; Applied mathematics; Statistical physics; Chemical reaction; Reaction rate; Chemical kinetics; Discrete time and continuous time; Algorithm; Mathematics; Statistics; Chemistry; Physics; Thermodynamics; Mathematical analysis; Kinetics","score_opus":0.0249748446552098,"score_gpt":0.2813953309130918,"score_spread":0.25642048625788205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380085615","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":[0.66125876,0.0019894256,0.33478385,0.0010688106,0.00038180893,0.00036109882,0.0000063036578,0.000042723517,0.00010718581],"genre_scores_gemma":[0.995281,0.0005751937,0.0024293484,0.0001509818,0.0002366659,0.00010581183,0.00021722764,0.000012183192,0.0009915946],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99950725,0.000021317699,0.00010390107,0.00016970148,0.00008193958,0.000115895804],"domain_scores_gemma":[0.99960595,0.000068418565,0.00006143334,0.00020449347,0.000042771102,0.000016905393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000155976,0.000066018336,0.000055206747,0.00002777072,0.0001216259,0.000015363717,0.00007522825,0.000045056106,0.0000049861446],"category_scores_gemma":[0.0000879396,0.000047016427,0.000068822315,0.00013309003,0.000025472715,0.0000069853468,0.000027896269,0.000021219272,0.000024697685],"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":[0.00011977261,0.00003133497,0.0043789833,0.000035357636,0.00013945937,4.3287847e-7,0.00007705271,0.083556585,0.49162492,0.0002226021,0.007817124,0.41199636],"study_design_scores_gemma":[0.0006224872,0.00024465928,0.023736577,0.00001856398,0.0001691761,0.000004043765,0.00024642024,0.4097202,0.0796306,0.0065706894,0.47871467,0.00032190996],"about_ca_topic_score_codex":0.0000020599582,"about_ca_topic_score_gemma":0.000019159497,"teacher_disagreement_score":0.47089756,"about_ca_system_score_codex":0.000007186629,"about_ca_system_score_gemma":0.00001003536,"threshold_uncertainty_score":0.19172743},"labels":[],"label_agreement":null},{"id":"W4380870251","doi":"10.2144/btn-2023-0039","title":"Multiscale Computational Modeling Offers Key to Understanding Molecular Logic Underpinning Development and Disease","year":2023,"lang":"en","type":"article","venue":"BioTechniques","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Royal Academy of Engineering; Michael Smith Health Research BC","keywords":"Underpinning; Key (lock); Development (topology); Computer science; Computational biology; Data science; Biology; Engineering; Mathematics","score_opus":0.04504704135137197,"score_gpt":0.2834783786868211,"score_spread":0.2384313373354491,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380870251","genre_codex":"methods","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":[0.43123195,0.00015900012,0.5678548,0.0004969567,0.000012664146,0.0001163979,0.0000026200755,0.000085674605,0.000039891223],"genre_scores_gemma":[0.95308137,0.000039690876,0.046297356,0.00032929934,0.000031014722,0.0000243081,0.000121173834,0.000022273141,0.00005350891],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990844,0.000034406676,0.00016261848,0.00035539953,0.00014810845,0.00021505951],"domain_scores_gemma":[0.9995799,0.000006620706,0.00003083819,0.00015800042,0.000028129643,0.00019648724],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017518987,0.00013793696,0.000109988316,0.00013908918,0.00013697258,0.000033734686,0.00009489796,0.00009823302,0.000002014819],"category_scores_gemma":[0.000030527328,0.00014440769,0.000050576582,0.00022132283,0.00003444339,0.0000030579693,0.00017720653,0.00004724713,0.0000051629913],"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":[0.00009342067,0.000047732854,0.0026193561,0.00008363314,0.00024345331,0.000046126395,0.00029844907,0.689959,0.29453605,0.0070220795,0.0021716172,0.0028791137],"study_design_scores_gemma":[0.00059095613,0.00019580535,0.0029023488,0.00021877755,0.0001106876,0.000010513333,0.00051511475,0.69960487,0.2594391,0.030303454,0.004727498,0.0013808326],"about_ca_topic_score_codex":0.0000045833594,"about_ca_topic_score_gemma":0.0000054645952,"teacher_disagreement_score":0.5218494,"about_ca_system_score_codex":0.00006201923,"about_ca_system_score_gemma":0.00007691933,"threshold_uncertainty_score":0.5888775},"labels":[],"label_agreement":null},{"id":"W4381620438","doi":"10.1016/j.matcom.2023.06.014","title":"Noisy prediction-based control leading to stability switch","year":2023,"lang":"en","type":"article","venue":"Mathematics and Computers in Simulation","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bounded function; Mathematics; Differentiable function; Stability (learning theory); Independent and identically distributed random variables; Domain (mathematical analysis); Chaotic; Derivative (finance); Applied mathematics; Exponential stability; Control theory (sociology); Variable (mathematics); Random variable; Control (management); Mathematical analysis; Computer science; Statistics; Nonlinear system","score_opus":0.015043834182687307,"score_gpt":0.25628734574397205,"score_spread":0.24124351156128473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4381620438","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":[0.71918535,0.000014518632,0.28046787,0.00006793727,0.000049557355,0.0001524297,0.000004140022,0.000020094041,0.000038126127],"genre_scores_gemma":[0.9954629,0.0000023796294,0.0042899665,0.00009849832,0.000068800306,0.000013567802,0.000036171492,0.000011432481,0.000016312924],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999291,0.000027017171,0.00021416518,0.00022082748,0.00010820213,0.00013877302],"domain_scores_gemma":[0.99957114,0.00007699558,0.000045913606,0.00021071378,0.000044166853,0.00005108325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003202452,0.00009187989,0.00013850466,0.00009489528,0.00004989124,0.00002531478,0.00006470112,0.00006268287,0.000003406227],"category_scores_gemma":[0.00004245258,0.00009366348,0.00004266908,0.00025272332,0.000016271197,0.0000025452882,0.00003073133,0.000032744494,0.00000693616],"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":[0.000012741516,0.000030008896,0.017053662,0.0000353828,0.000019639097,5.91103e-7,0.0001461813,0.9684395,0.0124447225,0.000040556202,0.000096708296,0.0016802575],"study_design_scores_gemma":[0.00038975725,0.00005578112,0.008705228,0.000021948385,0.0000132286805,2.8275775e-7,0.00004114375,0.9887334,0.0013624023,0.00037173237,0.00021457396,0.00009052812],"about_ca_topic_score_codex":0.0000018962783,"about_ca_topic_score_gemma":0.0000104903975,"teacher_disagreement_score":0.2762775,"about_ca_system_score_codex":0.000017467906,"about_ca_system_score_gemma":0.000014338155,"threshold_uncertainty_score":0.3819486},"labels":[],"label_agreement":null},{"id":"W4381955460","doi":"10.1016/b978-0-443-21699-2.00001-5","title":"Acquiring and analyzing nonmonotonic nonlinear dynamics","year":2023,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Nonlinear system; Linearization; Phenomenon; Statistical physics; Mathematics; Nyquist–Shannon sampling theorem; Entropy (arrow of time); Dynamics (music); Computer science; Physics; Mathematical analysis","score_opus":0.009033529495111202,"score_gpt":0.22707918798155538,"score_spread":0.21804565848644417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4381955460","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011669411,0.0051098606,0.0000905825,0.00005507885,0.00030486906,0.00041733767,0.00006170056,0.000071415925,0.98221976],"genre_scores_gemma":[0.005665278,0.0013800203,0.0006171732,0.000082052655,0.0006793444,0.000015071368,0.00037335543,0.00018766525,0.99100006],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99832946,0.000022351365,0.0003822767,0.00073701935,0.00018529192,0.00034360366],"domain_scores_gemma":[0.9988087,0.000014319053,0.00021870217,0.00073039526,0.00008050549,0.00014737765],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002361338,0.00043991892,0.00047912667,0.00015702244,0.00012897763,0.000049521528,0.00024970496,0.0005269064,0.00002067691],"category_scores_gemma":[0.000013122466,0.00046901725,0.00032631448,0.000023095936,0.00015445592,0.0000015767903,0.00043556988,0.0002472325,0.0000674721],"study_design_candidate":"design_other","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":[0.000018221352,0.00000427453,0.00019764395,0.00008904931,0.0008681923,0.000029456249,0.000021121572,0.000120788005,0.0019796235,0.0005125057,0.00009996398,0.9960592],"study_design_scores_gemma":[0.00038597884,0.00013053053,0.0001047493,0.00026724048,0.0007819273,0.00003751064,0.0000145891845,0.0034661498,0.0011584633,0.0013723919,0.9911053,0.0011751408],"about_ca_topic_score_codex":4.4765363e-7,"about_ca_topic_score_gemma":0.00019080177,"teacher_disagreement_score":0.994884,"about_ca_system_score_codex":0.00005104688,"about_ca_system_score_gemma":0.00009071455,"threshold_uncertainty_score":0.9997761},"labels":[],"label_agreement":null},{"id":"W4382065266","doi":"10.1137/22m149853x","title":"The Disguised Toric Locus and Affine Equivalence of Reaction Networks","year":2023,"lang":"en","type":"article","venue":"SIAM Journal on Applied Dynamical Systems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Affine transformation; Bijection; Dynamical systems theory; Mathematics; Equivalence (formal languages); Invertible matrix; Action (physics); Pure mathematics; Discrete mathematics; Physics","score_opus":0.006192741032119064,"score_gpt":0.22429849924276607,"score_spread":0.218105758210647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382065266","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":[0.9922239,0.0017384267,0.0041911914,0.00014238404,0.00064550404,0.00021962449,0.0000031911557,0.000021484917,0.00081430085],"genre_scores_gemma":[0.9974203,0.0012745594,0.000010734044,0.000011828212,0.00071388454,0.000013967398,0.000018073795,0.000020153291,0.0005164685],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99875695,0.00009334919,0.0003820769,0.00022408042,0.00026298905,0.00028054655],"domain_scores_gemma":[0.99920624,0.0000620627,0.00025694433,0.00028674095,0.000062489074,0.00012552069],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006412897,0.00014217084,0.00021311361,0.000052196057,0.00019897464,0.00005185677,0.00019296914,0.00014135413,0.0000016012267],"category_scores_gemma":[0.000032216736,0.0000956353,0.00010291577,0.0002925491,0.00008588357,0.0000021057065,0.000077683995,0.00018306909,0.0000064529963],"study_design_candidate":"simulation_or_modeling","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":[0.00070714403,0.00007752703,0.0015214843,0.00007244026,0.0005808316,0.000017079743,0.000033488566,0.21198009,0.747,0.005597098,0.0044607944,0.027952038],"study_design_scores_gemma":[0.006217689,0.0025046254,0.057528667,0.0005205089,0.00070012,0.00074482284,0.0018174044,0.8009047,0.010336757,0.001920061,0.11455852,0.0022461293],"about_ca_topic_score_codex":0.0000039666174,"about_ca_topic_score_gemma":0.000006276274,"teacher_disagreement_score":0.7366632,"about_ca_system_score_codex":0.000039124006,"about_ca_system_score_gemma":0.000022952987,"threshold_uncertainty_score":0.38998944},"labels":[],"label_agreement":null},{"id":"W4382340724","doi":"10.2139/ssrn.4489792","title":"Fundamental Trade-Off Between Speed of Switching and Robustness of Genetic Switches Limits Dynamic Control of Metabolism","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Robustness (evolution); Computer science; Control (management); Control theory (sociology); Biology; Genetics; Gene; Artificial intelligence","score_opus":0.010304071194515532,"score_gpt":0.2446415538921064,"score_spread":0.23433748269759086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382340724","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":[0.9320283,0.039350435,0.028050853,0.00010932869,0.00016355327,0.00023274125,0.000053741787,0.0000065512118,0.00000452546],"genre_scores_gemma":[0.9836216,0.015520405,0.0002659432,0.000004217932,0.00037688023,0.000003846315,0.00006222985,0.00007229641,0.00007261316],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9968018,0.00020110059,0.001049322,0.000481509,0.00038521682,0.0010810673],"domain_scores_gemma":[0.99792683,0.00003993965,0.0013200432,0.0004697568,0.0001337128,0.00010971303],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0012810997,0.0003865677,0.0010831988,0.00026369106,0.00006514173,0.000018147133,0.0005174114,0.00043420793,0.000002948203],"category_scores_gemma":[0.000047966067,0.00037749892,0.0005573136,0.00016770615,0.0001418459,0.000004831495,0.00025679305,0.0011530758,2.535996e-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":[0.00032585394,0.00016368339,0.08442927,0.0004460019,0.009561404,0.0000027456147,0.00015899098,0.122492746,0.75299317,0.00011713358,0.000015125558,0.029293848],"study_design_scores_gemma":[0.013630306,0.0032385697,0.6260093,0.0012790151,0.01770419,0.00071145507,0.004537696,0.04409577,0.24955003,0.03542376,0.00027217684,0.0035477362],"about_ca_topic_score_codex":0.00004996601,"about_ca_topic_score_gemma":0.0003244052,"teacher_disagreement_score":0.54158,"about_ca_system_score_codex":0.00011618749,"about_ca_system_score_gemma":0.0013722586,"threshold_uncertainty_score":0.9998677},"labels":[],"label_agreement":null},{"id":"W4382933023","doi":"10.1016/j.neunet.2023.06.035","title":"Safe control of logical control networks with random impulses","year":2023,"lang":"en","type":"article","venue":"Neural Networks","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Partition (number theory); Computer science; Domain (mathematical analysis); Control (management); State (computer science); State space; Control theory (sociology); Mathematics; Matrix (chemical analysis); Algorithm; Mathematical optimization; Artificial intelligence","score_opus":0.005887998308566379,"score_gpt":0.21510534223424385,"score_spread":0.20921734392567748,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382933023","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":[0.7842959,0.004113971,0.209615,0.00029934102,0.0004934082,0.00069175847,0.000021023228,0.00010781573,0.00036176314],"genre_scores_gemma":[0.9972674,0.0003019746,0.00006635258,0.000560518,0.0013063203,0.000037834547,0.00015499696,0.0000478619,0.00025673673],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99793077,0.0002483668,0.00043208746,0.00051720795,0.00024199895,0.0006295453],"domain_scores_gemma":[0.9987206,0.00012788067,0.00021953713,0.0005377458,0.00021849509,0.00017575522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035394082,0.00031508095,0.00058566977,0.00006766348,0.00011561942,0.000026336518,0.00030775595,0.00030914875,0.000047188165],"category_scores_gemma":[0.00006225749,0.00023764487,0.00031722916,0.0005120828,0.00022033737,0.0000050895965,0.000079918165,0.00021626947,0.0000060767215],"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":[0.0015233624,0.00003294252,0.018901506,0.000006606894,0.00035672061,0.000019569552,0.0000037204948,0.967116,0.0028558348,0.00001788936,0.0052786744,0.0038871698],"study_design_scores_gemma":[0.0071242773,0.0007076935,0.0148372,0.000019327454,0.00029968767,0.000021290276,0.000022129445,0.9730006,0.0005491615,0.000017623219,0.0030109354,0.0003901134],"about_ca_topic_score_codex":0.000008640117,"about_ca_topic_score_gemma":0.00003684771,"teacher_disagreement_score":0.2129715,"about_ca_system_score_codex":0.000009473504,"about_ca_system_score_gemma":0.000027055197,"threshold_uncertainty_score":0.96908766},"labels":[],"label_agreement":null},{"id":"W4385606554","doi":"10.3390/e25081168","title":"Quantifying Parameter Interdependence in Stochastic Discrete Models of Biochemical Systems","year":2023,"lang":"en","type":"article","venue":"Entropy","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Toronto Metropolitan University","keywords":"Sensitivity (control systems); Computer science; Inference; Singular value decomposition; Estimation theory; Collinearity; Stochastic modelling; Applied mathematics; Stochastic process; Mathematics; Mathematical optimization; Algorithm; Statistics; Artificial intelligence","score_opus":0.02703438862882992,"score_gpt":0.2780219583432249,"score_spread":0.250987569714395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385606554","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":[0.9697816,0.0008137644,0.029113302,0.000027186608,0.000111972964,0.000108214546,0.000007540899,0.000013397523,0.000023072209],"genre_scores_gemma":[0.99949837,0.000047200167,0.00016884788,0.000008372215,0.00007448446,0.000020397263,0.000057291018,0.000016683296,0.000108375556],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989984,0.0000603436,0.00026162996,0.00029088775,0.00014977217,0.00023895413],"domain_scores_gemma":[0.9994957,0.000023878216,0.00007806073,0.00031973605,0.000032559372,0.000050101822],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001739415,0.00011316268,0.00019399144,0.000098186676,0.000016909276,0.000012032615,0.00018254772,0.00009972036,0.00000515542],"category_scores_gemma":[0.0000590902,0.000106180436,0.00010226741,0.00025167855,0.000053370553,0.0000033234664,0.00013432732,0.000066857414,0.000013683754],"study_design_candidate":"simulation_or_modeling","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":[0.0000602069,0.000022685708,0.0029476113,0.000040654246,0.00008526738,0.0000060590687,0.00006836186,0.32892594,0.66671574,0.0004960976,0.0005545947,0.000076812554],"study_design_scores_gemma":[0.00067925686,0.0001287722,0.0016126741,0.00016563015,0.000060733477,0.000011261875,0.0003389041,0.8601484,0.13585128,0.00052759505,0.00010753199,0.00036797673],"about_ca_topic_score_codex":0.000028538523,"about_ca_topic_score_gemma":0.000010680132,"teacher_disagreement_score":0.53122246,"about_ca_system_score_codex":0.000014101274,"about_ca_system_score_gemma":0.000022107137,"threshold_uncertainty_score":0.43299127},"labels":[],"label_agreement":null},{"id":"W4385829651","doi":"10.1101/2023.08.13.553122","title":"Degeneracy in negative feedback (NFBL) and incoherent feedforward (IFFL) loops: Adaptation and resonance","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Consejo Nacional de Investigaciones Científicas y Técnicas; Division of Mathematical Sciences; York University; National Science Foundation","keywords":"Degeneracy (biology); Observable; Overshoot (microwave communication); Dynamical systems theory; Perturbation (astronomy); Statistical physics; Nonlinear system; Feedback loop; Control theory (sociology); Physics; Constant (computer programming); Computer science; Quantum mechanics; Artificial intelligence","score_opus":0.016844452868089298,"score_gpt":0.22297058083770593,"score_spread":0.20612612796961663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385829651","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":[0.9913013,0.0069786594,0.00060401886,0.00015708237,0.0002654223,0.0005350795,0.00008918129,0.00006556517,0.0000036754968],"genre_scores_gemma":[0.99157935,0.0038308038,0.0037510889,0.00009218502,0.00039009083,0.0001930582,0.0000033618844,0.0001271667,0.000032887056],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9971843,0.00020908315,0.0005317523,0.0013343843,0.0002628309,0.00047765012],"domain_scores_gemma":[0.9982858,0.000035243225,0.00034350718,0.0008587132,0.00027106138,0.0002057069],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00052200956,0.0005357249,0.0005402506,0.00024757747,0.00011938601,0.00013688886,0.00029002194,0.00061293127,0.0000051692878],"category_scores_gemma":[0.00019646392,0.00060335035,0.00010963539,0.00044986163,0.00018339769,0.000014103557,0.00081795536,0.00040301977,0.000011083727],"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":[0.00017025194,0.00012316706,0.09792733,0.00043373322,0.00045060366,0.000048316884,0.00007187661,0.003631254,0.896,0.000120405406,0.00090634375,0.0001166761],"study_design_scores_gemma":[0.0011794615,0.000121649966,0.7473893,0.00042624125,0.00018678888,6.097093e-8,0.000030657357,0.0074843685,0.23978281,0.000021534257,0.0022185454,0.001158559],"about_ca_topic_score_codex":0.00015555022,"about_ca_topic_score_gemma":0.00017272729,"teacher_disagreement_score":0.6562172,"about_ca_system_score_codex":0.00011330371,"about_ca_system_score_gemma":0.00031865004,"threshold_uncertainty_score":0.9996418},"labels":[],"label_agreement":null},{"id":"W4386410909","doi":"10.1101/2023.08.29.555255","title":"Exact solution of a three-stage model of stochastic gene expression including cell-cycle dynamics","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Queen's University","funders":"National Natural Science Foundation of China; Leverhulme Trust","keywords":"Messenger RNA; Stochastic modelling; Cell cycle; Translation (biology); Population; Dilution; Stochastic process; Biology; Mathematics; Statistical physics; Biological system; Statistics; Cell; Gene; Physics; Genetics; Thermodynamics","score_opus":0.023186378611123368,"score_gpt":0.234241824314788,"score_spread":0.21105544570366463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386410909","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":[0.7071796,0.0007188236,0.29116237,0.000012436599,0.00020343105,0.00031438077,0.0003538563,0.000052865824,0.0000022018],"genre_scores_gemma":[0.9891493,0.00018146622,0.0102019925,0.000009052687,0.00019665073,0.000073448406,0.000009317468,0.00016167025,0.000017148768],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9972438,0.0001042395,0.00076520734,0.000982113,0.00043395633,0.00047064354],"domain_scores_gemma":[0.9967307,0.000023161188,0.0009685708,0.0016412634,0.00046639837,0.00016989364],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005740502,0.0004987801,0.00068548054,0.00028657715,0.00011231523,0.000026671056,0.0006166814,0.00075186626,0.000006110188],"category_scores_gemma":[0.00010523271,0.0005677131,0.00036777303,0.00036585177,0.00014850887,0.000008861242,0.0013879916,0.0003294354,0.000004272336],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035859925,0.00007514148,0.0010854229,0.000313184,0.00013721746,0.0000017826036,0.0000033227689,0.30239746,0.69589657,0.000018455783,0.000034849225,7.655136e-7],"study_design_scores_gemma":[0.00025256193,0.000042374715,0.0014948482,0.00017825763,0.00016600957,3.8162753e-9,0.000002459238,0.34213975,0.6553489,0.0000058869523,0.0000040917625,0.000364872],"about_ca_topic_score_codex":0.000055588796,"about_ca_topic_score_gemma":0.00002516132,"teacher_disagreement_score":0.2819696,"about_ca_system_score_codex":0.00015567614,"about_ca_system_score_gemma":0.0005060402,"threshold_uncertainty_score":0.9996774},"labels":[],"label_agreement":null},{"id":"W4386417708","doi":"10.1101/2023.09.01.555799","title":"Exploiting fluctuations in gene expression to detect causal interactions between genes","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto; Connaught Fund; Concordia University; Government of Ontario","keywords":"Gene; Computational biology; Genetics; Gene expression; Biology; Expression (computer science); Computer science","score_opus":0.02352581856388541,"score_gpt":0.25909840989052574,"score_spread":0.23557259132664032,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386417708","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":[0.9803295,0.0006695946,0.01731033,0.00014894336,0.0006575788,0.0005473275,0.0001683771,0.00016582003,0.000002529106],"genre_scores_gemma":[0.9837676,0.00022146683,0.013644304,0.000065283144,0.0015872068,0.00048516758,0.000010168074,0.00019330102,0.000025469804],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9967754,0.00022561011,0.00070420327,0.0013525842,0.0003207906,0.00062142994],"domain_scores_gemma":[0.9975073,0.00005045067,0.0003116974,0.0014968126,0.00031607316,0.00031769395],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005475798,0.0005358173,0.0005431817,0.0005784031,0.00019634955,0.00012872067,0.00059065793,0.0005178198,0.000018252122],"category_scores_gemma":[0.00029867748,0.0006348035,0.00025019742,0.0007575412,0.000052148804,0.0000124983035,0.0011742366,0.00048360118,0.000094393356],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000124354965,0.000022861366,0.020850435,0.00004843086,0.00016061298,0.000013877882,0.0000068747986,0.0074074604,0.97110116,0.000002894919,0.0003648189,0.0000081579],"study_design_scores_gemma":[0.00019516068,0.000035144378,0.09789442,0.00017798514,0.000114119786,1.4592368e-8,0.000006648861,0.0001814465,0.89891064,0.0000029585317,0.0018549988,0.00062647974],"about_ca_topic_score_codex":0.00007117073,"about_ca_topic_score_gemma":0.00007968521,"teacher_disagreement_score":0.07704399,"about_ca_system_score_codex":0.00019311336,"about_ca_system_score_gemma":0.00035438538,"threshold_uncertainty_score":0.9996103},"labels":[],"label_agreement":null},{"id":"W4386590161","doi":"10.1073/pnas.2302016120","title":"Noise properties of adaptation-conferring biochemical control modules","year":2023,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Alliance de recherche numérique du Canada; Connaught Fund; University of Toronto; Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Robustness (evolution); Limit (mathematics); Synthetic biology; Adaptation (eye); Noise (video); Control theory (sociology); Biological system; Computer science; Control (management); Mathematics; Biology; Bioinformatics; Neuroscience; Artificial intelligence","score_opus":0.03743317946853417,"score_gpt":0.2648527273569789,"score_spread":0.22741954788844473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386590161","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":[0.9986961,0.00034254722,0.0000062541885,0.00055843167,0.0000076080487,0.00008279275,0.0000068123086,0.00000467873,0.00029479284],"genre_scores_gemma":[0.99942964,0.000040913284,0.00031938436,0.000043762204,0.00006398472,0.000007944679,4.0139997e-7,0.0000035137468,0.000090437796],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998966,0.0000054393713,0.00024172697,0.0001748276,0.0005080064,0.00010402153],"domain_scores_gemma":[0.99942505,0.00001245439,0.00025194063,0.000009991235,0.00028040496,0.000020150463],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000591839,0.00006507959,0.000120148936,0.0000975508,0.00006927508,0.0000064092965,0.00042176805,0.00006954868,0.0000019361348],"category_scores_gemma":[0.0002869542,0.000044408538,0.000094514,0.00048674943,0.0005508681,0.000011484714,0.00009946845,0.000041568946,5.7031286e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000140592865,0.000011809422,0.0031878331,0.000036710015,0.000034475408,7.6433787e-10,0.00004198645,0.0046360753,0.9904679,0.0011390286,0.00033630518,0.000093798444],"study_design_scores_gemma":[0.00012678848,0.000021885362,0.016398657,0.000040676216,0.000017534237,9.874288e-7,0.00015922343,0.013737578,0.96790344,0.0014840625,0.000058472437,0.00005070533],"about_ca_topic_score_codex":0.0000030280926,"about_ca_topic_score_gemma":6.231917e-8,"teacher_disagreement_score":0.02256449,"about_ca_system_score_codex":0.000005744313,"about_ca_system_score_gemma":0.000030068853,"threshold_uncertainty_score":0.20296964},"labels":[],"label_agreement":null},{"id":"W4386689194","doi":"10.1101/2023.09.11.557227","title":"Modularity of biological systems: a link between structure and function","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"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":"Defense Advanced Research Projects Agency; National Institutes of Health; Banff International Research Station for Mathematical Innovation and Discovery","keywords":"Modularity (biology); Modular design; Gene regulatory network; Robustness (evolution); Biological network; Boolean network; Computer science; Systems biology; Function (biology); Theoretical computer science; Network motif; Functional decomposition; Computational biology; Biology; Boolean function; Gene; Algorithm; Genetics; Machine learning","score_opus":0.020052442274136877,"score_gpt":0.22233271317106432,"score_spread":0.20228027089692743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386689194","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":[0.9912029,0.0038906583,0.0033114762,0.00006305049,0.0005326605,0.00040728218,0.0004963954,0.000094935625,6.727551e-7],"genre_scores_gemma":[0.99698806,0.0005017915,0.00073670165,0.000018643714,0.0016098028,0.00004399856,0.000010111021,0.00008497118,0.0000059143686],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99754417,0.0002295476,0.00054392405,0.0010668578,0.00024729143,0.0003681926],"domain_scores_gemma":[0.99778265,0.00002434803,0.00045632635,0.0011778742,0.00036778473,0.00019100161],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00048029041,0.00045477742,0.0006900858,0.00017172501,0.0000930291,0.00006856244,0.00035499837,0.0012882227,0.0000050380168],"category_scores_gemma":[0.00013602895,0.0004460715,0.00019691286,0.00030692233,0.0001784867,0.0000044647004,0.00077552366,0.00041569132,0.0000045637375],"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":[0.000030643496,0.000014824902,0.14769146,0.000353772,0.00073074916,0.0000044191906,0.0000013921425,0.0012195373,0.84973156,0.00007298279,0.00014267267,0.0000059562394],"study_design_scores_gemma":[0.00041199903,0.00020355213,0.7162329,0.00019194829,0.00052424474,2.4097416e-8,0.000003126271,0.0007922755,0.27762875,0.000014690995,0.0032075907,0.0007889273],"about_ca_topic_score_codex":0.000045833363,"about_ca_topic_score_gemma":0.0000030296596,"teacher_disagreement_score":0.57210284,"about_ca_system_score_codex":0.00004351139,"about_ca_system_score_gemma":0.00019714452,"threshold_uncertainty_score":0.99979913},"labels":[],"label_agreement":null},{"id":"W4387141906","doi":"10.3389/fsybi.2023.1255472","title":"Synthetic biology encompasses metagenomics, ecosystems, and biodiversity sustainability within its scope","year":2023,"lang":"en","type":"article","venue":"Frontiers in Synthetic Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"National Academy of Agricultural Sciences; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Metagenomics; Sustainability; Biodiversity; Biosphere; Synthetic biology; Scope (computer science); Ecosystem; Ecology; Environmental resource management; Biology; Computer science; Computational biology; Environmental science","score_opus":0.010268822825570886,"score_gpt":0.2384797226544339,"score_spread":0.228210899828863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387141906","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":[0.98792356,0.008128248,0.00163198,0.00058407476,0.0010051004,0.00044090557,0.00011251631,0.000057909892,0.00011572134],"genre_scores_gemma":[0.99702364,0.0013480686,0.0009820553,0.0000773772,0.00009741707,0.000046425383,0.00020120176,0.000022986671,0.00020081429],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99687916,0.00075447635,0.0005181999,0.0010902893,0.00007530143,0.00068258937],"domain_scores_gemma":[0.9987255,0.00006388027,0.00020749688,0.0007145877,0.00013121268,0.0001573482],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0012642145,0.0003474031,0.00068558584,0.00040491502,0.00017297833,0.000022474613,0.00046529464,0.0005223174,0.000028324708],"category_scores_gemma":[0.00042088496,0.00033235148,0.00016347489,0.0004768196,0.00060699176,0.000005238934,0.00046657835,0.00017972708,0.00003768132],"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":[0.00030118387,0.00020122035,0.86703813,0.00031444576,0.0010660586,0.000036017424,0.00039866593,0.0020871607,0.10214488,0.0012108809,0.0147788655,0.010422482],"study_design_scores_gemma":[0.008939156,0.0033276037,0.08886426,0.0002886222,0.0019932657,0.00036461887,0.015337719,0.0389689,0.33304408,0.035665166,0.46532828,0.007878336],"about_ca_topic_score_codex":0.00011623019,"about_ca_topic_score_gemma":0.00021388568,"teacher_disagreement_score":0.77817386,"about_ca_system_score_codex":0.000115153045,"about_ca_system_score_gemma":0.00016639187,"threshold_uncertainty_score":0.99991286},"labels":[],"label_agreement":null},{"id":"W4387390064","doi":"10.48550/arxiv.2310.02731","title":"State Feedback Control Design for Input-output Decoupling of Boolean Control Networks","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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; National Natural Science Foundation of China","keywords":"Decoupling (probability); Control theory (sociology); Control (management); Computer science; State (computer science); Feedback control; Control engineering; Engineering; Algorithm; Artificial intelligence","score_opus":0.05106777164736341,"score_gpt":0.19604367708417472,"score_spread":0.14497590543681133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387390064","genre_codex":"methods","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":[0.2520297,0.0004002213,0.7463947,0.00002362221,0.0002602285,0.00072393153,0.00010513557,0.000042213727,0.00002025854],"genre_scores_gemma":[0.99611914,0.0005552836,0.00063070713,0.000079540085,0.00030078235,0.00000927469,0.0002148412,0.00009336853,0.0019970671],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99764067,0.0001980468,0.000427422,0.0011072356,0.00007990518,0.0005467286],"domain_scores_gemma":[0.9976899,0.0001590505,0.0005761618,0.0010111666,0.0003752702,0.00018847392],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006678744,0.0004419445,0.0007101671,0.00018317607,0.0001220414,0.000032018386,0.0007009429,0.0005642758,0.000007672601],"category_scores_gemma":[0.00007684642,0.0005274772,0.0006850308,0.00026138846,0.00016348442,0.0000054964935,0.00038389515,0.00027545495,0.000009284975],"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":[0.0006973299,0.000045813555,0.0052223187,0.00007696788,0.0014204625,0.000016758364,0.000011903456,0.98949903,0.001393043,0.000106463944,0.0012588509,0.00025106812],"study_design_scores_gemma":[0.003059123,0.00023048768,0.0010876112,0.00007897657,0.0010330586,0.0000012272849,0.000043988926,0.9889628,0.0022151466,0.0022484618,0.0004324996,0.00060657924],"about_ca_topic_score_codex":0.000040552783,"about_ca_topic_score_gemma":0.00008045197,"teacher_disagreement_score":0.745764,"about_ca_system_score_codex":0.00007343023,"about_ca_system_score_gemma":0.0002313465,"threshold_uncertainty_score":0.99971765},"labels":[],"label_agreement":null},{"id":"W4387783577","doi":"10.1007/s11424-023-2013-3","title":"Finite-Time Observability of Probabilistic Logical Control Systems","year":2023,"lang":"en","type":"article","venue":"Journal of Systems Science and Complexity","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Observability; Reachability; Finite set; Probabilistic logic; Mathematics; Computer science; Algorithm; Applied mathematics; Artificial intelligence","score_opus":0.05029727325875114,"score_gpt":0.26661458854363856,"score_spread":0.21631731528488743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387783577","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":[0.9977382,0.00086544064,0.000769292,0.00008098241,0.00024111684,0.00017501239,0.000013622082,0.0000058987507,0.000110459885],"genre_scores_gemma":[0.9996119,0.000029873076,0.000051912528,0.000014303291,0.00018735092,0.0000036589042,0.00000239264,0.000004674406,0.00009393255],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981605,0.00018187753,0.0006011409,0.00023728279,0.0005810053,0.00023820717],"domain_scores_gemma":[0.99806994,0.00007287349,0.00047151232,0.00029547498,0.0009306053,0.00015962095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003461178,0.00011033096,0.000420577,0.00011232897,0.00013177996,0.000058107522,0.000380843,0.00007210147,0.0000038073129],"category_scores_gemma":[0.00056998763,0.00008071116,0.00011130476,0.0006001369,0.00084943254,0.000013555756,0.000100790705,0.00007609097,0.0000043661735],"study_design_candidate":"simulation_or_modeling","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":[0.0002683146,0.00024741548,0.07326093,0.00055979594,0.00029476866,0.000025254374,0.00014581127,0.15981992,0.7593744,0.0028384088,0.0027199339,0.0004450437],"study_design_scores_gemma":[0.0029708568,0.003114614,0.33743128,0.00044446782,0.00038317227,0.0006268425,0.0014447243,0.63754785,0.0050721588,0.0023617216,0.007763305,0.000838965],"about_ca_topic_score_codex":0.000029167279,"about_ca_topic_score_gemma":0.0000029323323,"teacher_disagreement_score":0.75430226,"about_ca_system_score_codex":0.000034647404,"about_ca_system_score_gemma":0.00026387512,"threshold_uncertainty_score":0.32913053},"labels":[],"label_agreement":null},{"id":"W4388384715","doi":"10.1093/oso/9780199637584.003.0001","title":"An introduction to differential display and related techniques","year":2000,"lang":"en","type":"book-chapter","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Dalhousie University","funders":"","keywords":"Skepticism; Simplicity; Differential (mechanical device); Computer science; Data science; Cognitive science; Epistemology; Psychology; Engineering; Philosophy","score_opus":0.003287152729861816,"score_gpt":0.20967354358970988,"score_spread":0.20638639085984806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388384715","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27732247,0.0025208823,0.0049453196,0.0026082252,0.0008584181,0.0018550247,0.00010330877,0.00044913578,0.70933723],"genre_scores_gemma":[0.30158606,0.0008635774,0.0008595535,0.000120176584,0.00260859,0.000015271658,0.0012788575,0.00010315412,0.6925647],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99889815,0.000017614859,0.0002125471,0.00062458,0.00010349442,0.00014359101],"domain_scores_gemma":[0.9992125,0.0000012722279,0.00006047237,0.00055722386,0.000041823972,0.00012668398],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00005452328,0.00025838078,0.00022723629,0.00009822227,0.00005385833,0.000027437161,0.00011629356,0.00047949402,0.0010057084],"category_scores_gemma":[0.0000024062774,0.00023854703,0.000102750164,0.000020117172,0.00005748169,0.0000018696599,0.000065946966,0.00010940186,0.000020413798],"study_design_candidate":"not_applicable","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":[0.0003485812,0.00009680943,0.00012061413,0.000039243452,0.0013291967,0.000013400933,0.000048177568,0.00017769601,0.6932286,0.02990259,0.06130952,0.21338558],"study_design_scores_gemma":[0.00013037978,0.0005151232,0.00020284795,0.000016017977,0.00028908515,0.00004826753,0.0000028319355,0.000058865873,0.04786811,0.0021291173,0.9480882,0.0006511096],"about_ca_topic_score_codex":0.00000398311,"about_ca_topic_score_gemma":0.000032086722,"teacher_disagreement_score":0.8867787,"about_ca_system_score_codex":0.000012769113,"about_ca_system_score_gemma":0.000016445045,"threshold_uncertainty_score":0.9999075},"labels":[],"label_agreement":null},{"id":"W4388915162","doi":"10.1016/j.biosystems.2023.105089","title":"Biological thermodynamics: Ervin Bauer and the unification of life sciences and physics","year":2023,"lang":"en","type":"article","venue":"Biosystems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Living systems; Statistical physics; Thermodynamic equilibrium; Equilibrium thermodynamics; Attractor; Physics; Mathematics; Computer science; Thermodynamics; Ecology; Biology","score_opus":0.01986174592511619,"score_gpt":0.23889334161075548,"score_spread":0.2190315956856393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388915162","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":[0.9968862,0.0023815194,0.00018678521,0.0002112645,0.000037815847,0.00010790699,0.000005666476,0.000008208588,0.00017462358],"genre_scores_gemma":[0.99886966,0.00086980994,0.00003872289,0.0000277229,0.00010913116,0.000008047435,0.000016429078,0.000004257796,0.00005621683],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9994183,0.000110783345,0.00012722664,0.00018337308,0.000070235066,0.000090086265],"domain_scores_gemma":[0.99967265,0.00002727145,0.00007877579,0.00016500709,0.00002910442,0.000027161768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005068471,0.00006385301,0.000117732576,0.000015477994,0.0000805016,0.000011286296,0.000104386374,0.00006246428,9.082852e-7],"category_scores_gemma":[0.000040164974,0.00003733914,0.000036925365,0.00019827728,0.00036690923,0.0000014213265,0.00008162961,0.000018667832,0.0000018161937],"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":[0.000085651576,0.000027634585,0.089228176,0.00008846994,0.0002349292,3.7400932e-7,0.0002189113,0.00067207176,0.8926574,0.010605412,0.0008876578,0.0052933437],"study_design_scores_gemma":[0.0051554474,0.00091705966,0.5317384,0.00014762142,0.0003051644,0.00003082923,0.005670713,0.35041776,0.080533996,0.005122316,0.01865285,0.0013078166],"about_ca_topic_score_codex":0.000020620435,"about_ca_topic_score_gemma":0.0000095354435,"teacher_disagreement_score":0.81212336,"about_ca_system_score_codex":0.0000018179007,"about_ca_system_score_gemma":0.000019643276,"threshold_uncertainty_score":0.1522646},"labels":[],"label_agreement":null},{"id":"W4388967813","doi":"10.3389/fbioe.2023.1266298","title":"Epistemology of synthetic biology: a new theoretical framework based on its potential objects and objectives","year":2023,"lang":"en","type":"article","venue":"Frontiers in Bioengineering and Biotechnology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Armand Frappier Museum; Institut National de la Recherche Scientifique; Collège Montmorency","funders":"","keywords":"Synthetic biology; Hierarchy; Confusion; Set (abstract data type); Modular design; Principal (computer security); Field (mathematics); Epistemology; Computer science; Data science; Management science; Biology; Computational biology; Mathematics; Psychology; Engineering","score_opus":0.004368073739086706,"score_gpt":0.2133370139750742,"score_spread":0.2089689402359875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388967813","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":[0.9342943,0.0033385959,0.060676236,0.0010904099,0.0003443893,0.00014211964,0.000013223171,0.000079237376,0.000021502532],"genre_scores_gemma":[0.9922397,0.0011329768,0.0064504934,0.000039408278,0.000060093655,0.000008613173,0.000020381214,0.000021521548,0.000026787211],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998893,0.000060131868,0.00020426232,0.000458469,0.000055286437,0.00032883303],"domain_scores_gemma":[0.999536,0.00003213877,0.00005248984,0.0002979199,0.000013131562,0.00006833509],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000178474,0.00019177371,0.00032779505,0.00052712293,0.000034288954,0.000005863475,0.00015064444,0.0007478714,0.000003224771],"category_scores_gemma":[0.00018915714,0.00018058,0.000062180174,0.00041276508,0.00046480706,0.0000017179834,0.000116747615,0.00020198694,0.0000011721894],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006134389,0.00016715899,0.043122336,0.00026672124,0.0005875475,0.00006867203,0.00016837275,0.024445424,0.8532218,0.029971747,0.0011593249,0.046207458],"study_design_scores_gemma":[0.0025003431,0.0030589346,0.021585431,0.00033771995,0.00021386884,0.00011467088,0.00067411165,0.38727954,0.5505469,0.03039057,0.0019421148,0.0013557989],"about_ca_topic_score_codex":0.0000025294185,"about_ca_topic_score_gemma":0.0000011094995,"teacher_disagreement_score":0.3628341,"about_ca_system_score_codex":0.000011534484,"about_ca_system_score_gemma":0.000032861844,"threshold_uncertainty_score":0.73638386},"labels":[],"label_agreement":null},{"id":"W4389034706","doi":"10.2390/biecoll-jib-2006-23","title":"Noise in Genetic Toggle Switch Models","year":2007,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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 Calgary","funders":"","keywords":"Noise (video); Computer science; Acoustics; Physics; Artificial intelligence","score_opus":0.12674422638702187,"score_gpt":0.48953683606362336,"score_spread":0.3627926096766015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389034706","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":[0.9599903,0.029828602,0.006730421,0.00004835956,0.00021642094,0.0003088654,0.000009401167,0.000010495056,0.0028571228],"genre_scores_gemma":[0.9906327,0.007120679,0.0011668461,0.00024170947,0.00031731115,0.000018633176,0.000025537332,0.00006336826,0.00041318886],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9971838,0.0001428395,0.0009558381,0.00062297704,0.0005022802,0.000592293],"domain_scores_gemma":[0.99808323,0.000050574356,0.00051397155,0.0007991699,0.00025033014,0.00030273185],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0014343966,0.00034043088,0.00061468646,0.0006303892,0.000119575445,0.0002886349,0.0020854254,0.0002412284,0.0010753957],"category_scores_gemma":[0.00008441908,0.00034003617,0.00027910396,0.000985543,0.00010423708,0.00007693728,0.0009360657,0.00024989422,0.000010494398],"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":[0.00018527664,0.00018985113,0.31297716,0.000026019166,0.00018998695,0.000041355128,0.000039678667,0.020192975,0.64713246,0.000016918046,0.0075577525,0.011450561],"study_design_scores_gemma":[0.0008672112,0.000024824993,0.68767214,0.000121295925,0.00011979302,0.000028961655,0.00007041213,0.0015753724,0.29759672,0.003434437,0.007786322,0.0007025332],"about_ca_topic_score_codex":0.00040852957,"about_ca_topic_score_gemma":0.0005390144,"teacher_disagreement_score":0.37469494,"about_ca_system_score_codex":0.000069208865,"about_ca_system_score_gemma":0.0001519635,"threshold_uncertainty_score":0.99990517},"labels":[],"label_agreement":null},{"id":"W4389071712","doi":"","title":"Synthetic and External Controls in Clinical Trials &amp;ndash; A Primer for Researchers","year":2020,"lang":"en","type":"article","venue":"SHILAP Revista de lepidopterología","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Primer (cosmetics); Clinical trial; Medicine; Psychology; Internal medicine; Chemistry","score_opus":0.13474205580958729,"score_gpt":0.4056129574685086,"score_spread":0.27087090165892136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389071712","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":[0.97123694,0.0074933795,0.015912192,0.0042965617,0.00005093782,0.0008511997,0.000020883039,0.000016201111,0.00012171816],"genre_scores_gemma":[0.99202275,0.0006695508,0.0034958774,0.0027279113,0.0007463353,0.000103082544,0.00003820626,0.00003489337,0.00016141104],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.995832,0.0017996395,0.0009926141,0.00072803994,0.00014957668,0.0004981292],"domain_scores_gemma":[0.9983955,0.00047261946,0.00027304818,0.00044203526,0.0000736141,0.00034317528],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007540399,0.00022310554,0.00082436757,0.00005770159,0.000058161597,0.000081925566,0.00030248988,0.00031997965,0.00003923499],"category_scores_gemma":[0.0056515657,0.00020056067,0.00042342412,0.00011804793,0.0002245095,0.0000050467934,0.0001535119,0.00025808203,0.000012542356],"study_design_candidate":"not_applicable","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":[0.0076749204,0.00031004043,0.47147852,0.0003883084,0.001334111,0.00003644017,0.00028433022,0.00068787375,0.38757506,0.0007329345,0.014172603,0.11532486],"study_design_scores_gemma":[0.010254987,0.0024142805,0.04212319,0.0001634309,0.0007313348,0.000038267128,0.00008091059,0.005524895,0.0065889056,0.00076704886,0.93027425,0.0010385124],"about_ca_topic_score_codex":0.00000880123,"about_ca_topic_score_gemma":0.000021853184,"teacher_disagreement_score":0.91610163,"about_ca_system_score_codex":0.00002140115,"about_ca_system_score_gemma":0.00010942425,"threshold_uncertainty_score":0.81786263},"labels":[],"label_agreement":null},{"id":"W4389476750","doi":"10.1016/j.bej.2023.109181","title":"Modeling heterogeneity in a cell culture using a coupled population balance-oxidative stress model","year":2023,"lang":"en","type":"article","venue":"Biochemical Engineering Journal","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sanofi (Canada); University of Waterloo","funders":"Mitacs","keywords":"Intracellular; Oxidative stress; Population; Oxidative phosphorylation; Cell; Chemistry; Biology; Biophysics; Cell biology; Biochemistry","score_opus":0.013120492359982533,"score_gpt":0.24322086395179826,"score_spread":0.23010037159181573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389476750","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":[0.9201824,0.0006408024,0.07901038,0.000009132133,0.00006205353,0.000060221264,0.000008201615,0.000023547856,0.0000032343082],"genre_scores_gemma":[0.9936587,0.0001596226,0.005696455,0.000011869598,0.00028697096,0.000004757696,0.00012891227,0.000031844655,0.000020833952],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99888116,0.000021425214,0.00029401327,0.00027377313,0.00018724763,0.00034237897],"domain_scores_gemma":[0.9995555,0.0000036440786,0.00006386722,0.0001775141,0.00006745262,0.00013201562],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018450168,0.00018743612,0.00019502919,0.00012627868,0.00005550785,0.00003447244,0.00016209502,0.00020313638,0.0000021448925],"category_scores_gemma":[0.00004512518,0.00018748325,0.00014350256,0.00032431525,0.000010330069,0.00000810597,0.0000855235,0.00022468016,0.0000015757729],"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":[0.000009502205,0.00001185269,0.0010128458,0.00001041957,0.00001858624,0.0000029409077,0.0000172804,0.52691823,0.47196293,5.63943e-7,0.000027963248,0.0000069032308],"study_design_scores_gemma":[0.00032230222,0.000014877051,0.00021503103,0.000041414707,0.000020818632,0.000017342822,0.00001971495,0.87777245,0.12137435,0.000012102985,0.0000060562943,0.0001835278],"about_ca_topic_score_codex":0.000009154172,"about_ca_topic_score_gemma":0.000003152987,"teacher_disagreement_score":0.35085425,"about_ca_system_score_codex":0.00007840265,"about_ca_system_score_gemma":0.000039363993,"threshold_uncertainty_score":0.76453453},"labels":[],"label_agreement":null},{"id":"W4389487553","doi":"10.1063/5.0173742","title":"Exact solution of a three-stage model of stochastic gene expression including cell-cycle dynamics","year":2023,"lang":"en","type":"article","venue":"The Journal of Chemical Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"National Natural Science Foundation of China; Leverhulme Trust","keywords":"Stochastic modelling; Messenger RNA; Cell cycle; Translation (biology); Population; Dilution; Stochastic process; Statistical physics; Biology; Mathematics; Biological system; Statistics; Cell; Gene; Physics; Genetics; Thermodynamics","score_opus":0.021812044128152,"score_gpt":0.2544348233203575,"score_spread":0.2326227791922055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389487553","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":[0.8034283,0.00016077158,0.19628674,0.000023073668,0.000023896664,0.000038080543,0.000010725784,0.000002648563,0.000025785805],"genre_scores_gemma":[0.9988539,0.000055226443,0.00084339734,0.000007669892,0.00017324107,7.158889e-7,0.000020976797,0.000018470755,0.000026358728],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990674,0.000039654424,0.00037112035,0.00009358868,0.00027272195,0.00015546367],"domain_scores_gemma":[0.9989449,0.000036134694,0.0005346554,0.00027025846,0.00016211013,0.000051946125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003229543,0.000110063746,0.00024266737,0.000032059925,0.000034551325,0.0000029265677,0.0002822464,0.00008603802,0.0000017474343],"category_scores_gemma":[0.00003145367,0.00008217921,0.00020850815,0.00019264672,0.000096780284,0.0000063354937,0.00019957524,0.00012900178,6.1794003e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000071412825,0.000037044378,0.000025820622,0.00002002753,0.000042735945,1.73899e-7,0.00003896028,0.34565446,0.65381956,0.000008109159,0.00008936584,0.00019234038],"study_design_scores_gemma":[0.00019031699,0.00003949831,0.000010170372,0.000023257326,0.0000831934,0.0000015067503,0.000025001715,0.34282818,0.65527135,0.0014742365,7.9629564e-7,0.000052486306],"about_ca_topic_score_codex":0.0000026740627,"about_ca_topic_score_gemma":8.6488825e-7,"teacher_disagreement_score":0.19544333,"about_ca_system_score_codex":0.000028054403,"about_ca_system_score_gemma":0.00006420664,"threshold_uncertainty_score":0.3351171},"labels":[],"label_agreement":null},{"id":"W4389711852","doi":"10.1038/s41467-023-43327-7","title":"Competition and evolutionary selection among core regulatory motifs in gene expression control","year":2023,"lang":"en","type":"article","venue":"Nature Communications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"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":"York University; New York University Abu Dhabi","keywords":"Gene regulatory network; Regulator; Biology; Psychological repression; Regulation of gene expression; Human evolutionary genetics; Gene; Selection (genetic algorithm); Transcription factor; Genetics; Autoregulation; Computational biology; Gene expression; Computer science; Genome","score_opus":0.00932612406963728,"score_gpt":0.2543615262463997,"score_spread":0.2450354021767624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389711852","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":[0.9937756,0.005143638,0.00022463885,0.00039255127,0.000053055184,0.00018247888,0.00001599477,0.0000462631,0.00016577209],"genre_scores_gemma":[0.99655473,0.0009906956,0.0012222625,0.000083860024,0.000081864666,0.000055986417,0.00082578027,0.0000168006,0.00016801042],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991589,0.00015844095,0.00017729338,0.00024108238,0.00011336464,0.00015088664],"domain_scores_gemma":[0.99895406,0.0000366441,0.00007853527,0.0007760473,0.00010238007,0.000052347696],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023226737,0.000105777624,0.00011680227,0.00015076285,0.00021661173,0.000011828811,0.00026895394,0.00033547648,0.0000054964066],"category_scores_gemma":[0.00005898296,0.00011389035,0.000054334447,0.0004359352,0.00013825193,0.0000079629635,0.00019918654,0.00029853726,0.0000053433037],"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":[0.00003850669,0.00007061591,0.42208776,0.000009137105,0.00005392888,8.122717e-7,0.000045105797,0.0056896633,0.5644426,0.0007216033,0.0065429467,0.00029736166],"study_design_scores_gemma":[0.00053429086,0.000038788792,0.96264654,0.000028192246,0.000031331256,0.000008491487,0.00005979035,0.019158412,0.011373983,0.00031480475,0.005635533,0.00016983342],"about_ca_topic_score_codex":0.000010401206,"about_ca_topic_score_gemma":0.00039891558,"teacher_disagreement_score":0.5530686,"about_ca_system_score_codex":0.00003678165,"about_ca_system_score_gemma":0.000037025762,"threshold_uncertainty_score":0.46443138},"labels":[],"label_agreement":null},{"id":"W4389891188","doi":"10.32920/24625170.v1","title":"Sensitivity Analysis of Stochastic Discrete Biochemical Systems and Applications","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Toronto Metropolitan University; York University","funders":"","keywords":"Robustness (evolution); Sensitivity (control systems); Identifiability; Systems biology; Computer science; Estimator; Mathematical and theoretical biology; Stochastic process; Biological system; Mathematics; Mathematical optimization; Bioinformatics; Chemistry; Biology; Machine learning; Engineering; Statistics","score_opus":0.013174165323360474,"score_gpt":0.26237284482995515,"score_spread":0.2491986795065947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389891188","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":[0.5019327,0.0018697376,0.49519944,0.000048131576,0.000072374125,0.00043594194,0.00032201278,0.000036881334,0.00008276692],"genre_scores_gemma":[0.99690133,0.00011982003,0.00027691622,0.000008557697,0.0001936785,0.000110712266,0.0017732369,0.000027935033,0.00058782805],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99846363,0.000099934834,0.0003596554,0.00072101335,0.00017409498,0.00018169667],"domain_scores_gemma":[0.9985572,0.000039810275,0.00022882322,0.00092508836,0.00014383925,0.00010525497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032105015,0.0002323701,0.00058083906,0.00025382245,0.000039230814,0.000026866812,0.00013898844,0.00038303033,0.0000037243587],"category_scores_gemma":[0.000034749344,0.00022390053,0.00036276254,0.00046928463,0.00014578408,6.534479e-7,0.0008104843,0.00012723147,0.0000027672586],"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":[0.000026654516,0.000057486428,0.0050998935,0.00030390843,0.0132700065,0.0000020291113,0.000021714859,0.77651715,0.20290369,0.00031950336,0.0012037825,0.00027418954],"study_design_scores_gemma":[0.0005805133,0.00012126017,0.0421309,0.00016396839,0.033643797,0.00001851178,0.00045283858,0.88282377,0.03612673,0.0005137163,0.0011665004,0.0022575285],"about_ca_topic_score_codex":0.00021392888,"about_ca_topic_score_gemma":0.00014452271,"teacher_disagreement_score":0.4949686,"about_ca_system_score_codex":0.000014523641,"about_ca_system_score_gemma":0.000058736303,"threshold_uncertainty_score":0.91303986},"labels":[],"label_agreement":null},{"id":"W4389919544","doi":"10.32920/24625170","title":"Sensitivity Analysis of Stochastic Discrete Biochemical Systems and Applications","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Toronto Metropolitan University; York University","funders":"","keywords":"Sensitivity (control systems); Robustness (evolution); Identifiability; Systems biology; Computer science; Estimator; Mathematical and theoretical biology; Stochastic process; Applied mathematics; Biological system; Mathematics; Mathematical optimization; Bioinformatics; Chemistry; Biology; Engineering; Statistics; Machine learning","score_opus":0.013174165323360474,"score_gpt":0.26237284482995515,"score_spread":0.2491986795065947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389919544","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":[0.5019327,0.0018697376,0.49519944,0.000048131576,0.000072374125,0.00043594194,0.00032201278,0.000036881334,0.00008276692],"genre_scores_gemma":[0.99690133,0.00011982003,0.00027691622,0.000008557697,0.0001936785,0.000110712266,0.0017732369,0.000027935033,0.00058782805],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99846363,0.000099934834,0.0003596554,0.00072101335,0.00017409498,0.00018169667],"domain_scores_gemma":[0.9985572,0.000039810275,0.00022882322,0.00092508836,0.00014383925,0.00010525497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032105015,0.0002323701,0.00058083906,0.00025382245,0.000039230814,0.000026866812,0.00013898844,0.00038303033,0.0000037243587],"category_scores_gemma":[0.000034749344,0.00022390053,0.00036276254,0.00046928463,0.00014578408,6.534479e-7,0.0008104843,0.00012723147,0.0000027672586],"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":[0.000026654516,0.000057486428,0.0050998935,0.00030390843,0.0132700065,0.0000020291113,0.000021714859,0.77651715,0.20290369,0.00031950336,0.0012037825,0.00027418954],"study_design_scores_gemma":[0.0005805133,0.00012126017,0.0421309,0.00016396839,0.033643797,0.00001851178,0.00045283858,0.88282377,0.03612673,0.0005137163,0.0011665004,0.0022575285],"about_ca_topic_score_codex":0.00021392888,"about_ca_topic_score_gemma":0.00014452271,"teacher_disagreement_score":0.4949686,"about_ca_system_score_codex":0.000014523641,"about_ca_system_score_gemma":0.000058736303,"threshold_uncertainty_score":0.91303986},"labels":[],"label_agreement":null},{"id":"W4390047245","doi":"10.1371/journal.pcbi.1011700","title":"Ten quick tips for fuzzy logic modeling of biomedical systems","year":2023,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"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":"Ministero dell'Università e della Ricerca; European Commission; Dipartimenti di Eccellenza","keywords":"Fuzzy logic; Computer science; Data science; Risk analysis (engineering); Artificial intelligence; Management science; Medicine; Engineering","score_opus":0.03423075056816541,"score_gpt":0.2811292068519812,"score_spread":0.24689845628381576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390047245","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":[0.8412868,0.0008480498,0.15666915,0.00037154465,0.00023002685,0.00029579742,0.0001340723,0.000045020894,0.00011953441],"genre_scores_gemma":[0.9935549,0.000030507688,0.0031580608,0.000068629815,0.00032825873,0.000051705898,0.0027083105,0.000015766149,0.00008387258],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989614,0.0000736343,0.00031958902,0.00031265273,0.00010825068,0.00022448438],"domain_scores_gemma":[0.99940634,0.0000708043,0.000101167076,0.00015201079,0.00020888753,0.00006079991],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021862694,0.00011237652,0.00022880173,0.00012803098,0.000058547594,0.0000055133696,0.00016555366,0.00018275628,0.0000045223087],"category_scores_gemma":[0.000086188156,0.00010060737,0.00012281617,0.00022078675,0.00009780529,0.0000013849481,0.00008878672,0.00003850345,0.000018993373],"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":[0.00006475731,0.00008480249,0.0019031877,0.00008205026,0.0004501396,0.0000010021864,0.000020443622,0.894051,0.09516083,0.005118809,0.0025332393,0.00052971055],"study_design_scores_gemma":[0.00041104297,0.0002765853,0.00021603041,0.000010835997,0.00004949216,0.00000781471,0.000045412773,0.9880449,0.0006822936,0.008277439,0.0018342347,0.00014388277],"about_ca_topic_score_codex":0.0000061151313,"about_ca_topic_score_gemma":0.0000014506866,"teacher_disagreement_score":0.15351109,"about_ca_system_score_codex":0.000010643103,"about_ca_system_score_gemma":0.00008157031,"threshold_uncertainty_score":0.41026497},"labels":[],"label_agreement":null},{"id":"W4390669115","doi":"10.1088/1367-2630/ad1bdd","title":"Breaking reflection symmetry: evolving long dynamical cycles in Boolean systems","year":2024,"lang":"en","type":"article","venue":"New Journal of Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"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; National Institute of Biomedical Imaging and Bioengineering; University of Pennsylvania; Army Research Office; Paul G. Allen Family Foundation; NIH Clinical Center; National Institutes of Health; National Science Foundation","keywords":"Physics; Dynamical systems theory; Reflection (computer programming); Boolean network; Reflection symmetry; Symmetry (geometry); Homogeneous space; Statistical physics; Dynamical system (definition); Complex system; Topology (electrical circuits); Boolean function; Computer science; Artificial intelligence; Quantum mechanics; Mathematics; Algorithm; Geometry; Combinatorics","score_opus":0.01084914911829387,"score_gpt":0.2707511638866176,"score_spread":0.2599020147683237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390669115","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":[0.9416127,0.011133418,0.046231437,0.000078079596,0.0006026157,0.000046861136,0.000001105052,0.000009121529,0.00028466323],"genre_scores_gemma":[0.99717146,0.00015450877,0.00030968868,0.00001526193,0.0021376621,5.232454e-7,0.0000067056794,0.000024843095,0.00017936397],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907684,0.00007071868,0.00032084543,0.00016583764,0.00019703442,0.00016874283],"domain_scores_gemma":[0.9995504,0.000015425754,0.00013704678,0.00014180694,0.00007678652,0.00007852555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002562962,0.00011513929,0.00019424577,0.00010202208,0.000030917476,0.000087107095,0.00013030766,0.000095498166,0.000003166443],"category_scores_gemma":[0.000021703212,0.00010644174,0.00018254195,0.00030971397,0.000019198904,0.000014647397,0.000039107024,0.00019928446,0.0000031923707],"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":[0.0001054797,0.00013518032,0.03305761,0.00024391046,0.00096500467,0.00018772707,0.00021723947,0.111010134,0.71846265,0.0014935696,0.007527472,0.12659402],"study_design_scores_gemma":[0.0048620272,0.002485904,0.102595694,0.006835534,0.0022855701,0.0035887342,0.0016260582,0.5286139,0.29804572,0.01248316,0.033457275,0.0031203933],"about_ca_topic_score_codex":0.000036858004,"about_ca_topic_score_gemma":0.00005461929,"teacher_disagreement_score":0.42041692,"about_ca_system_score_codex":0.00008838252,"about_ca_system_score_gemma":0.00013051464,"threshold_uncertainty_score":0.43405682},"labels":[],"label_agreement":null},{"id":"W4391021817","doi":"10.1109/cdc49753.2023.10383353","title":"New Results on Input-output Decoupling of Boolean Control Networks","year":2023,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lakehead University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Decoupling (probability); Computer science; Boolean network; Control (management); Boolean function; Control theory (sociology); Algorithm; Control engineering; Artificial intelligence; Engineering","score_opus":0.010704491806452787,"score_gpt":0.2401213789612591,"score_spread":0.22941688715480632,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391021817","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":[0.91925037,0.0006401327,0.07285386,0.0006063193,0.00031948093,0.00026727974,0.000015712076,0.00009956454,0.0059472593],"genre_scores_gemma":[0.99124926,0.00013244792,0.00036685378,0.00024485288,0.0004927036,0.000003528928,0.0001232062,0.000024419787,0.007362733],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99886966,0.00003428247,0.0003177169,0.0003499873,0.00014793209,0.0002804517],"domain_scores_gemma":[0.9991668,0.00003283266,0.00011350427,0.0005070357,0.00006013879,0.000119708624],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030308103,0.00014550125,0.00020707063,0.00008198928,0.000045967405,0.000011626093,0.00019045467,0.00015808853,0.000019803905],"category_scores_gemma":[0.000063287094,0.00013193984,0.00017304404,0.00030205012,0.00002765166,0.0000012659066,0.00007183356,0.000067914836,0.000037770897],"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":[0.0004908058,0.000033035114,0.004062702,0.000008453805,0.0003972825,0.00000566929,0.000021757472,0.8070967,0.029740682,0.00016852791,0.1363205,0.021653842],"study_design_scores_gemma":[0.01167516,0.001978069,0.04571457,0.00013245005,0.0005012316,0.000011739211,0.00024292864,0.5106881,0.28887373,0.00041795347,0.13814041,0.001623605],"about_ca_topic_score_codex":0.000027441323,"about_ca_topic_score_gemma":0.00006134451,"teacher_disagreement_score":0.2964086,"about_ca_system_score_codex":0.000008210703,"about_ca_system_score_gemma":0.000054672015,"threshold_uncertainty_score":0.5380351},"labels":[],"label_agreement":null},{"id":"W4391212377","doi":"10.48550/arxiv.2401.12477","title":"Modular control of Boolean network models","year":2024,"lang":"en","type":"preprint","venue":"PubMed","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Advanced Research Projects Agency; Banff International Research Station for Mathematical Innovation and Discovery; American Association of Immunologists","keywords":"Modular design; Computer science; ENCODE; Biological network; Control (management); Boolean network; Gene regulatory network; Systems biology; Computational biology; Artificial intelligence; Boolean function; Biology; Gene","score_opus":0.012341634564367453,"score_gpt":0.20214479842062313,"score_spread":0.18980316385625567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391212377","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":[0.8555439,0.09746261,0.034084335,0.0005357859,0.0021521773,0.0026017327,0.00025213722,0.0001086385,0.007258642],"genre_scores_gemma":[0.99486965,0.0004471353,0.00027616316,0.00012077867,0.0015026844,0.0010246902,0.00020554957,0.00007564604,0.0014776904],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99792933,0.00011393613,0.00045743064,0.0007431804,0.00024483827,0.00051128946],"domain_scores_gemma":[0.99842286,0.000008504594,0.00022710307,0.0010676384,0.00012138311,0.0001525301],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00052788487,0.00033313077,0.0005292476,0.00007846797,0.000029978344,0.000035709614,0.0004508579,0.00053972803,0.0000061755172],"category_scores_gemma":[0.000021548398,0.00033281866,0.0005888712,0.00013091408,0.00008836284,0.0000010622381,0.0010006557,0.00031838845,0.000004698975],"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":[0.000054531774,0.000031421492,0.00034788428,0.00018224108,0.0015741055,0.0000054379243,0.000009199272,0.9767171,0.0010983322,0.0003674936,0.0057278387,0.01388438],"study_design_scores_gemma":[0.0034041055,0.00020677762,0.032243844,0.00041403453,0.007834099,0.000039149123,0.00005190903,0.58788973,0.037996322,0.25623354,0.069201946,0.004484572],"about_ca_topic_score_codex":0.000017613691,"about_ca_topic_score_gemma":0.000018870534,"teacher_disagreement_score":0.38882744,"about_ca_system_score_codex":0.000029489349,"about_ca_system_score_gemma":0.00009538582,"threshold_uncertainty_score":0.9999124},"labels":[],"label_agreement":null},{"id":"W4391221974","doi":"10.7554/elife.92497","title":"Exploiting fluctuations in gene expression to detect causal interactions between genes","year":2024,"lang":"en","type":"article","venue":"eLife","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto; Connaught Fund; Concordia University; Government of Ontario","keywords":"Gene; Gene expression; Genetics; Computational biology; Expression (computer science); Biology; Computer science","score_opus":0.017961057945222864,"score_gpt":0.29235705557135233,"score_spread":0.2743959976261295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391221974","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":[0.9767658,0.0013956598,0.02122118,0.00016701697,0.00017783293,0.000097175376,0.000011118632,0.00003174609,0.00013245989],"genre_scores_gemma":[0.9939407,0.000080571604,0.0043231105,0.000076394106,0.00096158514,0.000051807147,0.000106226194,0.000025714442,0.00043388008],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990836,0.000055136745,0.000211574,0.00033461637,0.00012482193,0.00019027403],"domain_scores_gemma":[0.9995721,0.00002300926,0.000022979713,0.000250917,0.000040087372,0.00009090932],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015075566,0.00011247824,0.00011310657,0.00015129233,0.00006896248,0.00004062768,0.000108888285,0.000058747806,0.00003079919],"category_scores_gemma":[0.000055289707,0.00011263086,0.00008470949,0.0002802749,0.0000129719065,0.0000057369107,0.00011355192,0.00008140989,0.00006900387],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000037689204,0.000004883393,0.0030034417,0.000005805998,0.00004026788,0.000004052344,0.0000644103,0.0031693114,0.9838397,0.0000029109651,0.0015732544,0.008288231],"study_design_scores_gemma":[0.00006261034,0.000030825406,0.0072426484,0.000035503705,0.00002904868,0.000004238641,0.000057674788,0.0004259003,0.96647596,0.00002292061,0.025464717,0.00014797275],"about_ca_topic_score_codex":0.000017216023,"about_ca_topic_score_gemma":0.0001350971,"teacher_disagreement_score":0.023891464,"about_ca_system_score_codex":0.00003119218,"about_ca_system_score_gemma":0.000051436917,"threshold_uncertainty_score":0.45929533},"labels":[],"label_agreement":null},{"id":"W4391222373","doi":"10.7554/elife.92497.1","title":"Exploiting fluctuations in gene expression to detect causal interactions between genes","year":2024,"lang":"en","type":"preprint","venue":"eLife","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Connaught Fund; University of Toronto","keywords":"Gene; Computational biology; Gene expression; Genetics; Biology; Expression (computer science); Computer science","score_opus":0.022867263020649127,"score_gpt":0.30182857233699695,"score_spread":0.2789613093163478,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391222373","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":[0.9881276,0.002447191,0.008071216,0.0002258442,0.0005415577,0.00028443313,0.00006866133,0.000043740056,0.00018974642],"genre_scores_gemma":[0.9880681,0.0002104818,0.007932504,0.00008996536,0.0022061807,0.00021728427,0.0006239199,0.00006809658,0.00058347784],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9980922,0.000118400145,0.00045797345,0.00079703506,0.00023338081,0.00030104094],"domain_scores_gemma":[0.99890757,0.000023778975,0.00011120622,0.0006999595,0.00010395293,0.00015353397],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002524302,0.00029598203,0.00031844366,0.00029989763,0.00008178033,0.00007219076,0.00029899378,0.00025913442,0.00002815207],"category_scores_gemma":[0.000101191494,0.00031430626,0.00023280538,0.00023557493,0.000022781254,0.0000022990698,0.0016214338,0.0004091326,0.00009236171],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009908167,0.000013076897,0.0025781402,0.000045130582,0.00017911424,0.00000785156,0.0001216777,0.0310374,0.95732397,0.0000019298664,0.0029101677,0.0057716076],"study_design_scores_gemma":[0.00009884441,0.0000333137,0.004799632,0.00017769421,0.00014115388,0.0000040823425,0.00007154965,0.00042453912,0.9850369,0.00024904066,0.008537505,0.00042574215],"about_ca_topic_score_codex":0.00005720974,"about_ca_topic_score_gemma":0.00033721334,"teacher_disagreement_score":0.03061286,"about_ca_system_score_codex":0.00008247778,"about_ca_system_score_gemma":0.00017105337,"threshold_uncertainty_score":0.9999309},"labels":[],"label_agreement":null},{"id":"W4391389443","doi":"10.1021/acscentsci.3c01250","title":"High-Performance Genetically Encoded Green Fluorescent Biosensors for Intracellular <scp>l</scp>-Lactate","year":2024,"lang":"en","type":"article","venue":"ACS Central Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; University of Alberta; University of Toronto","funders":"National Institute of Neurological Disorders and Stroke; Ministry of Education, Culture, Sports, Science and Technology; Japan Society for the Promotion of Science; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Japan Agency for Medical Research and Development","keywords":"Green fluorescent protein; Biosensor; Intracellular; Biochemistry; Glycolysis; Fluorescence; Chemistry; Extracellular; Ex vivo; Cell biology; In vitro; Biology; Biophysics; Metabolism; Gene","score_opus":0.006925650539089414,"score_gpt":0.22059367378083747,"score_spread":0.21366802324174805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391389443","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":[0.99424356,0.0014638283,0.0030772963,0.00022227826,0.00053440605,0.00029551386,0.000018510702,0.00004519317,0.000099409],"genre_scores_gemma":[0.994233,0.0005982457,0.0033754215,0.00012518732,0.0004793767,0.000021811977,0.000050645485,0.000029124109,0.0010871931],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9974761,0.000032506225,0.00028781846,0.00081917143,0.00040400279,0.0009804167],"domain_scores_gemma":[0.99898684,0.000032202905,0.000057968104,0.00047104582,0.00014191285,0.00031001735],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047045216,0.00023557608,0.00017806307,0.00010579771,0.00023952448,0.00015099283,0.0006349622,0.0001231778,0.0000075197763],"category_scores_gemma":[0.00012475523,0.00020630754,0.00012328429,0.00066373183,0.00050853804,0.00001958362,0.00017945156,0.0001024515,0.000020964084],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008933196,0.000028874249,0.0010122214,0.000042839783,0.000049733113,0.0000058558016,0.00007254242,0.0034548368,0.9847675,0.00029984317,0.0014964185,0.008760383],"study_design_scores_gemma":[0.00017332866,0.00018032853,0.0044038338,0.000023398994,0.00006145115,0.000011757771,0.000030088879,0.026925387,0.9449628,0.00008571984,0.023000311,0.00014162257],"about_ca_topic_score_codex":0.000017877566,"about_ca_topic_score_gemma":0.000013576682,"teacher_disagreement_score":0.039804745,"about_ca_system_score_codex":0.000066191045,"about_ca_system_score_gemma":0.0002837139,"threshold_uncertainty_score":0.8412977},"labels":[],"label_agreement":null},{"id":"W4391505239","doi":"10.48550/arxiv.2402.00022","title":"Modular Construction of Boolean Networks","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Advanced Research Projects Agency; Banff International Research Station for Mathematical Innovation and Discovery; American Association of Immunologists","keywords":"Modular design; Computer science; Boolean expression; Theoretical computer science; Boolean function; Programming language; Algorithm","score_opus":0.02116833223488102,"score_gpt":0.16601012221562342,"score_spread":0.1448417899807424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391505239","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":[0.94706833,0.0015310805,0.049706794,0.00001588173,0.00047323917,0.00013916471,0.000022629174,0.00003194078,0.0010109177],"genre_scores_gemma":[0.99700016,0.0008160643,0.00028678015,0.000015955298,0.00030770194,5.751461e-7,0.00016868269,0.000034393197,0.0013696693],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99865127,0.00008642637,0.0002044707,0.0007902501,0.00005058109,0.00021698626],"domain_scores_gemma":[0.99874264,0.00000607899,0.00019559298,0.00083655963,0.00012562856,0.000093509945],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013517484,0.00025470814,0.00029974573,0.0001352742,0.000043966233,0.000017204284,0.00035663464,0.0005054713,0.00002953484],"category_scores_gemma":[0.000009256443,0.0003052706,0.0004176098,0.0002654908,0.00020056182,0.0000018930725,0.0010634132,0.00031570115,0.0000120867735],"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":[0.000047724512,0.000026120335,0.0026090469,0.00009967521,0.0006739332,0.000031911623,0.000008441471,0.98565924,0.005281252,0.0045568487,0.00052236783,0.00048345744],"study_design_scores_gemma":[0.00062741165,0.00017972036,0.0013749051,0.00024199144,0.0018940114,0.000023396391,0.0001970023,0.94458985,0.017295854,0.028903594,0.0035420211,0.0011302605],"about_ca_topic_score_codex":0.00003189704,"about_ca_topic_score_gemma":0.000033696295,"teacher_disagreement_score":0.049931824,"about_ca_system_score_codex":0.000043927423,"about_ca_system_score_gemma":0.00011592612,"threshold_uncertainty_score":0.9999399},"labels":[],"label_agreement":null},{"id":"W4391547256","doi":"10.1007/978-3-031-13920-8_12","title":"The Modelling Supremacy of the Topological Graph Theoretic Models and Connections to Biology","year":2024,"lang":"en","type":"book-chapter","venue":"Studies in neuroscience, consciousness and spirituality","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; Western University","funders":"","keywords":"Graph; Topology (electrical circuits); Mathematics; Computer science; Theoretical computer science; Combinatorics","score_opus":0.05527045853086002,"score_gpt":0.3182771971664865,"score_spread":0.2630067386356265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391547256","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":[0.8578288,0.089757495,0.004715386,0.006059641,0.0034001635,0.0017916369,0.00024319436,0.000045143788,0.03615857],"genre_scores_gemma":[0.9825029,0.011811545,0.00002241662,0.00028324118,0.00006287286,0.000025498604,0.0000015038407,0.000014146456,0.005275907],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99838823,0.000099060344,0.0003997577,0.00071062887,0.000143469,0.00025884682],"domain_scores_gemma":[0.9990893,0.00012958946,0.00011585384,0.0004902108,0.00011445025,0.00006057207],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0006258635,0.00025529275,0.00040137317,0.00007791727,0.00046863093,0.00003561241,0.00033262777,0.00017175273,0.0000010299456],"category_scores_gemma":[0.00011666427,0.00014486912,0.0001440331,0.00014364939,0.004655826,0.000003407148,0.0009374105,0.00021259086,2.3218757e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002932935,0.000016147724,0.0008217389,0.000081611775,0.00009121579,0.0000030371234,0.00027782138,0.006400047,0.0015808643,0.99010867,0.00016363506,0.00042588907],"study_design_scores_gemma":[0.00021080227,0.00023998,0.00023461475,0.00013730796,0.00019050049,0.000032627766,0.0005518488,0.005087568,0.00031156876,0.9744172,0.018138312,0.0004476621],"about_ca_topic_score_codex":0.000016083497,"about_ca_topic_score_gemma":0.0003826873,"teacher_disagreement_score":0.1246741,"about_ca_system_score_codex":0.000011716974,"about_ca_system_score_gemma":0.000052672527,"threshold_uncertainty_score":0.99805295},"labels":[],"label_agreement":null},{"id":"W4391554342","doi":"10.1016/j.automatica.2024.111546","title":"Information-theoretic multi-time-scale partially observable systems with inspiration from leukemia treatment","year":2024,"lang":"en","type":"article","venue":"Automatica","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto","funders":"University of Toronto","keywords":"Observable; Scale (ratio); Computer science; Physics; Geography; Cartography","score_opus":0.007157800798922264,"score_gpt":0.2119638239944722,"score_spread":0.20480602319554994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391554342","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":[0.97613436,0.0012170617,0.021126818,0.000086724474,0.0001229499,0.00034499043,0.000038974733,0.00012579493,0.00080233446],"genre_scores_gemma":[0.9946377,0.000052973046,0.0032192431,0.000056361092,0.0001455832,0.00011180277,0.00061493187,0.000023426463,0.0011379361],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990937,0.000061437444,0.0002914968,0.00020323491,0.00015575206,0.0001943528],"domain_scores_gemma":[0.9993686,0.000019847424,0.00006859042,0.00040674847,0.00005677063,0.00007946339],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009572258,0.00018172986,0.00018711643,0.000046063135,0.00007659738,0.00017341896,0.000109447,0.000118000185,0.00007648025],"category_scores_gemma":[0.000010266049,0.00013665907,0.00008317107,0.00015151982,0.00005327008,0.000022278877,0.000029950848,0.000037228918,0.00047584664],"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":[0.00033206842,0.0005469548,0.013295516,0.0009477757,0.0064775273,0.00005924962,0.0060324795,0.5714083,0.32639283,0.0022936584,0.019932583,0.052281093],"study_design_scores_gemma":[0.0006320692,0.0004182429,0.0021885452,0.00011384602,0.0003755727,0.000011112998,0.00015181625,0.92760986,0.029553927,0.000053766515,0.038557958,0.0003333093],"about_ca_topic_score_codex":0.00010517821,"about_ca_topic_score_gemma":0.00007279371,"teacher_disagreement_score":0.3562016,"about_ca_system_score_codex":0.00010706002,"about_ca_system_score_gemma":0.00022394134,"threshold_uncertainty_score":0.6116204},"labels":[],"label_agreement":null},{"id":"W4391888490","doi":"10.1016/j.crbiot.2024.100188","title":"Organizational change of synthetic biology research: Emerging initiatives advancing a bottom-up approach","year":2024,"lang":"en","type":"article","venue":"Current Research in Biotechnology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Genomics","funders":"Eidgenössische Technische Hochschule Zürich; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Organizational change; Engineering ethics; Process management; Engineering; Political science; Public relations","score_opus":0.13373366439654333,"score_gpt":0.4230022643753328,"score_spread":0.28926859997878945,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391888490","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":[0.9025508,0.08614315,0.0040876204,0.0035713532,0.001459154,0.0010524183,0.000052891242,0.00011932111,0.00096329255],"genre_scores_gemma":[0.990016,0.00832006,0.000565268,0.000005973592,0.0006643898,0.00017630598,0.00017006819,0.000040526982,0.000041419546],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99647796,0.0008681011,0.0003974418,0.0008657068,0.0004579385,0.0009328624],"domain_scores_gemma":[0.9986478,0.00016003358,0.000051450723,0.00061866216,0.00043055404,0.00009147982],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033503792,0.00018321715,0.0002885386,0.0021008954,0.00014103147,0.000024829289,0.000633569,0.0005620279,0.00004314246],"category_scores_gemma":[0.0007856757,0.00017397443,0.000090380614,0.0035326008,0.0012333797,0.000011984481,0.0008469568,0.001293137,0.000030619674],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009681737,0.0005178017,0.015569356,0.0010438543,0.0002811321,0.000017045739,0.0007488936,0.00009373999,0.8116101,0.08853121,0.0036348137,0.07785525],"study_design_scores_gemma":[0.0012856591,0.0016015384,0.0024312548,0.0013388266,0.000060616363,0.000084927124,0.0037792008,0.017808486,0.69634527,0.049403653,0.22462602,0.0012345496],"about_ca_topic_score_codex":0.00002670271,"about_ca_topic_score_gemma":0.000027058366,"teacher_disagreement_score":0.22099121,"about_ca_system_score_codex":0.000113452916,"about_ca_system_score_gemma":0.00034262953,"threshold_uncertainty_score":0.70944715},"labels":[],"label_agreement":null},{"id":"W4392494786","doi":"","title":"Robustesse des systèmes complexes : étude du rôle de l’aléa dans la dynamique des automates cellulaires","year":2023,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Future Earth","funders":"","keywords":"Computer science","score_opus":0.011983054042270767,"score_gpt":0.21895743237515805,"score_spread":0.2069743783328873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392494786","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":[0.8822944,0.00261634,0.11052606,0.0005744787,0.00007782616,0.0002683114,0.000074284726,0.00028560555,0.0032826473],"genre_scores_gemma":[0.9692562,0.0019446767,0.02399075,0.000018954199,0.000058414447,0.000098991724,0.0013373957,0.000109754175,0.0031848445],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99338144,0.004407415,0.0005112366,0.00089622394,0.0002708065,0.00053286785],"domain_scores_gemma":[0.9958897,0.00045979815,0.00039979705,0.0018941879,0.0011303003,0.0002262166],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0035046355,0.0004519096,0.00044791884,0.00016385684,0.00053344487,0.00034456782,0.0013171678,0.0004907304,0.000028617302],"category_scores_gemma":[0.0008401826,0.00048958656,0.0003876601,0.0003374445,0.00081160147,0.0000115340235,0.0019162095,0.0003172232,0.00001811948],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051813557,0.0011994895,0.1374657,0.0019063177,0.0017604982,0.00006876179,0.017280212,0.057024255,0.74832124,0.019561391,0.003243981,0.012116362],"study_design_scores_gemma":[0.0006616202,0.0000026714392,0.12612659,0.0026624457,0.00040995926,0.000087498665,0.0015099813,0.12743999,0.7266837,0.010983198,0.002051039,0.0013813308],"about_ca_topic_score_codex":0.0016573488,"about_ca_topic_score_gemma":0.015280505,"teacher_disagreement_score":0.086961776,"about_ca_system_score_codex":0.00017105936,"about_ca_system_score_gemma":0.0003601065,"threshold_uncertainty_score":0.99975556},"labels":[],"label_agreement":null},{"id":"W4392592216","doi":"10.3389/fsybi.2024.1337860","title":"Bridging the gap: enhancing science communication in synthetic biology with specific teaching modules, school laboratories, performance and theater","year":2024,"lang":"en","type":"article","venue":"Frontiers in Synthetic Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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 Manitoba","funders":"Technische Universität Berlin; Brandenburger Staatsministerium für Wissenschaft, Forschung und Kultur; Deutsche Forschungsgemeinschaft","keywords":"Bridging (networking); Mathematics education; Computer science; Biology; Psychology","score_opus":0.005591410131697582,"score_gpt":0.22371387952279156,"score_spread":0.21812246939109398,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392592216","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":[0.96320504,0.021860717,0.013539188,0.00050699426,0.0003229474,0.00021254951,0.000006466531,0.00002127771,0.00032480466],"genre_scores_gemma":[0.9928115,0.0026069335,0.004251522,0.0000722282,0.00010622651,0.00004846847,0.00002395627,0.000026060434,0.00005307426],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9980711,0.00033431177,0.00032605606,0.00069374277,0.00008816705,0.00048663575],"domain_scores_gemma":[0.99900764,0.000045547644,0.00007238947,0.0007587075,0.00004805532,0.000067676774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016818144,0.0002266641,0.00028257264,0.0002911495,0.00025203908,0.0000782434,0.0005177897,0.00018106507,0.0000069832986],"category_scores_gemma":[0.00008907949,0.00015725833,0.00003634577,0.0005273221,0.0012837875,0.000019168214,0.00024230822,0.00039628602,0.000003604071],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001630544,0.000076813965,0.3761659,0.0001034746,0.00017571829,0.000009023067,0.0010336549,0.0014441442,0.4539811,0.0033675907,0.0008771872,0.16260232],"study_design_scores_gemma":[0.0034960643,0.0018522759,0.112520665,0.0033431193,0.00043576513,0.0007621226,0.007880973,0.1529506,0.4240146,0.009121316,0.2790865,0.004536005],"about_ca_topic_score_codex":0.000049309732,"about_ca_topic_score_gemma":0.00010312234,"teacher_disagreement_score":0.27820933,"about_ca_system_score_codex":0.00010388707,"about_ca_system_score_gemma":0.00015460249,"threshold_uncertainty_score":0.6412809},"labels":[],"label_agreement":null},{"id":"W4392623872","doi":"10.1101/2024.03.08.584056","title":"Ratiometric control of two microbial populations via a dual chamber bioreactor","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Institute of Genetics; Ministero della Salute; European Commission","keywords":"Bioreactor; Dilution; Dual (grammatical number); Population; Biochemical engineering; Biological system; Single chamber; Control (management); Computer science; Process engineering; Biology; Engineering; Physics; Botany; Artificial intelligence; Biomedical engineering","score_opus":0.011763168694106834,"score_gpt":0.2345303264428643,"score_spread":0.22276715774875747,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392623872","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":[0.98411745,0.005304871,0.0077835796,0.000117442774,0.0013001123,0.0006283335,0.00064399914,0.00009696219,0.000007250806],"genre_scores_gemma":[0.99551404,0.000102387734,0.0025517067,0.00008955926,0.001434305,0.00010956098,0.000009443526,0.00016699417,0.000022006641],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9969634,0.00018554172,0.00081092,0.0011612937,0.0003632389,0.0005156204],"domain_scores_gemma":[0.99711496,0.000020073436,0.0005376659,0.0015024166,0.00058590306,0.00023900987],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00049767055,0.0006197752,0.0007374547,0.0007536789,0.00009570515,0.00010924801,0.00028789346,0.0006967175,0.00004910458],"category_scores_gemma":[0.00011929175,0.0006655048,0.0005453788,0.0012429047,0.0001673397,0.0000063027574,0.0006772795,0.00048231002,0.00005434181],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035368997,0.00011997318,0.0050172587,0.00019656886,0.00078592944,0.000024687215,0.0000028072648,0.0011207105,0.99170554,0.00016840347,0.00082010234,0.0000026686926],"study_design_scores_gemma":[0.0013656873,0.00013442758,0.028524619,0.0001990658,0.0013884893,2.519679e-7,0.0000012065216,0.003173127,0.95932496,0.000013101763,0.0046005133,0.0012745738],"about_ca_topic_score_codex":0.000080380014,"about_ca_topic_score_gemma":0.000020334508,"teacher_disagreement_score":0.032380585,"about_ca_system_score_codex":0.00011050668,"about_ca_system_score_gemma":0.0005773924,"threshold_uncertainty_score":0.9995796},"labels":[],"label_agreement":null},{"id":"W4393029888","doi":"10.1007/978-1-0716-3742-5_1","title":"Visualization of Glutamatergic Neurotransmission in Diverse Model Organisms with Genetically Encoded Indicators","year":2024,"lang":"en","type":"book-chapter","venue":"Neuromethods","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Glutamatergic; Visualization; Neurotransmission; Neuroscience; Biology; Computer science; Genetics; Data mining; Glutamate receptor; Receptor","score_opus":0.015371711418200422,"score_gpt":0.2751245403450827,"score_spread":0.2597528289268823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393029888","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":[0.73420936,0.003828209,0.15879518,0.00014037504,0.00054472045,0.0017086006,0.00016857553,0.00015676503,0.10044818],"genre_scores_gemma":[0.8314496,0.0032345364,0.03415983,0.0003038467,0.00027536217,0.000032201733,0.00047137932,0.00061899354,0.1294542],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99807984,0.000097150085,0.00047408516,0.00076801056,0.00034897233,0.00023193758],"domain_scores_gemma":[0.9990252,0.000016931099,0.00021101395,0.00055212784,0.00007170897,0.00012296709],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022958963,0.0003995816,0.00046718557,0.00050647947,0.000029984343,0.000019258205,0.00028741328,0.00050162466,0.00008228529],"category_scores_gemma":[0.00001578386,0.0003561262,0.0001794748,0.00024042063,0.00014064573,0.0000029912221,0.0001780734,0.00022882203,0.0000066168195],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028846535,0.0000904794,0.00046152025,0.00046553192,0.00033018738,0.000117723735,0.00013923406,0.053976465,0.92912465,0.0067683263,0.00020133359,0.0080361],"study_design_scores_gemma":[0.002709455,0.0034874172,0.0013579058,0.001102406,0.002641328,0.00015667613,0.00002994986,0.07755844,0.845913,0.017761892,0.04396656,0.0033149526],"about_ca_topic_score_codex":0.000002012161,"about_ca_topic_score_gemma":0.0000074582535,"teacher_disagreement_score":0.12463535,"about_ca_system_score_codex":0.000021250924,"about_ca_system_score_gemma":0.0001506575,"threshold_uncertainty_score":0.9998891},"labels":[],"label_agreement":null},{"id":"W4393259637","doi":"10.2139/ssrn.4775945","title":"Robustness and Evolvability: Revisited, Redefined and Applied","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Evolvability; Robustness (evolution); Computer science; Evolutionary biology; Biology; Genetics","score_opus":0.005229748583631717,"score_gpt":0.22128388769035706,"score_spread":0.21605413910672536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393259637","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":[0.8774011,0.117715135,0.003637014,0.00046803168,0.00013318738,0.00021466296,0.0000057139973,0.000020218444,0.00040489912],"genre_scores_gemma":[0.9677209,0.029883875,0.00043591057,0.000044379012,0.00082963426,0.000017098839,0.0000774223,0.00006118165,0.0009295817],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9972969,0.00010281546,0.0003810732,0.00078935234,0.00019650788,0.0012333029],"domain_scores_gemma":[0.99906707,0.000010291228,0.00019234413,0.00050378003,0.00008915534,0.00013735506],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001514354,0.0003706256,0.00043465552,0.00013046068,0.00013341517,0.00015650499,0.0002403725,0.00046958547,0.000007592424],"category_scores_gemma":[0.000037203223,0.00034211835,0.00019285076,0.00011752139,0.000121002515,0.0000015948007,0.0010081532,0.002253015,0.0000021283288],"study_design_candidate":"theoretical_or_conceptual","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":[0.0034229679,0.0006450304,0.017243277,0.00519794,0.036041465,0.000095990275,0.00072103174,0.11019734,0.26981735,0.105842456,0.013373823,0.43740132],"study_design_scores_gemma":[0.0036241086,0.001700606,0.0023565167,0.0008002381,0.0061684437,0.0051754257,0.002014924,0.014712894,0.0072417306,0.9386419,0.012984414,0.0045787836],"about_ca_topic_score_codex":0.0000069295115,"about_ca_topic_score_gemma":0.00014587314,"teacher_disagreement_score":0.83279943,"about_ca_system_score_codex":0.0002018061,"about_ca_system_score_gemma":0.0013062861,"threshold_uncertainty_score":0.9999031},"labels":[],"label_agreement":null},{"id":"W4394298181","doi":"10.6084/m9.figshare.20267685","title":"Additional file 1 of Network-based inference of master regulators in epithelial membrane protein 2-treated human RPE cells","year":2022,"lang":"en","type":"dataset","venue":"Open MIND","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Bruyère","funders":"","keywords":"Cell biology; Membrane protein; Inference; Computer science; Biology; Chemistry; Membrane; Computational biology; Artificial intelligence; Biochemistry","score_opus":0.01692697946505517,"score_gpt":0.253564516963397,"score_spread":0.23663753749834182,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394298181","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009454595,0.000028458497,6.359788e-7,0.0000040744835,0.000027303768,0.0005601786,0.9897878,4.2703178e-7,0.00013652821],"genre_scores_gemma":[0.0012130797,0.000004281291,0.00078760437,0.000013133235,0.00011719026,0.00036024547,0.9957053,0.000025485502,0.00177368],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99785876,0.00027410436,0.0006532769,0.0006096242,0.00031695573,0.00028728778],"domain_scores_gemma":[0.99812233,0.00008593824,0.00071909145,0.0009022028,0.000098152865,0.00007225287],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00023175278,0.0003148583,0.0005978454,0.00014967062,0.00006294648,0.000022778504,0.00091781083,0.0003587686,0.92723095],"category_scores_gemma":[0.00007174778,0.0003326715,0.00020346047,0.0003576695,0.00015584267,0.0000045719094,0.00060296565,0.00021388961,0.000028828545],"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":[0.0001112293,0.00015721374,0.000010992069,0.000043888558,0.00014249976,0.000008713972,0.0000020696416,0.0036838371,0.019263389,1.0576334e-7,0.9762961,0.0002799534],"study_design_scores_gemma":[0.00041082618,0.00023270847,0.000071131515,0.00020851886,0.00007687007,8.6837485e-7,0.0000061422493,0.000039190843,0.07229669,0.000003216632,0.92636406,0.00028979196],"about_ca_topic_score_codex":0.00014534562,"about_ca_topic_score_gemma":0.0011670562,"teacher_disagreement_score":0.92720217,"about_ca_system_score_codex":0.00003215835,"about_ca_system_score_gemma":0.0004310938,"threshold_uncertainty_score":0.99991256},"labels":[],"label_agreement":null},{"id":"W4394989136","doi":"10.1101/2024.04.16.589270","title":"Determining Interaction Directionality in Complex Biochemical Networks from Stationary Measurements","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Directionality; Computer science; Statistical physics; Physics; Biology; Genetics","score_opus":0.029766613252990334,"score_gpt":0.2593874405475685,"score_spread":0.22962082729457817,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394989136","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":[0.9939369,0.0028858827,0.001503493,0.000074996846,0.0010217237,0.0003085488,0.00015918528,0.000097449985,0.000011796623],"genre_scores_gemma":[0.9956489,0.00011409796,0.002610439,0.00013250436,0.0011927462,0.00014828822,0.00003860266,0.0001097822,0.0000046407954],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9969856,0.00024549436,0.00065324764,0.0013199867,0.00037783763,0.00041778965],"domain_scores_gemma":[0.9983193,0.000030336532,0.00029923712,0.0008975712,0.0002804268,0.00017310496],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005048769,0.0005021477,0.0004573806,0.0002164019,0.00008272308,0.00013762678,0.00036905645,0.0006587216,0.000051409996],"category_scores_gemma":[0.00010369827,0.00059448514,0.0002512356,0.0003739984,0.00008786831,0.000008340864,0.0008182721,0.000669597,0.000024515042],"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":[0.00005465416,0.00010602278,0.06938138,0.00008227993,0.00049861555,0.000016484091,0.0000035783082,0.007749312,0.9203398,0.0000052144783,0.0017520895,0.000010527348],"study_design_scores_gemma":[0.0005980867,0.00005071371,0.5677089,0.00049526064,0.00036897208,5.2720544e-8,0.0000060109833,0.02308653,0.40254742,0.000015162631,0.003853846,0.0012690506],"about_ca_topic_score_codex":0.00009821303,"about_ca_topic_score_gemma":0.000033629218,"teacher_disagreement_score":0.5177924,"about_ca_system_score_codex":0.00031466933,"about_ca_system_score_gemma":0.00030587762,"threshold_uncertainty_score":0.99965066},"labels":[],"label_agreement":null},{"id":"W4396508640","doi":"10.1016/j.eswa.2024.124014","title":"Optimal control of Boolean control networks with state-triggered impulses","year":2024,"lang":"en","type":"article","venue":"Expert Systems with Applications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Control (management); Computer science; Boolean network; State (computer science); Boolean function; Impulse control; Artificial intelligence; Algorithm; Neuroscience; Psychology","score_opus":0.0035429652022934185,"score_gpt":0.22069211798651164,"score_spread":0.21714915278421823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396508640","genre_codex":"methods","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":[0.032640185,0.023151899,0.94278145,0.00006848719,0.00005084014,0.000991313,0.000051956686,0.000056014986,0.00020785343],"genre_scores_gemma":[0.9968896,0.00011559697,0.0009223882,0.00005868145,0.00045525393,0.00089912454,0.00010691187,0.000055060613,0.00049739645],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986203,0.00006140293,0.00035740717,0.00046142077,0.0002036527,0.00029586712],"domain_scores_gemma":[0.99888915,0.000043479493,0.00013940975,0.00060597056,0.0001905517,0.00013143447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000209763,0.00022332897,0.00032703415,0.00008419305,0.00008971356,0.000053866497,0.00019843996,0.000114082206,0.0000070608107],"category_scores_gemma":[0.000003260694,0.00016104762,0.00010035559,0.00032995275,0.00014037179,0.0000056013737,0.000019269823,0.00008453788,0.000006729302],"study_design_candidate":"simulation_or_modeling","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":[0.0008240398,0.00019451861,0.004548639,0.00017240358,0.0032345806,0.000016893015,0.0001964425,0.8688794,0.11128653,0.0010548728,0.005772936,0.0038187504],"study_design_scores_gemma":[0.0071468446,0.0021522865,0.0015981959,0.00053467107,0.0010380299,0.0003731469,0.0015266525,0.40297204,0.036664486,0.000016184013,0.5439834,0.0019940534],"about_ca_topic_score_codex":0.0000688178,"about_ca_topic_score_gemma":0.00003807631,"teacher_disagreement_score":0.9642494,"about_ca_system_score_codex":0.000025002979,"about_ca_system_score_gemma":0.00012212562,"threshold_uncertainty_score":0.65673316},"labels":[],"label_agreement":null},{"id":"W4396558984","doi":"10.1101/2024.04.29.591679","title":"Joint distribution of nuclear and cytoplasmic mRNA levels in stochastic models of gene expression: analytical results and parameter inference","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Inference; Expression (computer science); Gene expression; Joint probability distribution; Joint (building); Distribution (mathematics); Computational biology; Messenger RNA; Biology; Statistical physics; Econometrics; Gene; Physics; Mathematics; Computer science; Statistics; Genetics; Artificial intelligence; Engineering; Mathematical analysis","score_opus":0.02082196733065323,"score_gpt":0.23218813778537667,"score_spread":0.21136617045472345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396558984","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":[0.9928148,0.002051312,0.004160562,0.000044788278,0.000082287705,0.00023747486,0.0005912822,0.000015859672,0.0000016762443],"genre_scores_gemma":[0.9977601,0.0002656495,0.0018219204,0.000011422371,0.00007281959,0.000018485454,0.0000037174711,0.000044291166,0.0000015797539],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99786663,0.00010936604,0.00069057604,0.0008495764,0.00021781457,0.00026605758],"domain_scores_gemma":[0.9985122,0.000036180863,0.000324573,0.0007603902,0.00022065161,0.0001460155],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00043914843,0.00033603483,0.0005868568,0.00016140028,0.000030540952,0.000041019557,0.00018502458,0.00049900264,0.0000024622502],"category_scores_gemma":[0.00024180791,0.0003387693,0.000119164935,0.00023754264,0.00023540911,0.000007384571,0.00076923857,0.00033061102,8.809676e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009880748,0.000060525417,0.0008081121,0.00030744186,0.00016944177,0.000008338973,0.000012352815,0.01381321,0.9844663,0.00020231468,0.000049425897,0.0000036906968],"study_design_scores_gemma":[0.0009302954,0.00018357259,0.06474349,0.0011059003,0.00039322,1.4091377e-7,0.000007653255,0.116341196,0.8154245,0.000092783455,0.000047374102,0.0007298913],"about_ca_topic_score_codex":0.000019481553,"about_ca_topic_score_gemma":0.0000026078355,"teacher_disagreement_score":0.16904186,"about_ca_system_score_codex":0.000046469202,"about_ca_system_score_gemma":0.00020456818,"threshold_uncertainty_score":0.9999064},"labels":[],"label_agreement":null},{"id":"W4396805322","doi":"10.5376/gab.2024.15.0006","title":"The Application of Single-Cell Omics Technologies in Neuroscientific Research","year":2024,"lang":"en","type":"article","venue":"Genomics and Applied Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Omics; Computational biology; Neuroscience; Data science; Psychology; Computer science; Cognitive science; Biology; Bioinformatics","score_opus":0.018423591644365644,"score_gpt":0.2656103181671251,"score_spread":0.24718672652275947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396805322","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":[0.99122965,0.0067570074,0.0011034831,0.00021110389,0.00007787022,0.0001849288,0.000008932593,0.00001307583,0.00041397222],"genre_scores_gemma":[0.9978956,0.0016640276,0.00021619613,0.000008701963,0.00004533545,0.000038304035,0.000036373374,0.000011271,0.00008420168],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991373,0.00003850596,0.00018530656,0.00037194355,0.00004247655,0.00022446206],"domain_scores_gemma":[0.9995553,0.000046723613,0.00003583182,0.00031781892,0.000027854001,0.000016459537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005827591,0.000079558675,0.00010230854,0.00010552768,0.0000960022,0.000032728723,0.00022155252,0.00015701256,2.6709472e-7],"category_scores_gemma":[0.00001284345,0.000059683833,0.00003280059,0.00028559612,0.000444479,7.27771e-7,0.00023900805,0.000113286515,0.0000030582055],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014737073,0.000015649053,0.00033489795,0.00001178501,0.000008765433,1.5861808e-7,0.0000141231685,0.00013198995,0.9614827,0.006048945,0.00009700869,0.031839214],"study_design_scores_gemma":[0.00013318792,0.00010381258,0.00022459977,0.0000024419198,0.000009797104,0.000003339393,0.00035119374,0.0019275914,0.7805886,0.007895427,0.20864156,0.00011844426],"about_ca_topic_score_codex":0.0000043513323,"about_ca_topic_score_gemma":0.00004190301,"teacher_disagreement_score":0.20854455,"about_ca_system_score_codex":0.000015667601,"about_ca_system_score_gemma":0.00003909375,"threshold_uncertainty_score":0.2433836},"labels":[],"label_agreement":null},{"id":"W4396832529","doi":"10.1093/toxsci/kfae063","title":"Comparative toxicological assessment of 2 bisphenols using a systems approach: evaluation of the behavioral and transcriptomic responses of <i>Danio rerio</i> to bisphenol A and tetrabromobisphenol A","year":2024,"lang":"en","type":"article","venue":"Toxicological Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Canada; National Research Council Canada","funders":"National Research Council Canada","keywords":"Danio; Zebrafish; Transcriptome; Toxicodynamics; Adverse Outcome Pathway; Toxicogenomics; Computational biology; Biology; Tetrabromobisphenol A; Model organism; Organism; Toxicology; Bioinformatics; Genetics; Toxicokinetics; Gene; Chemistry; Gene expression","score_opus":0.14022690195543547,"score_gpt":0.4004167432083533,"score_spread":0.26018984125291783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396832529","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":[0.995089,0.00305317,0.000797163,0.000050613413,0.000072317656,0.0006942616,0.000025558773,0.000006400904,0.00021152016],"genre_scores_gemma":[0.99749297,0.000029071074,0.0023714418,0.000020311785,0.000019278468,0.000046614696,0.0000017186311,0.0000043125924,0.000014296601],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978444,0.0006190097,0.00040391614,0.00045145993,0.0004883783,0.00019284037],"domain_scores_gemma":[0.99939376,0.000072084695,0.00014752177,0.00018058218,0.0001191558,0.0000869176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016790662,0.00014763167,0.0003908347,0.00006836015,0.00010664049,0.000039588896,0.000255296,0.0001357409,0.000014475983],"category_scores_gemma":[0.00007842861,0.00008781403,0.00009478879,0.000598632,0.0009885004,0.00000970883,0.00015715449,0.00007656039,7.7294416e-8],"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":[0.00004969567,0.00017387969,0.0057211374,0.00004926698,0.000058019454,2.897377e-7,0.00026701656,0.010878295,0.98178273,0.0005062577,0.000022916884,0.000490477],"study_design_scores_gemma":[0.0014710955,0.009434103,0.27771106,0.00038788232,0.0016283451,0.00009115092,0.008673232,0.3626895,0.33619,0.00051051273,0.0003858563,0.0008272562],"about_ca_topic_score_codex":0.000033161097,"about_ca_topic_score_gemma":0.00003181119,"teacher_disagreement_score":0.64559275,"about_ca_system_score_codex":0.000031348045,"about_ca_system_score_gemma":0.0002992797,"threshold_uncertainty_score":0.36421713},"labels":[],"label_agreement":null},{"id":"W4396843135","doi":"10.1142/s0218127424500706","title":"Dynamics of a New Delayed Glucose–Insulin Model with Obesity","year":2024,"lang":"en","type":"article","venue":"International Journal of Bifurcation and Chaos","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Obesity; Hopf bifurcation; Insulin; Diabetes mellitus; Bifurcation; Internal medicine; Endocrinology; Insulin resistance; Control theory (sociology); Dynamics (music); Medicine; Computer science; Physics; Control (management); Nonlinear system","score_opus":0.006256365532215773,"score_gpt":0.24329770834300068,"score_spread":0.2370413428107849,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396843135","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":[0.8858103,0.002286529,0.11026036,0.0013902542,0.00010648063,0.000029665242,0.00001029244,0.000002914747,0.000103168306],"genre_scores_gemma":[0.9962966,0.0008630111,0.0019030824,0.000075781376,0.00023556365,5.730178e-7,0.000036861962,0.0000081667895,0.00058036787],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99940574,0.000013177265,0.00022273093,0.000098010816,0.00020797785,0.00005234911],"domain_scores_gemma":[0.9994336,0.0000056696285,0.000140469,0.000072324816,0.00029043172,0.00005753218],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011416755,0.00006762814,0.00009159654,0.000103782666,0.000012521966,0.000025630337,0.00013239616,0.00005009854,0.000012086387],"category_scores_gemma":[0.000011258683,0.000054232216,0.00007261167,0.00006863878,0.000029695739,0.000009162973,0.000027700076,0.000057387886,8.524602e-7],"study_design_candidate":"simulation_or_modeling","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":[0.0029174937,0.0007306699,0.024642453,0.00015959515,0.0085485,0.00009638643,0.002167826,0.23739612,0.4208006,0.018034372,0.014986825,0.26951918],"study_design_scores_gemma":[0.002090544,0.00083256187,0.0077898414,0.00027434298,0.00041176935,0.0006993247,0.0003743112,0.85959905,0.11268674,0.004950529,0.00988673,0.0004042558],"about_ca_topic_score_codex":0.000011797588,"about_ca_topic_score_gemma":0.000053431482,"teacher_disagreement_score":0.62220293,"about_ca_system_score_codex":0.00002652293,"about_ca_system_score_gemma":0.0001780563,"threshold_uncertainty_score":0.22115256},"labels":[],"label_agreement":null},{"id":"W4396909065","doi":"10.30919/es1152","title":"s Generalization of Gene Network Representation on the Hypercube","year":2024,"lang":"en","type":"article","venue":"Engineered Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"BC Cancer Agency","funders":"","keywords":"Hypercube; Generalization; Representation (politics); Relation (database); Dimension (graph theory); Theoretical computer science; Computer science; Matrix (chemical analysis); Connection (principal bundle); State (computer science); Visibility; Discrete mathematics; Algorithm; Mathematics; Combinatorics; Parallel computing; Data mining","score_opus":0.011186395314374178,"score_gpt":0.24470514847127844,"score_spread":0.23351875315690426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396909065","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":[0.95996606,0.0017956075,0.037086483,0.00018589724,0.00032939593,0.00008712327,0.0000025834552,0.00001773024,0.00052913575],"genre_scores_gemma":[0.99826854,0.00006791256,0.0009821433,0.000058772584,0.00030430654,0.0000065077725,0.000020927324,0.000007937791,0.00028295277],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992957,0.000026219173,0.0001078652,0.0002326372,0.00020075719,0.00013683492],"domain_scores_gemma":[0.9995593,0.00001538418,0.000020276077,0.00031837693,0.000056746227,0.00002994732],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003862985,0.000063056264,0.000054209773,0.000049066653,0.00006818389,0.00002634086,0.0002036161,0.000031103962,0.000014380776],"category_scores_gemma":[0.00006444114,0.000044963836,0.00005026256,0.00079319737,0.000106695334,0.0000042462693,0.000031413518,0.00003422627,0.0000062814893],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000019474583,0.000003309158,0.00009686224,0.0000023695177,0.0000136655635,4.0015638e-7,0.00002537238,0.34155408,0.6536865,0.0019569404,0.0018954856,0.0007630076],"study_design_scores_gemma":[0.000038151557,0.000049581504,0.0028049895,0.000013981706,0.000020522084,0.0000049953337,0.000020186953,0.1427167,0.8507412,0.0001655407,0.003330041,0.00009408626],"about_ca_topic_score_codex":0.0000027236924,"about_ca_topic_score_gemma":0.0000014975782,"teacher_disagreement_score":0.19883738,"about_ca_system_score_codex":0.000011454447,"about_ca_system_score_gemma":0.000059522965,"threshold_uncertainty_score":0.1833572},"labels":[],"label_agreement":null},{"id":"W4399607148","doi":"10.3934/mbe.2024273","title":"Analytic delay distributions for a family of gene transcription models","year":2024,"lang":"en","type":"article","venue":"Mathematical Biosciences & Engineering","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Lethbridge","funders":"","keywords":"Transcription (linguistics); Gene; Genetics; Biology; Mathematics; Computational biology; Computer science","score_opus":0.015452207436859738,"score_gpt":0.23901801110295007,"score_spread":0.22356580366609033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399607148","genre_codex":"methods","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":[0.3041103,0.0010679098,0.69453865,0.000035599758,0.00005934351,0.00008859929,0.00003143719,0.000019485366,0.00004870813],"genre_scores_gemma":[0.9800849,0.000030858344,0.019687654,0.0000061305745,0.0000592538,0.000028298642,0.000031379313,0.000010535037,0.000060990413],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992134,0.0000066082257,0.00021898316,0.00023632094,0.00013169837,0.00019301008],"domain_scores_gemma":[0.99969345,0.000022628852,0.000019457084,0.00016488004,0.000038649705,0.000060905382],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002359767,0.00010276177,0.00014262577,0.00007253618,0.000034990768,0.000031370346,0.00014467345,0.000063583946,0.000004712929],"category_scores_gemma":[0.00003481504,0.00008662984,0.00017673936,0.0003108053,0.00005967834,0.000008224824,0.000017196502,0.000031603773,0.000002007386],"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":[0.0000021897406,0.00001969648,0.0000028612453,0.00010217175,0.00004844232,4.832622e-7,0.000031938038,0.045430597,0.94025284,0.013784135,0.000059998012,0.00026463528],"study_design_scores_gemma":[0.000053966498,0.00006431846,0.000025296948,0.000041887524,0.000088439556,0.0000065660997,0.000024895664,0.83276814,0.16357195,0.0024737967,0.0007654272,0.000115295385],"about_ca_topic_score_codex":9.646803e-7,"about_ca_topic_score_gemma":6.914229e-7,"teacher_disagreement_score":0.78733754,"about_ca_system_score_codex":0.000013690144,"about_ca_system_score_gemma":0.000033612007,"threshold_uncertainty_score":0.35326624},"labels":[],"label_agreement":null},{"id":"W4399765402","doi":"10.32920/26052829.v1","title":"The Search for Non-equilibrium States in Chemical Reaction Networks","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Toronto Metropolitan University","funders":"","keywords":"Economics; Computer science; Mathematical economics","score_opus":0.00990470336419323,"score_gpt":0.2693889064071084,"score_spread":0.25948420304291514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399765402","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":[0.9888776,0.0047023008,0.003255273,0.0009621236,0.00071709167,0.000646044,0.000017173086,0.000026537668,0.00079588743],"genre_scores_gemma":[0.9934949,0.0011386563,0.00034294362,0.000058759542,0.0010924814,0.00019013166,0.00088574615,0.000054693628,0.0027416423],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99845153,0.000049781447,0.00031349531,0.0006540159,0.00013559868,0.00039557886],"domain_scores_gemma":[0.99907565,0.000046704852,0.00005818424,0.0006530527,0.00009910773,0.00006729988],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005556677,0.00023499074,0.00022123154,0.000052935146,0.000041909887,0.000099710545,0.00034338937,0.0004989344,0.0000039785114],"category_scores_gemma":[0.000017125674,0.00017571334,0.00029633232,0.00012184865,0.00007928173,7.8141784e-7,0.0011266401,0.0004384206,0.000006341941],"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":[0.00049384503,0.00010393033,0.001112597,0.0004023138,0.0012323941,0.000006972613,0.00008220947,0.22453953,0.6690969,0.00018312207,0.080047645,0.022698559],"study_design_scores_gemma":[0.00043945556,0.00010809851,0.0003742075,0.00013527137,0.00021895269,0.0000075860285,0.00015947412,0.6335017,0.33055222,0.0032837943,0.0304995,0.00071976887],"about_ca_topic_score_codex":0.00005136457,"about_ca_topic_score_gemma":0.00013685181,"teacher_disagreement_score":0.40896216,"about_ca_system_score_codex":0.000057421534,"about_ca_system_score_gemma":0.00014972607,"threshold_uncertainty_score":0.71653825},"labels":[],"label_agreement":null},{"id":"W4399765500","doi":"10.32920/26052829","title":"The Search for Non-equilibrium States in Chemical Reaction Networks","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Toronto Metropolitan University","funders":"","keywords":"Statistical physics; Computer science; Mathematical economics; Economics; Physics","score_opus":0.00990470336419323,"score_gpt":0.2693889064071084,"score_spread":0.25948420304291514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399765500","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":[0.9888776,0.0047023008,0.003255273,0.0009621236,0.00071709167,0.000646044,0.000017173086,0.000026537668,0.00079588743],"genre_scores_gemma":[0.9934949,0.0011386563,0.00034294362,0.000058759542,0.0010924814,0.00019013166,0.00088574615,0.000054693628,0.0027416423],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99845153,0.000049781447,0.00031349531,0.0006540159,0.00013559868,0.00039557886],"domain_scores_gemma":[0.99907565,0.000046704852,0.00005818424,0.0006530527,0.00009910773,0.00006729988],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005556677,0.00023499074,0.00022123154,0.000052935146,0.000041909887,0.000099710545,0.00034338937,0.0004989344,0.0000039785114],"category_scores_gemma":[0.000017125674,0.00017571334,0.00029633232,0.00012184865,0.00007928173,7.8141784e-7,0.0011266401,0.0004384206,0.000006341941],"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":[0.00049384503,0.00010393033,0.001112597,0.0004023138,0.0012323941,0.000006972613,0.00008220947,0.22453953,0.6690969,0.00018312207,0.080047645,0.022698559],"study_design_scores_gemma":[0.00043945556,0.00010809851,0.0003742075,0.00013527137,0.00021895269,0.0000075860285,0.00015947412,0.6335017,0.33055222,0.0032837943,0.0304995,0.00071976887],"about_ca_topic_score_codex":0.00005136457,"about_ca_topic_score_gemma":0.00013685181,"teacher_disagreement_score":0.40896216,"about_ca_system_score_codex":0.000057421534,"about_ca_system_score_gemma":0.00014972607,"threshold_uncertainty_score":0.71653825},"labels":[],"label_agreement":null},{"id":"W4400804041","doi":"10.1515/jib-2024-0015","title":"Specifications of standards in systems and synthetic biology: status, developments, and tools in 2024","year":2024,"lang":"en","type":"editorial","venue":"Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"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":"Synthetic biology; Computer science; Engineering; Systems engineering; Computational biology; Biology","score_opus":0.016714085402925575,"score_gpt":0.2942096760844347,"score_spread":0.27749559068150914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400804041","genre_codex":"editorial","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"editorial","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14817213,0.25520125,0.025793932,0.00053149957,0.5042413,0.008420956,0.0159073,0.00014042412,0.041591257],"genre_scores_gemma":[0.359455,0.33204424,0.17430973,0.00061001175,0.1148604,0.0006337112,0.014523677,0.0007980763,0.0027651761],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9927077,0.00015452501,0.004881647,0.000293232,0.0012305385,0.000732334],"domain_scores_gemma":[0.993916,0.000442978,0.0030108371,0.0005448502,0.0017455124,0.0003398221],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0027278839,0.0009112391,0.0017776038,0.001806527,0.000077950375,0.00042273384,0.0006667453,0.001225669,0.000015441443],"category_scores_gemma":[0.0020717243,0.0006616789,0.00025025682,0.0011293801,0.0006383774,0.00040236098,0.00050408684,0.0013956879,0.00000958086],"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":[0.00112597,0.0003199601,0.004011798,0.010936104,0.0067959093,0.000042105432,0.04619944,0.0009902919,0.0006841815,0.0018675454,0.8658619,0.061164778],"study_design_scores_gemma":[0.0019565672,0.0009698183,0.00041114635,0.0032503053,0.00055992795,0.00011539949,0.019923948,0.0043098764,0.00074724713,0.000087622066,0.9666753,0.0009928871],"about_ca_topic_score_codex":0.000047721525,"about_ca_topic_score_gemma":0.00014269378,"teacher_disagreement_score":0.38938087,"about_ca_system_score_codex":0.0003649002,"about_ca_system_score_gemma":0.0028732368,"threshold_uncertainty_score":0.9995834},"labels":[],"label_agreement":null},{"id":"W4400998731","doi":"10.1038/s41467-024-50489-5","title":"Multi-condensate state as a functional strategy to optimize the cell signaling output","year":2024,"lang":"en","type":"article","venue":"Nature Communications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"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":"University of Toronto; University of Connecticut; National Institute of General Medical Sciences; Washington University in St. Louis","keywords":"Biological system; Statistical physics; Function (biology); Computer science; Work (physics); Statistical mechanics; Diffusion; Nucleation; State (computer science); Physics; Biology; Quantum mechanics; Evolutionary biology; Algorithm","score_opus":0.024415436627271282,"score_gpt":0.289844814579127,"score_spread":0.26542937795185567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400998731","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":[0.83331305,0.13022901,0.018622853,0.010836396,0.00073345937,0.0009271449,0.00013531509,0.00018679831,0.0050159628],"genre_scores_gemma":[0.98578215,0.00047625406,0.006359476,0.0007665075,0.00012317933,0.000056991517,0.00023709747,0.00002768028,0.006170694],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99906385,0.00014752834,0.00018242712,0.00028393322,0.00013961374,0.00018262131],"domain_scores_gemma":[0.9982518,0.00006759228,0.000039723996,0.00140938,0.00014991919,0.000081618455],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027405584,0.00014197461,0.000097293836,0.000063419495,0.00027171167,0.000109913155,0.0007306587,0.00018401368,0.00003086691],"category_scores_gemma":[0.00003929952,0.00011015157,0.00015050918,0.00031010894,0.00007867664,0.000004312906,0.00035952718,0.0004962286,0.000116899275],"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":[0.00005469352,0.00017932162,0.0002888499,0.000028623148,0.0006613198,0.0000051726183,0.0003761479,0.16873315,0.77683777,0.0009819404,0.047029015,0.004823996],"study_design_scores_gemma":[0.00070621475,0.00024515984,0.002991404,0.00006549468,0.00041764733,0.00004616328,0.00066152593,0.067101896,0.12292863,0.00050002115,0.80349714,0.00083871157],"about_ca_topic_score_codex":0.000014245682,"about_ca_topic_score_gemma":0.00020945753,"teacher_disagreement_score":0.7564681,"about_ca_system_score_codex":0.000024177438,"about_ca_system_score_gemma":0.00015718672,"threshold_uncertainty_score":0.44918507},"labels":[],"label_agreement":null},{"id":"W4401285541","doi":"10.1016/j.biosystems.2024.105281","title":"Robustness and evolvability: Revisited, redefined and applied","year":2024,"lang":"en","type":"article","venue":"Biosystems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Concordia University","funders":"Alliance de recherche numérique du Canada","keywords":"Evolvability; Robustness (evolution); Computer science; Theoretical computer science; Fitness landscape; Systems biology; Synthetic biology; Artificial intelligence; Computational biology; Biology; Genetics","score_opus":0.0071371355057214605,"score_gpt":0.2154015793917759,"score_spread":0.20826444388605445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401285541","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":[0.97059196,0.02745492,0.00077547,0.000109928056,0.00010876624,0.00017923066,0.0000066266703,0.000037119764,0.0007360035],"genre_scores_gemma":[0.9985482,0.0002878936,0.00029273255,0.00002438743,0.00032482162,0.000017064272,0.000043522625,0.000020043832,0.00044134381],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99910855,0.000038381626,0.00017173156,0.0004507912,0.00008379018,0.00014674649],"domain_scores_gemma":[0.99955827,0.000009531163,0.000027683096,0.00030155483,0.000025625386,0.000077336874],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026974495,0.00013251166,0.0001732262,0.000047425678,0.000052288866,0.000079456455,0.000060352617,0.00012947572,0.0000067324427],"category_scores_gemma":[0.000013211072,0.00011516756,0.00004708404,0.000140466,0.000056528348,0.0000017883721,0.00008591902,0.000042111966,0.0000036744948],"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":[0.000089965135,0.000029706382,0.008418211,0.0013410295,0.00054664945,0.000011628743,0.00009333621,0.0005003524,0.9632636,0.0011647785,0.01145871,0.013082075],"study_design_scores_gemma":[0.002707948,0.0009615769,0.019837026,0.001073993,0.0013825266,0.0008168816,0.0011574487,0.07616263,0.19708197,0.00038903017,0.6950026,0.0034263462],"about_ca_topic_score_codex":0.0000052557607,"about_ca_topic_score_gemma":0.000009934962,"teacher_disagreement_score":0.7661816,"about_ca_system_score_codex":0.000009802233,"about_ca_system_score_gemma":0.000022624568,"threshold_uncertainty_score":0.4696397},"labels":[],"label_agreement":null},{"id":"W4401728618","doi":"10.1186/s12859-024-05816-4","title":"Modeling relaxation experiments with a mechanistic model of gene expression","year":2024,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"York University","funders":"Laboratoire d'Excellence Ecofect; Agence Nationale de la Recherche; Université de Lyon; U.S. Department of Veterans Affairs","keywords":"DNA microarray; Computational biology; Relaxation (psychology); Population; Gene expression; Expression (computer science); Gene; Biology; Biological system; Computer science; Bioinformatics; Genetics; Neuroscience; Medicine","score_opus":0.021187813006774928,"score_gpt":0.24732616860079504,"score_spread":0.22613835559402012,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401728618","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":[0.15760368,0.0007277521,0.84129596,0.0000023175337,0.000031778272,0.00012720963,0.000007832474,0.000019086536,0.00018439423],"genre_scores_gemma":[0.731025,0.00005165738,0.26862475,0.000014116193,0.000030790656,0.00001694819,0.00008661032,0.000016847129,0.00013326727],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99921286,0.0000150122205,0.00030702996,0.00013954706,0.00019044976,0.00013510897],"domain_scores_gemma":[0.9994901,0.0000045722522,0.00007671274,0.0003119481,0.00006917451,0.000047535083],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012486153,0.00012624357,0.000141179,0.00007135255,0.000040393803,0.000024828189,0.00011073711,0.000100387704,0.0000034459454],"category_scores_gemma":[0.000016013222,0.00009721708,0.000078593745,0.000112433154,0.000021163884,0.000010653511,0.000050789236,0.00004230122,0.000005255283],"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":[0.000026766837,0.000012770868,0.000015421478,0.0006600219,0.00004716487,2.1033544e-7,0.00020914078,0.73817706,0.2606256,0.00011170279,0.00004632238,0.000067789755],"study_design_scores_gemma":[0.00010366875,0.00005280848,4.922981e-7,0.00018416073,0.00005780737,0.0000034726127,0.00014220628,0.753179,0.24611123,0.00006576442,0.0000057229286,0.00009364317],"about_ca_topic_score_codex":0.0000014489563,"about_ca_topic_score_gemma":0.0000034393802,"teacher_disagreement_score":0.5734213,"about_ca_system_score_codex":0.000015529191,"about_ca_system_score_gemma":0.00010092697,"threshold_uncertainty_score":0.39643976},"labels":[],"label_agreement":null},{"id":"W4401774132","doi":"10.1007/s12551-024-01219-0","title":"Session commentaries: synthetic and constructive biology","year":2024,"lang":"en","type":"review","venue":"Biophysical Reviews","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Iketani Science and Technology Foundation","keywords":"Synthetic biology; Constructive; Theme (computing); Session (web analytics); Field (mathematics); Chemistry; Computer science; Biology; Computational biology; Mathematics; World Wide Web; Process (computing)","score_opus":0.03246356280612227,"score_gpt":0.34312552712524425,"score_spread":0.31066196431912196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401774132","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000039667786,0.99869484,0.000076302014,0.00003332401,0.00023936077,0.0006692249,0.00006813814,0.000015137782,0.00016400972],"genre_scores_gemma":[0.000048399197,0.99794203,0.00025730865,0.000105283965,0.00062696845,0.00016467262,0.00045989334,0.00005862983,0.00033678702],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99764127,0.00046144947,0.0006293182,0.00089617947,0.00008102675,0.000290781],"domain_scores_gemma":[0.9988191,0.000056417306,0.00028917487,0.00065974955,0.000027537655,0.00014803407],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022871274,0.00057429756,0.00200648,0.00007799344,0.00007576242,0.00004399934,0.00026527434,0.00041979871,0.000028312705],"category_scores_gemma":[0.0001011163,0.00037078102,0.00092628394,0.00025836396,0.00036427047,0.0000020014286,0.0004399632,0.000265612,0.00024046534],"study_design_candidate":"not_applicable","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":[0.0000023877592,0.000025218895,0.0000012038267,0.0058179023,0.0003417528,0.0000022065112,0.000004659514,3.082916e-8,0.00041568736,0.0004571182,0.008333242,0.9845986],"study_design_scores_gemma":[0.00004643341,0.000088287255,2.119133e-7,0.0045859492,0.0025480513,0.000026238715,0.000003594165,0.0000045376996,0.000038701506,0.0001239962,0.99216175,0.00037222213],"about_ca_topic_score_codex":0.0000049180253,"about_ca_topic_score_gemma":0.0000027517708,"teacher_disagreement_score":0.98422635,"about_ca_system_score_codex":0.0000372403,"about_ca_system_score_gemma":0.0001099188,"threshold_uncertainty_score":0.9998744},"labels":[],"label_agreement":null},{"id":"W4402010313","doi":"10.1142/s1793524524501146","title":"Dynamics analysis in a delayed glucose-insulin model incorporating obesity","year":2024,"lang":"en","type":"article","venue":"International Journal of Biomathematics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Insulin; Obesity; Dynamics (music); Medicine; Mathematics; Internal medicine; Computer science; Physics","score_opus":0.00899897748852384,"score_gpt":0.2720290545111547,"score_spread":0.26303007702263087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402010313","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":[0.7495836,0.0009869832,0.24890608,0.00022016186,0.00013914771,0.000034524473,0.000020299956,0.0000061325036,0.000103072714],"genre_scores_gemma":[0.97824496,0.00017199547,0.021184105,0.00003741495,0.0001992871,0.0000015841163,0.000063570165,0.000017422673,0.00007964355],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99851954,0.000045674315,0.00072048354,0.00017136378,0.00041740632,0.00012551786],"domain_scores_gemma":[0.99906754,0.00003153992,0.00033088366,0.00017782285,0.00032712315,0.00006506225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006259543,0.00013899893,0.00026586317,0.0006142125,0.000020203692,0.000085472544,0.00042301795,0.00011415935,0.00000894275],"category_scores_gemma":[0.0000859257,0.00012392284,0.00040129563,0.00056535925,0.0000406218,0.000014162426,0.00010443175,0.000111143636,0.00000415354],"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":[0.0002614139,0.0009437498,0.022049207,0.00014050993,0.019405415,0.0006388096,0.00090975227,0.7585068,0.17375703,0.009208801,0.00092115765,0.013257383],"study_design_scores_gemma":[0.00022229034,0.00005227541,0.0003689679,0.00006833835,0.00039520202,0.00010228674,0.00009127145,0.98296463,0.008429653,0.0071344683,0.000037886355,0.00013272172],"about_ca_topic_score_codex":0.000006702128,"about_ca_topic_score_gemma":0.00020086256,"teacher_disagreement_score":0.22866137,"about_ca_system_score_codex":0.00013618759,"about_ca_system_score_gemma":0.00016409687,"threshold_uncertainty_score":0.50534266},"labels":[],"label_agreement":null},{"id":"W4402320855","doi":"10.1177/00236772241247105","title":"Depicting variability and uncertainty using intervals and error bars","year":2024,"lang":"en","type":"article","venue":"Laboratory Animals","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"Statistics; Notation; Range (aeronautics); Variation (astronomy); Interval (graph theory); Population; Population mean; Confidence interval; Sample (material); Mathematics; Econometrics; Demography; Arithmetic; Combinatorics","score_opus":0.013732717550587099,"score_gpt":0.27552833592704296,"score_spread":0.2617956183764559,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402320855","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":[0.99212027,0.006779341,0.0007303959,0.000057938574,0.000088948815,0.00008826166,0.000031448035,0.000029142704,0.00007425785],"genre_scores_gemma":[0.99810994,0.000093545685,0.0014289403,0.00009920799,0.00020127319,0.000005461267,0.000008504967,0.000022628728,0.000030480707],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988488,0.00018873466,0.00020671304,0.00048312813,0.00007731409,0.00019532755],"domain_scores_gemma":[0.9995127,0.000035715315,0.000042284086,0.00023201582,0.00007749486,0.00009979822],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073422905,0.00015530961,0.00017768562,0.000041436404,0.000097371,0.000086384505,0.000069517795,0.0001311745,0.000022886905],"category_scores_gemma":[0.000118920085,0.00014889172,0.00004947444,0.00020488923,0.00011154345,0.000007922994,0.00013776058,0.000085343316,0.000001806105],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003353416,0.00001589045,0.026741479,0.00015112039,0.00022749547,0.000013844248,0.00014150985,0.0008231897,0.96942663,0.00041795033,0.00023118648,0.0017761805],"study_design_scores_gemma":[0.0019311961,0.001492793,0.09802472,0.000856117,0.0020585984,0.00030249218,0.0027778642,0.19034098,0.49249947,0.0037446427,0.20207995,0.0038911637],"about_ca_topic_score_codex":0.000009866955,"about_ca_topic_score_gemma":0.000015897222,"teacher_disagreement_score":0.47692713,"about_ca_system_score_codex":0.000019432282,"about_ca_system_score_gemma":0.000081532424,"threshold_uncertainty_score":0.60716283},"labels":[],"label_agreement":null},{"id":"W4402364254","doi":"10.1128/mbio.02229-24","title":"Loss of Gre factors leads to phenotypic heterogeneity and cheating in <i>Escherichia coli</i> populations under nitric oxide stress","year":2024,"lang":"en","type":"article","venue":"mBio","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"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 Chemical, Bioengineering, Environmental, and Transport Systems; Natural Sciences and Engineering Research Council of Canada; Keio University; Princeton University; National Science Foundation","keywords":"Cheating; Phenotype; Escherichia coli; Microbiology; Biology; Genetics; Evolutionary biology; Gene","score_opus":0.01788545674222495,"score_gpt":0.2659275334263129,"score_spread":0.24804207668408798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402364254","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":[0.9969793,0.0016926107,0.0010480181,0.00005082679,0.00004485792,0.00010516102,0.000024389648,0.000011190279,0.000043641754],"genre_scores_gemma":[0.9991288,0.000025978594,0.000546288,0.00005956633,0.000050753966,0.0000072283588,0.00007032116,0.000019064415,0.000091963884],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991833,0.00004777812,0.00020766068,0.00029574634,0.00008853956,0.00017695512],"domain_scores_gemma":[0.9996457,0.000010179461,0.00003402062,0.00020966094,0.00002930363,0.0000711075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008982497,0.00012768245,0.0001606808,0.000089487614,0.00003894652,0.000021891847,0.000086643246,0.00010440957,0.0000058149176],"category_scores_gemma":[0.000017147102,0.00012467068,0.0000711643,0.00037805072,0.00003819173,0.0000037419384,0.00008364348,0.00006697444,0.0000020878824],"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":[0.000007849324,0.000024984909,0.49977192,0.000044752152,0.000047126214,0.0000014307483,0.000040183546,0.006970969,0.49276906,0.00005991831,0.000059147103,0.00020264974],"study_design_scores_gemma":[0.0001483625,0.000045215704,0.6977581,0.000047884307,0.00006148693,0.0000016972938,0.0000992447,0.00093097065,0.30030006,0.000091425,0.00030612198,0.00020942281],"about_ca_topic_score_codex":0.00012732844,"about_ca_topic_score_gemma":0.00093987107,"teacher_disagreement_score":0.19798617,"about_ca_system_score_codex":0.000023527153,"about_ca_system_score_gemma":0.000033142238,"threshold_uncertainty_score":0.5083923},"labels":[],"label_agreement":null},{"id":"W4402409541","doi":"10.1103/physreve.110.034309","title":"Characterizing the nonmonotonic behavior of mutual information along biochemical reaction cascades","year":2024,"lang":"en","type":"article","venue":"Physical review. E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biological system; Mutual information; Statistical physics; Neuroscience; Computer science; Chemistry; Cognitive science; Psychology; Cognitive psychology; Biophysics; Artificial intelligence; Biology; Physics","score_opus":0.009014458584996951,"score_gpt":0.2905989320509497,"score_spread":0.2815844734659528,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402409541","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":[0.98755115,0.011647325,0.00009520969,0.00028122094,0.00007197261,0.00020639444,0.000008134533,0.000012727104,0.00012587404],"genre_scores_gemma":[0.99402004,0.00521007,0.00002535505,0.0001676851,0.00031049497,0.000064270185,0.00017151519,0.000010032013,0.000020539292],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992799,0.000045501052,0.00024536965,0.00015614604,0.00014557372,0.00012748851],"domain_scores_gemma":[0.9995273,0.000018035798,0.00008612932,0.0002818893,0.000048944075,0.000037708003],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017038948,0.00011130947,0.00017564303,0.000021948295,0.000033904525,0.000019337142,0.00013133764,0.000046383255,0.0000055023243],"category_scores_gemma":[0.000047216643,0.00007688887,0.00024283932,0.00018175704,0.000057759753,0.000015066102,0.00006600378,0.00010382445,0.00004542425],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000052429737,0.000025738671,0.0001195658,0.00023671071,0.000054735618,4.805448e-7,0.00003628246,0.0000021318501,0.97938144,0.00011531283,0.0010102657,0.019012112],"study_design_scores_gemma":[0.00007541572,0.00008141227,0.0048375977,0.00042073792,0.00051098363,0.000021544658,0.000022507822,0.001127505,0.8982035,0.000049027807,0.09445227,0.00019749053],"about_ca_topic_score_codex":0.000007566541,"about_ca_topic_score_gemma":0.000001261834,"teacher_disagreement_score":0.09344201,"about_ca_system_score_codex":0.000015826456,"about_ca_system_score_gemma":0.0000374754,"threshold_uncertainty_score":0.3135437},"labels":[],"label_agreement":null},{"id":"W4402547787","doi":"10.1007/s00285-024-02138-0","title":"Graph-based, dynamics-preserving reduction of (bio)chemical systems","year":2024,"lang":"en","type":"article","venue":"Journal of Mathematical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"Natural Sciences and Engineering Research Council of Canada; University of Lethbridge","keywords":"Reduction (mathematics); Mathematics; Graph; Dynamics (music); Theoretical computer science; Computer science; Biological system; Discrete mathematics; Biology; Physics; Geometry","score_opus":0.010109779307757817,"score_gpt":0.2585284779761892,"score_spread":0.24841869866843141,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402547787","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":[0.92120457,0.0054425164,0.07215975,0.00035348363,0.00042967108,0.00008039244,0.000008753501,0.000008951389,0.00031189373],"genre_scores_gemma":[0.9963589,0.000076657634,0.0030182728,0.000010106317,0.00041403648,0.0000027785245,0.000021597367,0.000016918182,0.000080740116],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987247,0.00012922788,0.00065357704,0.00017806776,0.00013742587,0.0001769857],"domain_scores_gemma":[0.99917644,0.0000653281,0.00024197545,0.0002518525,0.00017754966,0.0000868792],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061326654,0.00013038055,0.00036755225,0.00015706541,0.000018573915,0.000017836559,0.00025233856,0.00024054284,0.000040216622],"category_scores_gemma":[0.00015481832,0.00009732915,0.000339461,0.00018607324,0.00016422605,0.00000440196,0.00006636894,0.00015433252,0.0000058052474],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008795412,0.00012689842,0.00032167023,0.0004544994,0.0005298693,0.000011258086,0.000023426266,0.0014861018,0.9830625,0.010340518,0.0022988208,0.001256485],"study_design_scores_gemma":[0.0016336355,0.0025619192,0.00013127601,0.0015662069,0.0014884443,0.0032533486,0.00073027366,0.16814783,0.742948,0.06727097,0.009277954,0.000990128],"about_ca_topic_score_codex":0.000001706628,"about_ca_topic_score_gemma":6.293381e-7,"teacher_disagreement_score":0.2401145,"about_ca_system_score_codex":0.00003137944,"about_ca_system_score_gemma":0.000088260684,"threshold_uncertainty_score":0.39689678},"labels":[],"label_agreement":null},{"id":"W4403225196","doi":"10.37394/232023.2024.4.5","title":"Artificial Intelligence and Machine Learning with Moment Generating Functions to Enhance Biological Count Data Analysis","year":2024,"lang":"en","type":"article","venue":"MOLECULAR SCIENCES AND APPLICATIONS","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"McGill University","funders":"","keywords":"Moment (physics); Computer science; Artificial intelligence; Machine learning; Count data; Biological data; Mathematics; Statistics; Physics; Biology; Bioinformatics","score_opus":0.03250055710611216,"score_gpt":0.30166366590613314,"score_spread":0.269163108800021,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403225196","genre_codex":"methods","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":[0.28729662,0.003926369,0.7082398,0.00034473542,0.000006982056,0.00011120092,0.000022098922,0.000012564282,0.000039623465],"genre_scores_gemma":[0.9888302,0.00032822127,0.010312205,0.00010481467,0.00006573496,0.00007662243,0.00019373729,0.0000054959987,0.00008296506],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99885607,0.00003326953,0.00013885762,0.00070203346,0.00011969894,0.00015008746],"domain_scores_gemma":[0.9995389,0.000012067857,0.000027611139,0.0003046239,0.00003062277,0.000086160806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032221852,0.00010052561,0.0000998894,0.00009475064,0.00033831576,0.00016579848,0.00019076011,0.0000365699,0.000008857055],"category_scores_gemma":[0.000008411707,0.0000762294,0.000028595712,0.0009875913,0.00018074144,0.000006344127,0.00022735649,0.000057889527,0.000004515274],"study_design_candidate":"simulation_or_modeling","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":[0.000010850847,0.000060123344,0.00485968,0.00001539767,0.00055406376,0.0000044776766,0.00007550154,0.23562123,0.53805447,0.005903475,0.00006986273,0.21477088],"study_design_scores_gemma":[0.000026389835,0.00058184785,0.0007731545,0.000019914052,0.00073718146,0.00002966859,0.00044644467,0.8190988,0.053634528,0.0004626516,0.12357669,0.00061272626],"about_ca_topic_score_codex":0.000025361112,"about_ca_topic_score_gemma":0.00012617122,"teacher_disagreement_score":0.70153356,"about_ca_system_score_codex":0.00000569326,"about_ca_system_score_gemma":0.000033707925,"threshold_uncertainty_score":0.31085446},"labels":[],"label_agreement":null},{"id":"W4403482142","doi":"10.1101/2024.10.15.618412","title":"Parameter Dependence in Identifiability Applied to FP-Fisher-KPP Reaction-Diffusion Equations Parameterized for Tauopathy Network Modeling","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Identifiability; Parameterized complexity; Tauopathy; Diffusion; Applied mathematics; Mathematics; Physics; Statistics; Combinatorics; Thermodynamics","score_opus":0.017160483488605372,"score_gpt":0.24068746934073718,"score_spread":0.2235269858521318,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403482142","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":[0.8721734,0.00084877945,0.123758234,0.00011757284,0.0010831446,0.0017834858,0.00010951248,0.00012065908,0.00000521171],"genre_scores_gemma":[0.9771747,0.000113028356,0.019549783,0.00018078943,0.000898359,0.0018814738,0.00001108845,0.00017894765,0.0000118195285],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99540174,0.00019865873,0.0010116902,0.002160428,0.00039893156,0.0008285242],"domain_scores_gemma":[0.99683094,0.000107247106,0.00031808316,0.0020281388,0.0004031503,0.0003124126],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0015556483,0.00069623376,0.0007729791,0.0003052065,0.0001874904,0.00029360005,0.00066204614,0.00092000107,0.000010091855],"category_scores_gemma":[0.00054172066,0.00079605385,0.00044413796,0.00077325694,0.00006742933,0.000011697329,0.0011647023,0.00062738534,0.000036294823],"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":[0.00015052977,0.00010903559,0.0011095686,0.00025165448,0.00022111715,0.0000051893467,0.000008431095,0.1547776,0.843062,0.00009043373,0.0001988114,0.000015641659],"study_design_scores_gemma":[0.0020715902,0.00029059214,0.01195444,0.0010970741,0.0014958922,9.2062926e-8,0.000025583478,0.6733065,0.29992184,0.00079603394,0.0046715643,0.004368752],"about_ca_topic_score_codex":0.0000732551,"about_ca_topic_score_gemma":0.00010204915,"teacher_disagreement_score":0.5431402,"about_ca_system_score_codex":0.00028578725,"about_ca_system_score_gemma":0.0004986866,"threshold_uncertainty_score":0.999449},"labels":[],"label_agreement":null},{"id":"W4404155686","doi":"10.1101/2024.11.04.621989","title":"Efficient Finite-Difference Estimation of Second-Order Parametric Sensitivities for Stochastic Discrete Biochemical Systems","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Parametric statistics; Estimation; Mathematics; Applied mathematics; Order (exchange); Econometrics; Statistics; Economics","score_opus":0.00959429236467873,"score_gpt":0.22322060886036538,"score_spread":0.21362631649568664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404155686","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":[0.8877651,0.006053526,0.10373772,0.000025085688,0.0007564011,0.0008353828,0.00075223634,0.00007278946,0.0000017677498],"genre_scores_gemma":[0.99550277,0.00003245065,0.0035638176,0.000018405883,0.00040660467,0.0003140153,0.000011863529,0.00012728872,0.000022765535],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972408,0.00012383243,0.0006854368,0.0011267071,0.00034221436,0.00048100477],"domain_scores_gemma":[0.9974879,0.00013745848,0.00046825456,0.0011424884,0.00060070545,0.00016320907],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00049401756,0.0005720574,0.0007210164,0.0003840218,0.00008161159,0.00012866536,0.00034696137,0.00070216384,0.000004838906],"category_scores_gemma":[0.0005099928,0.0005884262,0.00034721027,0.0006180213,0.00019397867,0.000001990391,0.00060531666,0.00034777462,0.000008716393],"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":[0.00004048304,0.0000556172,0.000048137175,0.00130855,0.00042813362,0.0000028332065,0.0000054336697,0.35792655,0.63989466,0.00010465734,0.00018325164,0.0000017091596],"study_design_scores_gemma":[0.00031485906,0.000110017645,0.0010184462,0.0005256693,0.0005592715,5.561301e-8,0.000007941784,0.5422338,0.45442113,0.000005818028,0.00007347661,0.000729488],"about_ca_topic_score_codex":0.000013977797,"about_ca_topic_score_gemma":0.0000014655154,"teacher_disagreement_score":0.18547352,"about_ca_system_score_codex":0.00010157461,"about_ca_system_score_gemma":0.00050070096,"threshold_uncertainty_score":0.99965674},"labels":[],"label_agreement":null},{"id":"W4404334329","doi":"10.1038/s41559-024-02577-4","title":"How genotype-by-environment interactions on fitness emerge","year":2024,"lang":"en","type":"article","venue":"Nature Ecology & Evolution","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Natural Sciences and Engineering Research Council of Canada; Université Laval","funders":"","keywords":"Genotype; Evolutionary biology; Psychology; Biology; Genetics; Gene","score_opus":0.003138997667537579,"score_gpt":0.22103512191587857,"score_spread":0.21789612424834098,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404334329","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":[0.97486705,0.012512089,0.005681633,0.0040975553,0.0020296448,0.00019620491,0.000037795984,0.000055583612,0.00052245427],"genre_scores_gemma":[0.9895202,0.00021276294,0.000107197586,0.00018381016,0.0006158295,0.0000390904,0.00037608828,0.00002466786,0.008920366],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989596,0.000089782734,0.000120869634,0.000475646,0.00011454063,0.0002395504],"domain_scores_gemma":[0.99954265,0.000016421607,0.000044471264,0.00030731378,0.00003076501,0.000058390408],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000116253,0.0001620449,0.0001237835,0.00009060584,0.000118492586,0.000027535294,0.00012723073,0.00050420006,0.00012866777],"category_scores_gemma":[0.00003069279,0.00015483271,0.00014463834,0.00013230264,0.000061290775,0.000006574805,0.00006362254,0.00040335374,0.00010790119],"study_design_candidate":"not_applicable","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":[0.00008556335,0.00019129727,0.008412115,0.000028266759,0.0006520629,0.00001003487,0.000023472514,0.0038692872,0.5695544,0.0015688111,0.4126057,0.0029990058],"study_design_scores_gemma":[0.00026760093,0.00034794048,0.044768844,0.0000150338265,0.0002096341,0.00003052773,0.00004469041,0.002977646,0.030387936,0.0004238314,0.92016727,0.0003590749],"about_ca_topic_score_codex":0.0000025114184,"about_ca_topic_score_gemma":0.00007642293,"teacher_disagreement_score":0.53916645,"about_ca_system_score_codex":0.00016682385,"about_ca_system_score_gemma":0.00004257375,"threshold_uncertainty_score":0.6313895},"labels":[],"label_agreement":null},{"id":"W4404388835","doi":"10.1007/978-1-0716-4200-9_14","title":"A Computational Protocol for the Knowledge-Based Assessment and Capture of Pathologies","year":2024,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Protocol (science); Computer science; Medicine; Pathology","score_opus":0.029849059436040964,"score_gpt":0.44885965252595117,"score_spread":0.4190105930899102,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404388835","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0022472043,0.0018039132,0.9845214,0.0002410251,0.000057574758,0.011025278,0.000011125155,0.000009130032,0.00008333876],"genre_scores_gemma":[0.060883593,0.0000069934986,0.8935197,0.00012529995,0.000049866954,0.04530718,0.000046119363,0.000021213842,0.000040033883],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99864495,0.0005868591,0.0002325803,0.00033885182,0.00003958121,0.00015720788],"domain_scores_gemma":[0.9993403,0.00028322835,0.000054448756,0.00022893319,0.00007226196,0.000020820224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011221578,0.00013038852,0.00018841453,0.00008378167,0.000034492336,0.000012912034,0.00014922483,0.00017178926,0.0000051262614],"category_scores_gemma":[0.00010249784,0.00008930362,0.00012290034,0.0001632484,0.00021997355,9.1145205e-7,0.000094961135,0.00009035206,1.6486624e-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":[0.000077989,0.00007849488,0.0029122236,0.00026475135,0.00023473767,0.0000047028766,0.00005603097,0.025564387,0.91686434,0.007072749,0.00024157464,0.046628024],"study_design_scores_gemma":[0.0030860407,0.0014173789,0.007814686,0.00015471871,0.00029120018,0.000044500124,0.0002131315,0.42535326,0.3963145,0.039436433,0.12509091,0.0007832471],"about_ca_topic_score_codex":0.0000035934527,"about_ca_topic_score_gemma":0.000007584976,"teacher_disagreement_score":0.52054983,"about_ca_system_score_codex":0.000013841564,"about_ca_system_score_gemma":0.00016438666,"threshold_uncertainty_score":0.3641696},"labels":[],"label_agreement":null},{"id":"W4404505896","doi":"10.1002/asjc.3543","title":"On the input‐output decoupling of Boolean control networks by state feedback","year":2024,"lang":"en","type":"article","venue":"Asian Journal of Control","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Lakehead University","funders":"National Natural Science Foundation of China","keywords":"Decoupling (probability); Control theory (sociology); Control (management); State (computer science); Feedback control; Boolean network; Computer science; Control engineering; Boolean function; Engineering; Artificial intelligence; Algorithm","score_opus":0.003536456759164918,"score_gpt":0.20599744538845205,"score_spread":0.20246098862928713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404505896","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":[0.65371937,0.02535855,0.314303,0.0049955617,0.0006187387,0.00031588704,0.0000391394,0.000011753884,0.0006379904],"genre_scores_gemma":[0.99839425,0.0001921853,0.00004367157,0.00055576983,0.0004895619,0.000003192591,0.0000049128894,0.0000325723,0.00028390496],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99855727,0.00016347544,0.0005713478,0.00018482251,0.0002522527,0.00027086074],"domain_scores_gemma":[0.9989528,0.00010587291,0.00034817538,0.0002950673,0.00017426103,0.00012380084],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008373792,0.00018682779,0.0003657236,0.00007572168,0.000060851387,0.00006002404,0.000325477,0.00010738165,0.00003293721],"category_scores_gemma":[0.000078919446,0.0001254189,0.0004283777,0.00014157344,0.00009344208,0.00000660761,0.000019726525,0.00027264617,0.000005391933],"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":[0.002970205,0.00031048173,0.00682494,0.00009278998,0.011956026,0.00016908384,0.00040907468,0.48870236,0.17706822,0.0011575744,0.1766524,0.13368684],"study_design_scores_gemma":[0.035102792,0.012769698,0.013207289,0.002455123,0.007664669,0.0010481874,0.0019110012,0.54370046,0.118279725,0.009519629,0.25073254,0.0036088708],"about_ca_topic_score_codex":0.0000012741574,"about_ca_topic_score_gemma":0.000004425334,"teacher_disagreement_score":0.3446749,"about_ca_system_score_codex":0.000020153877,"about_ca_system_score_gemma":0.00010992571,"threshold_uncertainty_score":0.51144344},"labels":[],"label_agreement":null},{"id":"W4405075731","doi":"10.1007/s12064-024-00429-0","title":"A new symbiotic, holistic and gradualist model proposal for the concept of “living organism”","year":2024,"lang":"en","type":"article","venue":"Theory in Biosciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique; Collège Montmorency","funders":"","keywords":"Organism; Living systems; Living cell; Philosophy of biology; Context (archaeology); Pluralism (philosophy); Epistemology; Biology; Confusion; Ecology; Cognitive science; Psychology; Philosophy of science; Philosophy; Genetics","score_opus":0.015274599769298583,"score_gpt":0.27776910473053845,"score_spread":0.2624945049612399,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405075731","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":[0.87792486,0.013468519,0.10679155,0.0009255627,0.00029282854,0.00038056358,0.000030695785,0.000018723289,0.00016668875],"genre_scores_gemma":[0.9973364,0.00009768497,0.0018357623,0.000051865456,0.00008437618,0.0000051442858,0.0000021034273,0.000007830617,0.0005788659],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99931294,0.00005390882,0.00013790892,0.0002513525,0.000093563656,0.00015034548],"domain_scores_gemma":[0.99957293,0.00017187712,0.00003392045,0.0001621097,0.000022679802,0.000036485377],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060868217,0.00008531315,0.00010114018,0.000043583543,0.0000723683,0.000044772405,0.00021825181,0.000047239362,0.00000873902],"category_scores_gemma":[0.00017833684,0.000054613607,0.000046644473,0.00020654449,0.00043947416,0.0000046732325,0.00007986959,0.00003444605,4.0323218e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041155545,0.000033830354,0.00078335596,0.000081159626,0.00009881196,0.0000011836802,0.0019925828,0.0059801047,0.6859124,0.29593047,0.0014029087,0.0077420706],"study_design_scores_gemma":[0.00040558682,0.0007056103,0.0024455106,0.00043855648,0.00045128295,0.000045058754,0.0052994327,0.25893813,0.49628878,0.23325883,0.0009220361,0.00080118736],"about_ca_topic_score_codex":0.000013972894,"about_ca_topic_score_gemma":0.00006032851,"teacher_disagreement_score":0.25295803,"about_ca_system_score_codex":0.0000058344485,"about_ca_system_score_gemma":0.00021983043,"threshold_uncertainty_score":0.22270782},"labels":[],"label_agreement":null},{"id":"W4405494970","doi":"10.3390/mca29060120","title":"Efficient Finite-Difference Estimation of Second-Order Parametric Sensitivities for Stochastic Discrete Biochemical Systems","year":2024,"lang":"en","type":"article","venue":"Mathematical and Computational Applications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Parametric statistics; Sensitivity (control systems); Population; Biological system; Applied mathematics; Stochastic process; Computer science; Parametric model; Estimation theory; Stochastic modelling; Finite difference; Mathematics; Mathematical optimization; Statistical physics; Algorithm; Physics; Statistics; Engineering; Mathematical analysis; Biology","score_opus":0.009416838343819922,"score_gpt":0.252123546528501,"score_spread":0.24270670818468107,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405494970","genre_codex":"methods","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":[0.25780427,0.00070480537,0.7410132,0.000064652304,0.000011562552,0.00028979694,0.0000717134,0.000013313177,0.000026615226],"genre_scores_gemma":[0.9811099,0.0000020631649,0.01810133,0.000011788305,0.000054794065,0.00030548993,0.0002523081,0.000011064293,0.00015126113],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992846,0.000017227783,0.0002400976,0.0002366807,0.000121120574,0.00010022336],"domain_scores_gemma":[0.9993167,0.00036714578,0.000048664642,0.00011548721,0.0001060827,0.00004595552],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000106452084,0.000100484685,0.00014724235,0.00007142762,0.00006045112,0.000037475325,0.00005330928,0.000060064383,0.000005660182],"category_scores_gemma":[0.000052110252,0.000086825785,0.0000645255,0.00022467747,0.00010703957,0.0000013382338,0.000036793816,0.000034365665,0.0000055317473],"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":[0.000008028415,0.0000631663,0.0000028022978,0.00045312406,0.00009203703,1.0050435e-7,0.00003961688,0.9242501,0.0048887986,0.068719424,0.000119619915,0.001363129],"study_design_scores_gemma":[0.00008321006,0.000033693806,0.00009295932,0.000038075523,0.000063640415,0.000010740389,0.000038245482,0.9742604,0.0007621327,0.02444101,0.00008037103,0.000095543895],"about_ca_topic_score_codex":6.005655e-7,"about_ca_topic_score_gemma":2.2833217e-7,"teacher_disagreement_score":0.72330564,"about_ca_system_score_codex":0.000007717037,"about_ca_system_score_gemma":0.000039803188,"threshold_uncertainty_score":0.35406527},"labels":[],"label_agreement":null},{"id":"W4405838316","doi":"10.1109/tkde.2024.3523857","title":"A Survey of Change Point Detection in Dynamic Graphs","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Knowledge and Data Engineering","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Computer science; Point (geometry); Mathematics","score_opus":0.027271724777452266,"score_gpt":0.268731027236579,"score_spread":0.24145930245912672,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405838316","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":[0.60269797,0.009176524,0.387439,0.000008405288,0.00034828606,0.00010703909,0.0001849818,0.00002551324,0.000012260085],"genre_scores_gemma":[0.9988684,0.00087582093,0.00008086284,0.000002229778,0.000021200409,0.00001511483,0.00009328954,0.000016597614,0.000026470336],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994415,0.000024811434,0.00012932147,0.0002637473,0.000037528316,0.000103114384],"domain_scores_gemma":[0.99959844,0.000019015331,0.0000100917405,0.00032027124,0.000019342104,0.00003282151],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021598075,0.000093365685,0.000102172955,0.00019395031,0.000016918035,0.000010388619,0.00009407464,0.00007050147,0.0000036054273],"category_scores_gemma":[0.000003952342,0.00009707183,0.000033435917,0.00033019754,0.000013762533,0.000010812487,0.0000051711877,0.00008092994,0.0000024495566],"study_design_candidate":"simulation_or_modeling","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":[0.00008084299,0.00022374306,0.00040474557,0.000581591,0.0004888382,0.000008600151,0.00030748587,0.024232915,0.49247965,0.0000089488385,0.000105014034,0.4810776],"study_design_scores_gemma":[0.00030731113,0.00016230953,0.020658758,0.00016009314,0.000094488925,0.000015233544,0.00001954299,0.8721309,0.1046075,0.0000058824317,0.0015360597,0.00030195733],"about_ca_topic_score_codex":0.000076629054,"about_ca_topic_score_gemma":0.0029695516,"teacher_disagreement_score":0.84789795,"about_ca_system_score_codex":0.000011035855,"about_ca_system_score_gemma":0.0000145560025,"threshold_uncertainty_score":0.39584744},"labels":[],"label_agreement":null},{"id":"W4405859867","doi":"10.5376/cmb.2024.14.0006","title":"Modeling Biological Networks: A Systematic Review of Computational Approaches to Network Dynamics","year":2024,"lang":"en","type":"review","venue":"Computational Molecular Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Dynamics (music); Biological network; Network dynamics; Management science; Data science; Computational biology; Biology; Psychology; Engineering; Mathematics","score_opus":0.0670123840900099,"score_gpt":0.31599377298630604,"score_spread":0.24898138889629615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405859867","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000005217298,0.5596482,0.43897116,0.00003720642,0.00013462121,0.0010652441,0.00008996781,0.000021458713,0.000026918944],"genre_scores_gemma":[0.001544962,0.9676604,0.014455123,0.0005259242,0.00036813287,0.00046877353,0.014826357,0.00011989876,0.000030409541],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99510694,0.0010341246,0.0018495959,0.001202133,0.00027869202,0.00052851817],"domain_scores_gemma":[0.99820334,0.00012630047,0.000545113,0.0006667597,0.00026382649,0.0001946756],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00089029147,0.0007767984,0.0030717214,0.000254884,0.00008108195,0.000032034033,0.00077267137,0.0007374474,0.000008206006],"category_scores_gemma":[0.00020485953,0.000619597,0.0015080384,0.0009719334,0.0001498981,0.0000025116253,0.0006510539,0.00033233268,0.000042419008],"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":[0.0000050393214,0.00003395999,7.8827253e-7,0.25860935,0.0015385019,0.0000073143196,0.000001978372,0.7251853,5.6971663e-7,0.01052352,0.00029676818,0.0037969402],"study_design_scores_gemma":[0.00014165582,0.00032655738,2.2318716e-7,0.29738498,0.0061136256,0.00022782132,0.000006181158,0.6705831,1.8926936e-7,0.018527938,0.005511672,0.0011760605],"about_ca_topic_score_codex":0.0000021312947,"about_ca_topic_score_gemma":0.0000028924437,"teacher_disagreement_score":0.42451605,"about_ca_system_score_codex":0.00011278094,"about_ca_system_score_gemma":0.00041241205,"threshold_uncertainty_score":0.99962556},"labels":[],"label_agreement":null},{"id":"W4406164793","doi":"10.1101/2025.01.06.631612","title":"An algorithm for the transformation of the Petri net models of biological signaling networks into influence graphs","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Université Laval","funders":"","keywords":"Petri net; Transformation (genetics); Computer science; Net (polyhedron); Petri dish; Distributed computing; Mathematics; Biology; Genetics","score_opus":0.011398418380794332,"score_gpt":0.2274819868227852,"score_spread":0.21608356844199086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406164793","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":[0.687668,0.0031652413,0.3079271,0.00004357893,0.00024138516,0.0007728283,0.00015931958,0.000021389094,0.0000011439059],"genre_scores_gemma":[0.99097157,0.00083390594,0.0077341455,0.000088917266,0.0001663496,0.0001710376,0.000003617046,0.000029355277,0.000001099546],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99796844,0.00022836351,0.0006787886,0.00058223616,0.00022965255,0.00031250625],"domain_scores_gemma":[0.99723196,0.00007025105,0.0005629989,0.0013579436,0.0006984337,0.00007842623],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008574478,0.00036088988,0.0004613727,0.000109521476,0.00018586309,0.00003904204,0.0010908697,0.00063531904,0.0000019755514],"category_scores_gemma":[0.00006196898,0.00025325522,0.00045538144,0.0005333629,0.0002741355,0.0000127102185,0.00028408258,0.00029761577,1.1294456e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040458024,0.00006857316,0.0013752714,0.00014340381,0.00040852636,1.8061769e-7,0.000016072974,0.45024547,0.5472157,0.00036879408,0.00002577414,0.000091769536],"study_design_scores_gemma":[0.0003694988,0.0001284055,0.007027536,0.0001841007,0.00039619862,9.6509245e-9,0.000012182955,0.3615434,0.6295485,0.00005738482,0.00034296897,0.0003898282],"about_ca_topic_score_codex":0.00004823852,"about_ca_topic_score_gemma":0.000006160873,"teacher_disagreement_score":0.30330357,"about_ca_system_score_codex":0.000034138087,"about_ca_system_score_gemma":0.00033278103,"threshold_uncertainty_score":0.99999195},"labels":[],"label_agreement":null},{"id":"W4406457134","doi":"10.5376/cmb.2024.14.0016","title":"Dynamic Modeling in Systems Biology: From Pathway Analysis to Whole-Cell Simulations","year":2024,"lang":"en","type":"article","venue":"Computational Molecular Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Systems biology; Computational biology; Computer science; Biology","score_opus":0.010471654790795249,"score_gpt":0.2740645748759938,"score_spread":0.2635929200851985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406457134","genre_codex":"methods","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":[0.4722417,0.0042292583,0.52291983,0.00011858019,0.00012648608,0.00012257951,0.00018859595,0.000021785232,0.000031171003],"genre_scores_gemma":[0.98669964,0.000008610883,0.0060775676,0.00019394128,0.000085709464,0.000037364338,0.0067806784,0.000033986405,0.00008248392],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99797803,0.0002558099,0.00045833376,0.0008733317,0.0001056526,0.00032887017],"domain_scores_gemma":[0.9992574,0.000067734516,0.000055917113,0.00037513778,0.00012672493,0.000117091986],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018018049,0.0002502845,0.0003508984,0.0006203744,0.00006172588,0.000055904296,0.00026211666,0.00028285195,0.000017046053],"category_scores_gemma":[0.000036623365,0.00025928693,0.0002659714,0.0011261806,0.00005232983,0.0000035166438,0.00016048652,0.00012795886,0.00005102468],"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":[0.000009544656,0.000022779232,0.0017327946,0.000005843242,0.00054176396,0.000008043203,0.000022400201,0.7675566,0.2284772,0.0011468991,0.00001852454,0.00045758107],"study_design_scores_gemma":[0.0002007896,0.00007446583,0.00045318328,0.000012414499,0.00020424204,0.0000020674588,0.000021434227,0.9887172,0.00060023146,0.008438938,0.0009875268,0.0002875368],"about_ca_topic_score_codex":0.0001170516,"about_ca_topic_score_gemma":0.00014087834,"teacher_disagreement_score":0.51684225,"about_ca_system_score_codex":0.00006544511,"about_ca_system_score_gemma":0.00014167312,"threshold_uncertainty_score":0.99998593},"labels":[],"label_agreement":null},{"id":"W4406565654","doi":"10.1016/s9999-9994(10)20571-8","title":"10.1016/s9999-9994(10)20571-8","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Embryonic stem cell; Biology; Stem cell; Computational biology; Transcription factor; Genetics; Gene","score_opus":0.0033043084828096466,"score_gpt":0.16863122782535742,"score_spread":0.16532691934254776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406565654","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016448358,0.0005028096,0.0000060591233,0.00014560825,0.0000018030495,0.00013083564,0.00001347708,0.000038990107,0.98271203],"genre_scores_gemma":[0.0040960577,0.0000022675256,0.00016605388,0.00006112851,0.00040978994,0.000018177698,0.00014842508,0.000037493213,0.9950606],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988557,0.000056577028,0.00019408153,0.0004090996,0.00015273268,0.00033177197],"domain_scores_gemma":[0.999118,0.0000062159475,0.00003671104,0.00059607957,0.000060863218,0.00018213707],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00012816284,0.00019098958,0.00018632373,0.000049634866,0.00007863601,0.00002745451,0.00027852718,0.00014276823,0.9870532],"category_scores_gemma":[0.00001864819,0.00019472139,0.00015927108,0.00020214915,0.00004240506,0.0000026126465,0.00007882855,0.000057813213,0.9615711],"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":[0.00011414788,0.00005333953,9.248996e-7,0.0000043751324,0.00013325,0.0000038153257,0.0000039778106,0.0021018651,0.014040602,2.2016495e-7,0.6916206,0.29192287],"study_design_scores_gemma":[0.00019842637,0.0001690174,0.00003721106,0.0000047781577,0.00005087407,0.000008222378,6.9875165e-7,0.00022634046,0.007896324,0.0000028709608,0.9911607,0.00024454057],"about_ca_topic_score_codex":0.0000065113563,"about_ca_topic_score_gemma":7.526503e-7,"teacher_disagreement_score":0.29954007,"about_ca_system_score_codex":0.000016475118,"about_ca_system_score_gemma":0.000038207134,"threshold_uncertainty_score":0.7940508},"labels":[],"label_agreement":null},{"id":"W4406757174","doi":"10.1038/s41598-025-86332-0","title":"Determining interaction directionality in complex biochemical networks from stationary measurements","year":2025,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Snapshot (computer storage); Directionality; Computer science; Inference; Node (physics); Complex system; Complex network; Sampling (signal processing); Systems biology; Data mining; Biological system; Topology (electrical circuits); Statistical physics; Bioinformatics; Artificial intelligence; Physics; Mathematics; Biology","score_opus":0.0302513445242388,"score_gpt":0.29628855254799014,"score_spread":0.26603720802375136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406757174","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":[0.9940234,0.00033905747,0.00280933,0.000045271652,0.001979314,0.00010556329,0.000001847448,0.000013093761,0.0006831594],"genre_scores_gemma":[0.9975437,0.000002838444,0.00067137124,0.00005863475,0.00009924187,0.000018586567,0.0010217695,0.000006623347,0.0005772276],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9984503,0.00008658054,0.00040680927,0.0006581983,0.00022288355,0.00017527398],"domain_scores_gemma":[0.9991812,0.000012898542,0.00015325673,0.0004757003,0.00013079357,0.000046111392],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064588175,0.000107331296,0.0001293801,0.00011629114,0.00012895033,0.00007175302,0.00008955356,0.00009101082,0.00005375142],"category_scores_gemma":[0.00009985959,0.00011555893,0.00008705453,0.00038743878,0.00009395235,0.0000071302843,0.00009792005,0.00007000897,0.0000019475146],"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":[0.000021320708,0.000070715,0.4182286,0.000004593686,0.000079050726,0.0000122807005,0.00001536701,0.009349739,0.54676366,0.0000016087891,0.02259063,0.002862484],"study_design_scores_gemma":[0.0004070707,0.000021772858,0.6385873,0.00008360068,0.00008199384,0.000028343295,0.00010532905,0.015221616,0.29038447,0.0019469837,0.052733462,0.00039807314],"about_ca_topic_score_codex":0.000045123717,"about_ca_topic_score_gemma":0.00016975297,"teacher_disagreement_score":0.25637916,"about_ca_system_score_codex":0.00006620663,"about_ca_system_score_gemma":0.00009658212,"threshold_uncertainty_score":0.47123563},"labels":[],"label_agreement":null},{"id":"W4406878149","doi":"10.1101/2025.01.24.634773","title":"scGRIP: a graph-based explainable AI framework for single-cell multi-omics Gene Regulatory Inference with Prior Knowledge","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"McGill University","funders":"","keywords":"Computational biology; Gene regulatory network; Graph; Computer science; Cell; Gene; Biology; Gene expression; Genetics; Theoretical computer science","score_opus":0.014389301411701534,"score_gpt":0.23883817606753158,"score_spread":0.22444887465583005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406878149","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":[0.5298987,0.009225599,0.45730287,0.00010097568,0.00074770104,0.0019810002,0.0004950407,0.00023613317,0.0000119892275],"genre_scores_gemma":[0.8510177,0.00022623243,0.14666955,0.0003625697,0.00055813463,0.0008695969,0.000014356922,0.00020712714,0.000074722404],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9953694,0.00023022888,0.00079653546,0.0021922158,0.00035223583,0.0010594361],"domain_scores_gemma":[0.9941975,0.00011369172,0.0007050714,0.0030642452,0.0015016228,0.00041785403],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00066094095,0.0011283217,0.0010163252,0.0004772713,0.0003907619,0.00024084399,0.0011442333,0.0014401833,0.000009636698],"category_scores_gemma":[0.00027488006,0.0012024655,0.0005717066,0.0008419286,0.00031706507,0.000015228945,0.00070921343,0.00078430376,0.000008947664],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003074581,0.00088486634,0.0051195,0.0011899265,0.0006470452,0.000014608334,0.000010417967,0.010049619,0.9809781,0.00030352297,0.0004795446,0.000015399024],"study_design_scores_gemma":[0.0016989984,0.00026074742,0.0027439878,0.00069594296,0.0006662204,2.7967584e-8,0.0000048512293,0.0039177793,0.9821038,0.000011428637,0.006378411,0.0015178032],"about_ca_topic_score_codex":0.000016452575,"about_ca_topic_score_gemma":0.000019713101,"teacher_disagreement_score":0.321119,"about_ca_system_score_codex":0.0002873745,"about_ca_system_score_gemma":0.0025891752,"threshold_uncertainty_score":0.9998562},"labels":[],"label_agreement":null},{"id":"W4407069166","doi":"10.1007/978-981-97-9194-1","title":"Mathematical Analysis and Applications in Biological Phenomena through Modelling","year":2025,"lang":"en","type":"book","venue":"Springer proceedings in mathematics & statistics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Science and Engineering Research Board; Szegedi Tudományegyetem; Department of Science and Technology, Ministry of Science and Technology, India; National Board for Higher Mathematics; Jadavpur University; Vysoká Škola Chemicko-technologická v Praze; University of Ottawa; Washington State University","keywords":"Computer science; Management science; Engineering","score_opus":0.01723285841341383,"score_gpt":0.25943043717100756,"score_spread":0.24219757875759373,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407069166","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0059241946,0.0019102065,0.92426866,0.000019690024,0.000028661556,0.0010688135,0.00018507935,0.000035652243,0.06655903],"genre_scores_gemma":[0.019070437,0.006750948,0.8480846,0.0001084401,0.00056393596,0.0006582386,0.0012242848,0.00021079007,0.12332829],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9973229,0.000017071392,0.0010205496,0.00088467955,0.00029338562,0.00046137525],"domain_scores_gemma":[0.9987813,0.00013136186,0.00040467866,0.00041030708,0.0001823495,0.00008996857],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005110595,0.0005351648,0.0010664875,0.0005063971,0.00007646616,0.00008410001,0.00040443862,0.0006028716,0.000026085741],"category_scores_gemma":[0.00011557562,0.0005222758,0.00017728728,0.0005367641,0.00021942385,0.000006939438,0.00039984824,0.00042994125,0.0000065781473],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006310592,0.0012067795,0.009403846,0.007089883,0.0043876716,0.00002804876,0.0029923564,0.015414693,0.0009521899,0.9525022,0.0031705084,0.0027887318],"study_design_scores_gemma":[0.0006221564,0.00010754306,0.00025261744,0.0005440123,0.002280396,0.0000068123913,0.00050430174,0.08207252,0.00032803608,0.8860413,0.025755804,0.0014845144],"about_ca_topic_score_codex":0.0000057952366,"about_ca_topic_score_gemma":0.000040205494,"teacher_disagreement_score":0.076184034,"about_ca_system_score_codex":0.00014073522,"about_ca_system_score_gemma":0.00015558029,"threshold_uncertainty_score":0.9997229},"labels":[],"label_agreement":null},{"id":"W4407505903","doi":"10.1371/journal.pcbi.1012817","title":"Bimodality in E. coli gene expression: Sources and robustness to genome-wide stresses","year":2025,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Opetushallitus; Suomen Kulttuurirahasto; Sigrid Juséliuksen Säätiö; Jane ja Aatos Erkon Säätiö; Suomalainen Tiedeakatemia","keywords":"Bimodality; Biology; Gene; Gene expression; Transcription (linguistics); Genetics; Robustness (evolution); Phenotype; Promoter; Transcriptome; Regulation of gene expression; Computational biology; Genome; Physics","score_opus":0.010335491251024963,"score_gpt":0.24831464024446834,"score_spread":0.23797914899344338,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407505903","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":[0.9770981,0.0013979003,0.02057041,0.00060482044,0.000045539517,0.0001572422,0.000023138995,0.000011050775,0.00009176525],"genre_scores_gemma":[0.99304116,0.000048064874,0.005891784,0.0004914005,0.00008163844,0.00003921077,0.00030547316,0.000008026453,0.00009327045],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9989248,0.00013887792,0.0002351344,0.000439161,0.00006480478,0.00019723663],"domain_scores_gemma":[0.99952334,0.00007924054,0.00005327682,0.00017663933,0.00010030529,0.00006722512],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000112552705,0.00013699298,0.00020830538,0.00014797517,0.00007636543,0.000016076603,0.00015615077,0.00013366368,0.000016023818],"category_scores_gemma":[0.000080721926,0.00013268909,0.000041976466,0.00023655157,0.00009469683,0.000002377035,0.00023026002,0.00005568834,0.000002642099],"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":[0.00008946905,0.00010938473,0.32942337,0.000029389732,0.00014150693,0.0000024959206,0.000031290892,0.44429037,0.22483619,0.00022183184,0.00031750518,0.00050720107],"study_design_scores_gemma":[0.001196072,0.00021944042,0.81175023,0.00005910768,0.000068255766,0.000005747133,0.00012105487,0.012881406,0.16360627,0.0039083916,0.0056207883,0.000563237],"about_ca_topic_score_codex":0.000010431338,"about_ca_topic_score_gemma":0.000044725108,"teacher_disagreement_score":0.48232684,"about_ca_system_score_codex":0.000017803313,"about_ca_system_score_gemma":0.00009118208,"threshold_uncertainty_score":0.5410904},"labels":[],"label_agreement":null},{"id":"W4407603264","doi":"10.1093/bioadv/vbag179","title":"CycleMix: Gaussian Mixture Modeling of the Cell Cycle","year":2025,"lang":"en","type":"preprint","venue":"Bioinformatics Advances","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Western University","funders":"","keywords":"Gaussian; Mixture model; Computer science; Statistical physics; Artificial intelligence; Physics; Chemistry; Computational chemistry","score_opus":0.005661072395691977,"score_gpt":0.23241871094834993,"score_spread":0.22675763855265796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407603264","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":[0.6975938,0.068839885,0.14393021,0.00062879064,0.003610606,0.0021667327,0.00095342245,0.00009715065,0.08217941],"genre_scores_gemma":[0.9793973,0.0025747123,0.016527321,0.00014814436,0.00019826023,0.000026041898,0.00020083362,0.000019375515,0.00090799807],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985814,0.000044044653,0.0006096629,0.00026288998,0.00025445534,0.00024755805],"domain_scores_gemma":[0.99818355,0.00000922423,0.0005032742,0.0011154042,0.0001334335,0.000055126042],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016764755,0.00029555126,0.0003452105,0.0000707572,0.00010206892,0.000028869807,0.00080718036,0.00036940785,0.000005789315],"category_scores_gemma":[0.00003254759,0.0002182959,0.00040499697,0.00016399665,0.0000872016,0.000006061849,0.0011511191,0.00025575553,0.0000018314821],"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":[0.000016576829,0.00003882184,0.00060880365,0.0010327874,0.00015479814,1.7479157e-7,0.00015782817,0.99119794,0.001967815,0.000050452032,0.0008430027,0.0039310115],"study_design_scores_gemma":[0.0003270959,0.00003920829,0.00006867102,0.0003770982,0.00029216116,0.0000021762826,0.00036867143,0.8994758,0.07535574,0.0016405723,0.02149513,0.0005576462],"about_ca_topic_score_codex":0.000008608641,"about_ca_topic_score_gemma":0.000033220524,"teacher_disagreement_score":0.28180352,"about_ca_system_score_codex":0.00002159362,"about_ca_system_score_gemma":0.00023621373,"threshold_uncertainty_score":0.8901848},"labels":[],"label_agreement":null},{"id":"W4407778147","doi":"10.1016/j.biosystems.2025.105415","title":"An algorithm for the transformation of the Petri net models of biological signaling networks into influence graphs","year":2025,"lang":"en","type":"article","venue":"Biosystems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Petri net; Transformation (genetics); Computer science; Stochastic Petri net; Algorithm; Theoretical computer science; Biology","score_opus":0.011015649460473516,"score_gpt":0.24457986872057794,"score_spread":0.23356421926010443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407778147","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":[0.72857314,0.0026610172,0.26817897,0.00004067664,0.00012321224,0.0003818467,0.000014781108,0.000005009585,0.00002134617],"genre_scores_gemma":[0.99910367,0.00013595194,0.000565933,0.000042738608,0.000065089844,0.000036443344,0.000032025146,0.0000057326506,0.000012427565],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999133,0.00011483472,0.00035563615,0.00017175866,0.00009378752,0.00013098255],"domain_scores_gemma":[0.9992205,0.00003658648,0.00016638912,0.00039532664,0.00015922358,0.00002199543],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004514875,0.00010371362,0.00017546646,0.000037547565,0.000105213214,0.000010945911,0.0003695486,0.00015653331,5.464239e-7],"category_scores_gemma":[0.000013739658,0.0000588032,0.00020372488,0.00030381684,0.00010099098,0.000005264941,0.000033310902,0.000043012045,5.4517333e-8],"study_design_candidate":"simulation_or_modeling","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":[0.000054113225,0.000053001277,0.002499022,0.00009397231,0.0003306128,4.8424244e-8,0.00016685143,0.4616738,0.5153155,0.0015391639,0.00012407864,0.01814988],"study_design_scores_gemma":[0.00033918032,0.00016159793,0.0013148864,0.00006576016,0.00011442003,0.0000012727876,0.00031433124,0.75425774,0.24172078,0.00057396747,0.0010190732,0.0001169981],"about_ca_topic_score_codex":0.00006710908,"about_ca_topic_score_gemma":0.000030160172,"teacher_disagreement_score":0.29258394,"about_ca_system_score_codex":0.000007721966,"about_ca_system_score_gemma":0.00004166883,"threshold_uncertainty_score":0.2397925},"labels":[],"label_agreement":null},{"id":"W4407934538","doi":"10.1016/j.brs.2024.12.450","title":"TMS-Induced Changes in Global Brain Dynamics: Insights from EEG Microstate Analysis","year":2025,"lang":"en","type":"article","venue":"Brain stimulation","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Innovation Council; Canada Research Chairs; University of Toronto; Centre for Addiction and Mental Health; Simon Fraser University","funders":"","keywords":"Ministate; Electroencephalography; Neuroscience; Dynamics (music); Psychology","score_opus":0.006222253761671314,"score_gpt":0.2613738715997461,"score_spread":0.25515161783807483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407934538","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":[0.98455274,0.00052921206,0.012658882,0.0015434644,0.00009402926,0.00018292035,0.000052808875,0.000020375748,0.000365562],"genre_scores_gemma":[0.99590963,0.00001538338,0.00044739243,0.00083020865,0.00007732618,0.00001419139,0.0021378377,0.00001162819,0.00055642193],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9986004,0.00018419133,0.00029438714,0.0005544943,0.000138051,0.00022847719],"domain_scores_gemma":[0.9992208,0.000058664675,0.00011581046,0.00046824862,0.000081344726,0.00005516582],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015286646,0.00020076921,0.0002896408,0.00026650584,0.000073262236,0.000042515432,0.00017670749,0.00023356856,0.000019652623],"category_scores_gemma":[0.0001105405,0.00021774025,0.00016598175,0.0014070062,0.000033879638,0.00000586806,0.0001101709,0.00006589399,0.0000065422496],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001691651,0.00010103039,0.23337443,0.000014133603,0.0014611942,0.0000074036707,0.00011567381,0.13936728,0.6087497,0.0003540296,0.0017018411,0.014584123],"study_design_scores_gemma":[0.0009462822,0.000051323994,0.78925306,0.000019336254,0.00033211126,3.1280038e-7,0.000078382676,0.1987626,0.006958055,0.0013608757,0.0019445533,0.00029312092],"about_ca_topic_score_codex":0.0004972024,"about_ca_topic_score_gemma":0.030183028,"teacher_disagreement_score":0.6017916,"about_ca_system_score_codex":0.00014811778,"about_ca_system_score_gemma":0.00006791163,"threshold_uncertainty_score":0.9875136},"labels":[],"label_agreement":null},{"id":"W4408083017","doi":"10.1101/2025.02.25.640181","title":"geneRNIB: a living benchmark for gene regulatory network inference","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada); Mila - Quebec Artificial Intelligence Institute; Université de Montréal","funders":"","keywords":"Inference; Benchmark (surveying); Gene regulatory network; Computational biology; Gene; Computer science; Biology; Genetics; Artificial intelligence; Gene expression; Geography; Cartography","score_opus":0.00980508437019819,"score_gpt":0.22617011656980313,"score_spread":0.21636503219960493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408083017","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":[0.92848885,0.014547205,0.05247686,0.00009280197,0.002147543,0.0014902005,0.0004803379,0.00024059281,0.000035582616],"genre_scores_gemma":[0.96838075,0.0010131072,0.025835363,0.00040729533,0.0033506833,0.00069594226,0.000010066636,0.00016801861,0.00013880209],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9953829,0.00025981458,0.0008597209,0.0020012343,0.00039834654,0.0010979495],"domain_scores_gemma":[0.99513096,0.000113801725,0.00065735827,0.002904531,0.0008336197,0.00035974957],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0011358,0.00093939254,0.0009138078,0.0002402946,0.00036494175,0.00018998291,0.0011836626,0.0013432681,0.00003145527],"category_scores_gemma":[0.00046310519,0.0011100542,0.0006811005,0.0005431904,0.0001732952,0.000010234381,0.0016132813,0.0005109862,0.000010673803],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007381147,0.00014447002,0.017971085,0.0005043983,0.0013677435,0.000008945559,0.0000058069263,0.027729308,0.94209,0.00037846985,0.009703218,0.000022796927],"study_design_scores_gemma":[0.000969676,0.00024230193,0.11739763,0.0015377133,0.0015519538,5.3342255e-8,0.000003745181,0.0086923735,0.8104227,0.0000261946,0.05558132,0.0035743166],"about_ca_topic_score_codex":0.00002010943,"about_ca_topic_score_gemma":0.000014547533,"teacher_disagreement_score":0.13166723,"about_ca_system_score_codex":0.00018776167,"about_ca_system_score_gemma":0.0013601586,"threshold_uncertainty_score":0.9999532},"labels":[],"label_agreement":null},{"id":"W4408127335","doi":"10.1038/s44385-025-00015-z","title":"Subcellular systems follow Onsager reciprocity","year":2025,"lang":"en","type":"article","venue":"npj Biomedical Innovations.","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Fisheries and Oceans Canada","keywords":"Reciprocity (cultural anthropology); Statistical physics; Environmental science; Physics; Psychology; Social psychology","score_opus":0.010615242114696949,"score_gpt":0.2551190097652438,"score_spread":0.24450376765054688,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408127335","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":[0.88098985,0.0027927791,0.10596528,0.0027189597,0.0012799158,0.00037671896,0.000025935984,0.00007942709,0.0057711173],"genre_scores_gemma":[0.9882044,0.00004975947,0.0009947649,0.0007303139,0.0003414443,0.000058258218,0.00059427123,0.000014962072,0.009011821],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.998571,0.00007665067,0.00042764255,0.0004027551,0.00025428418,0.00026771764],"domain_scores_gemma":[0.99900526,0.000016889764,0.00009415932,0.0005335676,0.00027092794,0.00007922381],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048197387,0.00015718634,0.00020186233,0.00023945146,0.00015505464,0.00004076738,0.0002653659,0.00031153674,0.00005656593],"category_scores_gemma":[0.00019863572,0.00014800318,0.000107827196,0.0016910619,0.00019212149,0.0000033544848,0.00012953799,0.00013448195,0.0000328698],"study_design_candidate":"not_applicable","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":[0.000050170765,0.00030918664,0.012371659,0.00009572948,0.0007406094,0.00001057644,0.000016968444,0.00013970246,0.63701636,0.012098057,0.32497108,0.01217991],"study_design_scores_gemma":[0.00068307,0.00007959271,0.0034639894,0.000043833228,0.00009010596,0.0000060143902,0.000059393373,0.0014804256,0.027453076,0.00044931498,0.96590745,0.00028372626],"about_ca_topic_score_codex":0.000021092788,"about_ca_topic_score_gemma":0.0000067311807,"teacher_disagreement_score":0.6409364,"about_ca_system_score_codex":0.000039048467,"about_ca_system_score_gemma":0.00020751536,"threshold_uncertainty_score":0.60353947},"labels":[],"label_agreement":null},{"id":"W4408237664","doi":"10.23977/acss.2025.090108","title":"Inference of Gene Regulatory Networks Based on Heterogeneous Graph Neural Networks","year":2025,"lang":"en","type":"article","venue":"Advances in Computer Signals and Systems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Inference; Gene regulatory network; Computer science; Artificial neural network; Graph; Computational biology; Gene; Artificial intelligence; Biology; Genetics; Theoretical computer science; Gene expression","score_opus":0.0068037630290342585,"score_gpt":0.24213221886784037,"score_spread":0.2353284558388061,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408237664","genre_codex":"methods","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":[0.27915457,0.04064821,0.67933035,0.000012045108,0.00057047914,0.0002067541,0.0000031424743,0.000011205566,0.0000632598],"genre_scores_gemma":[0.9981394,0.0007776005,0.0005345183,0.00021244468,0.00024681538,0.00002504551,0.00002852022,0.000013799971,0.000021844546],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99844754,0.00020982075,0.00046429934,0.000472221,0.00013568896,0.000270455],"domain_scores_gemma":[0.9991222,0.00008165795,0.00017534738,0.00047677368,0.00008116868,0.00006287676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028207822,0.00022270149,0.00039491637,0.00013948734,0.000057585745,0.00003101488,0.00022397583,0.00016436688,0.0000014503021],"category_scores_gemma":[0.0000065407194,0.0002069027,0.000120998695,0.00029036272,0.00010127669,0.0000073188953,0.000078201505,0.00009773803,1.2494668e-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":[0.000053833897,0.000035902125,0.011839166,0.00004085976,0.0000460557,0.000004767186,0.0000042175707,0.97054493,0.0011546509,0.000058897742,0.000061852705,0.016154869],"study_design_scores_gemma":[0.0003982513,0.0002220581,0.0019446915,0.00015544708,0.000021203374,0.0000041606095,0.000004054084,0.994618,0.0020335575,0.000038024064,0.00037519302,0.00018535949],"about_ca_topic_score_codex":0.000009211287,"about_ca_topic_score_gemma":0.000021919377,"teacher_disagreement_score":0.71898484,"about_ca_system_score_codex":0.000011260841,"about_ca_system_score_gemma":0.000022208822,"threshold_uncertainty_score":0.84372467},"labels":[],"label_agreement":null},{"id":"W4408614039","doi":"10.1021/acs.jctc.4c01780","title":"Comparative Analysis of Reinforcement Learning Algorithms for Finding Reaction Pathways: Insights from a Large Benchmark Data Set","year":2025,"lang":"en","type":"article","venue":"Journal of Chemical Theory and Computation","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Toronto Metropolitan University","funders":"Japan Society for the Promotion of Science","keywords":"Benchmark (surveying); Reinforcement learning; Computer science; Set (abstract data type); Data set; Machine learning; Artificial intelligence; Algorithm","score_opus":0.0312515664154304,"score_gpt":0.3167783314802967,"score_spread":0.2855267650648663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408614039","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":[0.6910083,0.00055508607,0.3082984,0.000008781798,0.00003066437,0.000040316343,0.000011715502,0.0000011760787,0.00004553273],"genre_scores_gemma":[0.99698144,0.000050243892,0.0013474291,0.000027459537,0.00008065402,0.000001407949,0.0014945841,0.000002574113,0.000014209641],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991857,0.00012646503,0.0003620216,0.00015547077,0.00009974847,0.00007062764],"domain_scores_gemma":[0.99910986,0.00017116591,0.00040307574,0.00011767475,0.00016629454,0.0000319319],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048422653,0.00007910795,0.00028941044,0.00013224587,0.000048878155,0.000012901739,0.000112821624,0.00007374758,0.000002748256],"category_scores_gemma":[0.00008747166,0.00006984523,0.00012347312,0.00023515009,0.000029851397,0.0000126558125,0.00007820585,0.00007868681,5.2751414e-8],"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":[0.0007212404,0.00006340825,0.00045944587,0.000022086972,0.0040652216,6.2710785e-7,0.0004904562,0.05328431,0.9359681,0.0011127497,0.00017491021,0.0036374214],"study_design_scores_gemma":[0.0017022069,0.00028607313,0.0019706208,0.00010514865,0.0038232242,0.0000028123457,0.0016776688,0.517437,0.4564492,0.014259956,0.0020720153,0.0002140528],"about_ca_topic_score_codex":0.0000013643507,"about_ca_topic_score_gemma":0.00000102485,"teacher_disagreement_score":0.47951892,"about_ca_system_score_codex":0.0000148833,"about_ca_system_score_gemma":0.00003548063,"threshold_uncertainty_score":0.28482056},"labels":[],"label_agreement":null},{"id":"W4408780429","doi":"10.1073/pnas.2504067122","title":"Striking the balance: Complexity, simplicity, and credibility in mathematical biology","year":2025,"lang":"en","type":"letter","venue":"Proceedings of the National Academy of Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Innovation Cluster (Canada)","funders":"","keywords":"Simplicity; Balance (ability); Credibility; Computer science; Biology; Epistemology; Neuroscience; Philosophy","score_opus":0.0488534268142625,"score_gpt":0.3259426137812051,"score_spread":0.27708918696694257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408780429","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":[0.65352,0.0007407934,0.000008749191,0.34152573,0.000026206948,0.00039147335,0.00006758673,0.000004889917,0.0037145836],"genre_scores_gemma":[0.9724418,0.000075423035,0.00042433932,0.02652396,0.00036850217,0.0000117048185,0.0000029044497,0.000004088919,0.00014728513],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99853325,0.00002989829,0.00038190407,0.00038938675,0.00048042025,0.00018512986],"domain_scores_gemma":[0.9992915,0.00012559221,0.00038277172,0.000024416668,0.00016238003,0.0000133865215],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015118299,0.00013847926,0.0002685226,0.00011157294,0.00012651694,0.000020220543,0.0010345561,0.0003899755,0.0000059998083],"category_scores_gemma":[0.00047621081,0.00008156232,0.0001093074,0.0004665421,0.0019027309,0.0000065949616,0.0006190737,0.00043797874,8.781015e-8],"study_design_candidate":"theoretical_or_conceptual","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":[0.000046128145,0.000133795,0.12985401,0.0015009419,0.00039181023,5.0844843e-8,0.00014551391,0.00035738983,0.3184509,0.055712078,0.49256507,0.00084230024],"study_design_scores_gemma":[0.00042714336,0.00011450662,0.082568206,0.00040157905,0.00014083278,0.000025431147,0.0001135714,0.005609128,0.07905241,0.78190637,0.049203765,0.00043707903],"about_ca_topic_score_codex":0.000004335748,"about_ca_topic_score_gemma":3.4928422e-7,"teacher_disagreement_score":0.72619426,"about_ca_system_score_codex":0.000019177913,"about_ca_system_score_gemma":0.00005438625,"threshold_uncertainty_score":0.7010691},"labels":[],"label_agreement":null},{"id":"W4408836921","doi":"10.1101/2025.03.23.644840","title":"The temperature dependence of binding entropy is a selective pressure in protein evolution","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"","keywords":"Enthalpy; SUPERFAMILY; Entropy (arrow of time); Transcription factor; Chemistry; Thermodynamics; Computational biology; Biology; Economics; Gene; Biochemistry; Physics","score_opus":0.004548882851761937,"score_gpt":0.20592653260317337,"score_spread":0.20137764975141142,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408836921","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":[0.98921996,0.008913631,0.00035361337,0.00012146001,0.00023394686,0.0009425584,0.00017855632,0.000029788962,0.000006486433],"genre_scores_gemma":[0.9983116,0.00036877257,0.0006744789,0.000028734941,0.00021101117,0.00026723175,9.656194e-7,0.00004015318,0.000097077274],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9974655,0.00029423245,0.00050548266,0.00094729237,0.00032984998,0.00045768046],"domain_scores_gemma":[0.99762404,0.000021922437,0.00044601085,0.0012590197,0.0005619711,0.00008705164],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006132855,0.00041924478,0.000431373,0.00020091765,0.00017281248,0.00007869885,0.00070085586,0.0008043244,0.000004837717],"category_scores_gemma":[0.00021880386,0.0003807816,0.00022526289,0.0007248179,0.00012891294,0.0000072437533,0.00058721984,0.00062298344,0.000002612182],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007150207,0.000057067733,0.0153717995,0.00020471361,0.00043653703,0.0000030272215,0.000006488204,0.0010026984,0.98228985,0.00018444059,0.0003708286,0.000001027143],"study_design_scores_gemma":[0.00029393134,0.00004781327,0.025048068,0.00038083433,0.0001677491,9.766297e-9,0.0000053367676,0.00047925313,0.97131807,0.0000053299536,0.0018776872,0.00037590036],"about_ca_topic_score_codex":0.00005839704,"about_ca_topic_score_gemma":0.0000339287,"teacher_disagreement_score":0.010971783,"about_ca_system_score_codex":0.00015084456,"about_ca_system_score_gemma":0.0010372616,"threshold_uncertainty_score":0.9998644},"labels":[],"label_agreement":null},{"id":"W4408848626","doi":"10.1016/j.ces.2025.121574","title":"Solving the chemical master equation for stochastic biochemical systems: A variational autoencoder approach with effective reactions","year":2025,"lang":"en","type":"article","venue":"Chemical Engineering Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Queen's University","funders":"Scientific and Innovative Action Plan of Shanghai; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Master equation; Autoencoder; Chemical reaction; Applied mathematics; Computer science; Statistical physics; Mathematics; Chemistry; Physics; Artificial intelligence; Artificial neural network","score_opus":0.007352636473125509,"score_gpt":0.21261946014458158,"score_spread":0.20526682367145607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408848626","genre_codex":"methods","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":[0.11028063,0.0001645216,0.8888758,0.00008167928,0.000095722666,0.00038154892,0.0000038589,0.000027550623,0.00008869801],"genre_scores_gemma":[0.9795165,6.0360463e-7,0.019770317,0.00003202433,0.00018000808,0.00035941318,0.000041139083,0.000013234812,0.0000867586],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99879664,0.000010901338,0.00018549997,0.00047378486,0.0002323222,0.0003008204],"domain_scores_gemma":[0.9992651,0.000105959625,0.00005576649,0.00031660602,0.000185135,0.00007145906],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038045325,0.00015593375,0.00013738635,0.0000735456,0.00012457144,0.000070817194,0.00032488554,0.00010610169,9.2504536e-7],"category_scores_gemma":[0.00045102055,0.00011524865,0.000072335606,0.00055423495,0.00022962218,0.000010907822,0.00010096932,0.000118390424,7.845511e-7],"study_design_candidate":"simulation_or_modeling","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":[0.000018100098,0.000020360216,0.000012847313,0.000034239136,0.000043879438,4.360956e-8,0.000014364403,0.31254306,0.6862206,0.0009453198,0.00009695738,0.00005023087],"study_design_scores_gemma":[0.00023437146,0.000016680819,0.0000954042,0.000039403818,0.000057479534,0.000009577676,0.000019340676,0.8050724,0.19413519,0.00003207348,0.00015149896,0.00013656962],"about_ca_topic_score_codex":0.0000020554914,"about_ca_topic_score_gemma":3.6083488e-8,"teacher_disagreement_score":0.8692359,"about_ca_system_score_codex":0.00010567553,"about_ca_system_score_gemma":0.0001536322,"threshold_uncertainty_score":0.46997035},"labels":[],"label_agreement":null},{"id":"W4409101111","doi":"10.1101/2025.04.02.646789","title":"Principles underlying implementation of <i>nearly</i> -homeostatic biological networks","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Homeostasis; Biology; Cell biology","score_opus":0.025840110442565786,"score_gpt":0.2682728836472393,"score_spread":0.2424327732046735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409101111","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":[0.9750743,0.0042549088,0.019191723,0.000061653074,0.00048831635,0.0006481246,0.00018729502,0.000079431265,0.000014279543],"genre_scores_gemma":[0.993561,0.0013747775,0.0044247108,0.00013871468,0.00028060598,0.00013908399,0.000009509541,0.000059613107,0.00001196886],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9969474,0.00027196505,0.00086875533,0.0010823141,0.00027570094,0.00055383897],"domain_scores_gemma":[0.9973028,0.000039356055,0.0007122137,0.001346073,0.0004305713,0.00016899602],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006543512,0.0005437097,0.0006655082,0.00021214703,0.00013443845,0.000077918354,0.00063261506,0.0007406329,0.00003395995],"category_scores_gemma":[0.000079310834,0.00057125906,0.00035998676,0.00046836174,0.00017066479,0.0000068649024,0.00094358594,0.00037682033,0.000004446224],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006052121,0.00013776809,0.084563866,0.000417347,0.0011990636,0.000009299752,0.000008351475,0.018369079,0.8941798,0.0005789679,0.00044405714,0.000031854226],"study_design_scores_gemma":[0.0012443772,0.00032105268,0.26823795,0.0004333436,0.000718852,3.281186e-8,0.000040672177,0.0041772868,0.71283233,0.00000627915,0.010335799,0.0016520257],"about_ca_topic_score_codex":0.000052957177,"about_ca_topic_score_gemma":0.000017282899,"teacher_disagreement_score":0.18367408,"about_ca_system_score_codex":0.00009626077,"about_ca_system_score_gemma":0.0006386956,"threshold_uncertainty_score":0.9996739},"labels":[],"label_agreement":null},{"id":"W4409665917","doi":"10.1038/s41467-025-58996-9","title":"Engineering coupled consortia-based biosensors for diagnostic","year":2025,"lang":"en","type":"article","venue":"Nature Communications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Canadian Institute for Advanced Research","funders":"Technion-Israel Institute of Technology; European Commission; Canadian Institute for Advanced Research","keywords":"Biosensor; Computer science; Computational biology; Nanotechnology; Biology; Materials science","score_opus":0.007346231875330661,"score_gpt":0.2715238895781313,"score_spread":0.2641776577028006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409665917","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":[0.69164973,0.119415686,0.15610568,0.02580655,0.0011654146,0.002825469,0.00022698674,0.00030906824,0.0024953953],"genre_scores_gemma":[0.98751765,0.0002700681,0.010756952,0.00055042875,0.000042765474,0.00013497443,0.00044917248,0.000014029095,0.00026398446],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994387,0.000037125486,0.00015552892,0.00018027553,0.000049006136,0.00013935052],"domain_scores_gemma":[0.99801034,0.00035148242,0.000047714973,0.0013912016,0.00016320629,0.000036056223],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013804539,0.00010318417,0.00011397766,0.00008210964,0.00014283675,0.000016377753,0.00053091184,0.00025187654,0.000003829334],"category_scores_gemma":[0.00095918606,0.00011038406,0.0001278515,0.00024112876,0.00006246584,0.0000011935721,0.00012011615,0.00017410178,0.000002707953],"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":[0.00010535395,0.0005571551,0.037262358,0.00015291548,0.0014254134,0.0000011720786,0.000031442214,0.06615812,0.7723839,0.0265023,0.09273874,0.0026811264],"study_design_scores_gemma":[0.0010583885,0.000052540763,0.013243965,0.000058382866,0.00034693716,0.0000014791369,0.00002643659,0.14966774,0.078875095,0.000110935034,0.7561799,0.00037814936],"about_ca_topic_score_codex":0.0000023038456,"about_ca_topic_score_gemma":0.00010039243,"teacher_disagreement_score":0.6935088,"about_ca_system_score_codex":0.000017984961,"about_ca_system_score_gemma":0.00009239256,"threshold_uncertainty_score":0.45013314},"labels":[],"label_agreement":null},{"id":"W4409666529","doi":"10.7554/elife.92497.2","title":"Exploiting fluctuations in gene expression to detect causal interactions between genes","year":2025,"lang":"en","type":"preprint","venue":"eLife","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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":"Gene; Gene expression; Genetics; Computational biology; Biology; Expression (computer science); Computer science","score_opus":0.022135240399835405,"score_gpt":0.30426629385503606,"score_spread":0.2821310534552007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409666529","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":[0.9642708,0.0010758659,0.033348028,0.00017175174,0.000392152,0.00032508565,0.00009001214,0.000030557254,0.00029576113],"genre_scores_gemma":[0.9824834,0.00024730756,0.013725299,0.0001520968,0.0012892211,0.00023186387,0.00080354745,0.00003135392,0.0010359167],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9981524,0.00015414777,0.00046812295,0.00072621054,0.000205803,0.00029335977],"domain_scores_gemma":[0.99876523,0.00003368784,0.00014687456,0.0007806159,0.00014363418,0.00012992778],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00023746208,0.0002821501,0.0003451271,0.00030706395,0.00010977639,0.000043435703,0.0003577805,0.000267567,0.00002265002],"category_scores_gemma":[0.00015595849,0.00031546093,0.00021022813,0.00024121765,0.000021541558,0.0000030024667,0.0011822354,0.00030161053,0.000018885485],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019675907,0.000025027992,0.012967088,0.000043404158,0.00021455597,0.0000036046856,0.00011735523,0.07245582,0.9023764,0.0000020500531,0.0029642351,0.008810788],"study_design_scores_gemma":[0.00015696332,0.000026343172,0.012377898,0.00015473174,0.00010709511,0.0000013492805,0.00006093573,0.0003038688,0.97582465,0.000063932195,0.01054053,0.00038170346],"about_ca_topic_score_codex":0.00007471489,"about_ca_topic_score_gemma":0.00041506422,"teacher_disagreement_score":0.07344826,"about_ca_system_score_codex":0.00007992665,"about_ca_system_score_gemma":0.00021866974,"threshold_uncertainty_score":0.9999297},"labels":[],"label_agreement":null},{"id":"W4409879732","doi":"10.1016/j.isci.2025.112536","title":"Harnessing the analog computing power of regulatory networks with the Regulatory Network Machine","year":2025,"lang":"en","type":"article","venue":"iScience","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Kingston Health Sciences Centre; Kingston Process Metallurgy (Canada)","funders":"Templeton World Charity Foundation","keywords":"Regulatory science; Computer science; Chemistry; Biology; Ecology","score_opus":0.004508679443297565,"score_gpt":0.22231907870336362,"score_spread":0.21781039926006607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409879732","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":[0.9286455,0.013942234,0.054279875,0.0007254971,0.00021954978,0.00019028039,0.0000012286976,0.000017240576,0.0019785836],"genre_scores_gemma":[0.9978117,0.000028978817,0.00044298638,0.0007261847,0.0001682623,0.000004264109,0.0000052721284,0.000012688084,0.00079965877],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9984911,0.00017759323,0.0002562108,0.00041961364,0.00027273563,0.0003827543],"domain_scores_gemma":[0.9985459,0.000059283546,0.00022310892,0.0009998941,0.0001258732,0.000045977045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011430313,0.00017888045,0.00019713449,0.000039482202,0.0005844839,0.00005058516,0.00076004403,0.00009181596,0.0000075724947],"category_scores_gemma":[0.000023697825,0.00009799657,0.0001211178,0.0009380042,0.0009455065,0.0000060810808,0.00032065593,0.00015675905,6.8219794e-7],"study_design_candidate":"simulation_or_modeling","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":[0.000050976407,0.000026921334,0.035391767,0.000010498563,0.00016418291,0.0000023861069,0.00010529957,0.93097156,0.012552899,0.0010944712,0.012541738,0.007087324],"study_design_scores_gemma":[0.0009140298,0.0002952774,0.61344194,0.00031728134,0.00041641342,0.000060117574,0.000837463,0.31952372,0.020623295,0.00041007544,0.04230252,0.000857878],"about_ca_topic_score_codex":0.000013877091,"about_ca_topic_score_gemma":0.00007829138,"teacher_disagreement_score":0.6114478,"about_ca_system_score_codex":0.00001749833,"about_ca_system_score_gemma":0.00016241684,"threshold_uncertainty_score":0.44954368},"labels":[],"label_agreement":null},{"id":"W4409905545","doi":"10.1093/nargab/lqaf048","title":"Discovering governing equations of biological systems through representation learning and sparse model discovery","year":2025,"lang":"en","type":"article","venue":"NAR Genomics and Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"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 Waterloo","funders":"","keywords":"Autoencoder; Computer science; Identification (biology); Representation (politics); Gene regulatory network; Artificial intelligence; Machine learning; Dynamical systems theory; Biological network; Complex system; Biological data; Nonlinear system; PageRank; Systems biology; Key (lock); Theoretical computer science; Deep learning; Data mining; Computational biology; Gene; Biology; Bioinformatics; Gene expression","score_opus":0.02124096170560071,"score_gpt":0.26378734613985466,"score_spread":0.24254638443425394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409905545","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":[0.7858101,0.0014712702,0.21196117,0.000021902726,0.000038171467,0.00010060963,0.000018228448,0.0000047751782,0.00057375594],"genre_scores_gemma":[0.99075776,0.0027791387,0.0059416234,0.000024671808,0.00003181415,0.0000049864143,0.00011171311,0.0000059027757,0.0003423638],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931586,0.000024590341,0.0003226799,0.00014507554,0.00006829643,0.00012349848],"domain_scores_gemma":[0.9995976,0.000026003594,0.00017235501,0.00013944371,0.000039184804,0.000025382462],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015484319,0.000106146406,0.00017397021,0.00003909052,0.00011506806,0.0000658988,0.00006129714,0.00010432507,3.9885234e-7],"category_scores_gemma":[0.00006327251,0.000092672315,0.000051083825,0.00009479669,0.00008016852,0.000020627856,0.00017915375,0.00006810781,3.8013664e-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":[0.000101517515,0.0000504393,0.038678605,0.00036690768,0.00044619653,6.362888e-7,0.001228286,0.7352794,0.21004441,0.0077687968,0.0002232499,0.0058115725],"study_design_scores_gemma":[0.00032433023,0.00007481765,0.00062599976,0.000040446186,0.000072115676,0.0000038431144,0.002067787,0.98866695,0.005973592,0.00019448929,0.0017964449,0.0001592015],"about_ca_topic_score_codex":0.00001978892,"about_ca_topic_score_gemma":0.000006792376,"teacher_disagreement_score":0.25338754,"about_ca_system_score_codex":0.000016422584,"about_ca_system_score_gemma":0.000051409348,"threshold_uncertainty_score":0.37790674},"labels":[],"label_agreement":null},{"id":"W4410017164","doi":"10.1016/j.mbs.2025.109449","title":"Exploring the spatio–temporal dynamics in activator–inhibitor systems through a dual approach of analysis and computation","year":2025,"lang":"en","type":"article","venue":"Mathematical Biosciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"H2020 Marie Skłodowska-Curie Actions; British Columbia Knowledge Development Fund; Horizon 2020; Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Canada Research Chairs; Royal Society; Pacific Institute for the Mathematical Sciences; Canada Excellence Research Chairs, Government of Canada; Wolfson Foundation; Canada Foundation for Innovation; Simons Foundation","keywords":"Computation; Dual (grammatical number); Dynamics (music); Computer science; Activator (genetics); Algorithm; Sociology; Medicine; Internal medicine; Philosophy; Linguistics","score_opus":0.03393923073505847,"score_gpt":0.2716254700412398,"score_spread":0.23768623930618135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410017164","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":[0.90193325,0.00014371038,0.09706033,0.000097530334,0.000042764364,0.00012585965,0.000003393774,0.000004270478,0.0005889145],"genre_scores_gemma":[0.99718463,0.000019926823,0.0026657726,0.00001138602,0.00002066672,0.000024924972,0.000020455222,0.0000029070022,0.00004931038],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990733,0.000088776855,0.0002793343,0.00025224572,0.00017641358,0.0001299173],"domain_scores_gemma":[0.99961656,0.00005289733,0.00009414362,0.00017607579,0.000038149865,0.000022169897],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041764652,0.00009242754,0.00022225604,0.00011329336,0.00007209765,0.000041652314,0.00012719941,0.000044401946,7.1385153e-7],"category_scores_gemma":[0.00006723895,0.000061280334,0.00007520448,0.0010942434,0.0002546116,0.000011471272,0.00009533283,0.000041530886,2.5327935e-7],"study_design_candidate":"simulation_or_modeling","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":[0.000272425,0.002200108,0.5797838,0.0024312139,0.004093493,0.0000071948293,0.005498941,0.13661413,0.062205285,0.19032338,0.00047614594,0.016093876],"study_design_scores_gemma":[0.00035134584,0.00011907271,0.02608207,0.000087473796,0.00047101115,0.000004572478,0.007722309,0.94273806,0.018730067,0.0032899943,0.00010840042,0.0002956111],"about_ca_topic_score_codex":0.00006019189,"about_ca_topic_score_gemma":0.00008210518,"teacher_disagreement_score":0.8061239,"about_ca_system_score_codex":0.000020221256,"about_ca_system_score_gemma":0.000033610013,"threshold_uncertainty_score":0.24989393},"labels":[],"label_agreement":null},{"id":"W4410205270","doi":"10.1007/s13538-025-01785-y","title":"Two-State Stochastic Model of In Vivo Observations of Transcriptional Bursts","year":2025,"lang":"en","type":"article","venue":"Brazilian Journal of Physics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"National Institutes of Health; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; McGill University","keywords":"Physics; Statistical physics; Bursting; Drosophila melanogaster; Stochastic modelling; Stochastic process; Master equation; Gene expression; Expression (computer science); Gene; Computational biology; Genetics; Biology; Quantum mechanics; Statistics; Mathematics; Computer science; Neuroscience","score_opus":0.016199512606685153,"score_gpt":0.254851384516644,"score_spread":0.23865187190995887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410205270","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":[0.8812071,0.00040796728,0.118113995,0.00007300702,0.00005434612,0.000045196677,0.000025907453,7.5968217e-7,0.00007168411],"genre_scores_gemma":[0.9974017,0.00003270072,0.0022153766,0.000035512232,0.000060907452,0.0000011804636,0.0000065631143,0.000007835903,0.0002381918],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991346,0.000038633403,0.0004647437,0.00009985312,0.00015489444,0.00010725053],"domain_scores_gemma":[0.9992191,0.000012348692,0.0002796242,0.00016419681,0.0002877352,0.000037004895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015839521,0.00009089127,0.0002443557,0.00008641393,0.00001743663,0.0000035266987,0.00018157043,0.00004129403,0.000004249342],"category_scores_gemma":[0.00002166596,0.00009203784,0.0002173669,0.00026826403,0.00007695851,0.000008048466,0.000020881147,0.000079176345,1.2607137e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004449305,0.000074637406,0.0014161783,0.000017338629,0.00009360391,3.0708006e-7,0.000041255353,0.4748981,0.5221558,0.0007095356,0.000120733646,0.0004279847],"study_design_scores_gemma":[0.003372083,0.0003305452,0.0230802,0.00036912775,0.00039210735,0.000007749836,0.00018595163,0.14496467,0.8005031,0.026298651,0.00016989642,0.00032595132],"about_ca_topic_score_codex":0.0000036453737,"about_ca_topic_score_gemma":0.000026631878,"teacher_disagreement_score":0.32993343,"about_ca_system_score_codex":0.000015048667,"about_ca_system_score_gemma":0.00026211553,"threshold_uncertainty_score":0.3753194},"labels":[],"label_agreement":null},{"id":"W4410987009","doi":"10.1007/s11538-025-01471-9","title":"Modular Control of Boolean Network Models","year":2025,"lang":"en","type":"article","venue":"Bulletin of Mathematical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Defense Sciences Office, DARPA; National Heart, Lung, and Blood Institute; National Science Foundation; Advanced Research Projects Agency; Banff International Research Station for Mathematical Innovation and Discovery; American Association of Immunologists; Simons Foundation","keywords":"Boolean network; Modular design; Control (management); And-inverter graph; Boolean expression; Computer science; Boolean function; Mathematics; Theoretical computer science; Discrete mathematics; Artificial intelligence; Programming language","score_opus":0.00663133627631198,"score_gpt":0.22839674776792457,"score_spread":0.22176541149161258,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410987009","genre_codex":"methods","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":[0.42790863,0.0059452886,0.54320085,0.0016184394,0.00013453107,0.00047900307,0.000029677845,0.000023689532,0.020659866],"genre_scores_gemma":[0.99252796,0.00007640205,0.0061981464,0.00026934067,0.00007720556,0.00001596833,0.00002213187,0.000011533489,0.0008013275],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987558,0.00014903084,0.0005003781,0.00027309192,0.00007178501,0.00024993013],"domain_scores_gemma":[0.9990912,0.00008544213,0.00016669706,0.0004918872,0.00011827331,0.00004648985],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042350247,0.00014788737,0.0004852766,0.000045261222,0.000027618444,0.0000024146302,0.00027129985,0.00024428783,0.00018507363],"category_scores_gemma":[0.00013067535,0.00012740787,0.00023093841,0.00009867237,0.00026075792,4.1032575e-7,0.00012935998,0.00006177522,0.000012449407],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005160283,0.0006171339,0.0027602918,0.00053015305,0.0020460887,0.0000023292134,0.000030182902,0.08617725,0.415971,0.45311394,0.03406415,0.0041714427],"study_design_scores_gemma":[0.0048870784,0.0014058278,0.0011464088,0.00039799878,0.0010855107,0.000019871055,0.00010865407,0.04797685,0.16868655,0.57745755,0.19582513,0.0010025413],"about_ca_topic_score_codex":0.0000047404706,"about_ca_topic_score_gemma":0.0000012184008,"teacher_disagreement_score":0.5646193,"about_ca_system_score_codex":0.0000057737993,"about_ca_system_score_gemma":0.000036953657,"threshold_uncertainty_score":0.5195542},"labels":[],"label_agreement":null},{"id":"W4411151395","doi":"10.1063/5.0245376","title":"An accelerated hybrid framework for stochastic simulations of reaction–diffusion epidemic models","year":2025,"lang":"en","type":"article","venue":"AIP Advances","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Diffusion; Statistical physics; Reaction–diffusion system; Computer science; Physics; Thermodynamics","score_opus":0.01886158915210444,"score_gpt":0.32360454872223526,"score_spread":0.3047429595701308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411151395","genre_codex":"methods","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":[0.45715055,0.0016996851,0.5408321,0.000042700023,0.00008167358,0.00013419098,0.000020253487,0.000009923778,0.000028938022],"genre_scores_gemma":[0.9904389,0.00018487382,0.008792076,0.00011467327,0.00010525696,0.000027755626,0.00022771406,0.000012535724,0.00009625726],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99919194,0.000042308424,0.00024611823,0.0002971881,0.00006943456,0.00015299841],"domain_scores_gemma":[0.99920774,0.000084196676,0.00012722037,0.0003704726,0.0001698826,0.000040490515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000098445686,0.00011368938,0.00017953818,0.00007259297,0.00010419293,0.00000795448,0.00015000308,0.00009046663,0.000004998864],"category_scores_gemma":[0.00012415738,0.00011287319,0.00009290147,0.00018880471,0.000048885642,0.000014188013,0.000030881165,0.000052258205,4.5341423e-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":[0.0000807547,0.00006614707,0.0005946852,0.000020551248,0.00006724189,7.8503305e-8,0.000009167094,0.7251212,0.26753685,0.0012267618,0.00014125451,0.0051352945],"study_design_scores_gemma":[0.0006267327,0.00027284047,0.0010244931,0.00009690255,0.00022668637,0.000001496894,0.00010092384,0.73078287,0.12870996,0.13212276,0.00571162,0.00032274617],"about_ca_topic_score_codex":0.00000606028,"about_ca_topic_score_gemma":0.000021110154,"teacher_disagreement_score":0.5332883,"about_ca_system_score_codex":0.000014054547,"about_ca_system_score_gemma":0.000057988247,"threshold_uncertainty_score":0.46028352},"labels":[],"label_agreement":null},{"id":"W4411274961","doi":"10.1016/j.tcs.2025.115414","title":"Parameterized complexity of weighted target set selection","year":2025,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Exploratory Research for Advanced Technology; Japan Society for the Promotion of Science","keywords":"Parameterized complexity; Set (abstract data type); Selection (genetic algorithm); Mathematics; Computer science; Computational complexity theory; Algorithm; Theoretical computer science; Combinatorics; Artificial intelligence; Programming language","score_opus":0.010843718815755833,"score_gpt":0.260680608681841,"score_spread":0.24983688986608518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411274961","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":[0.5565009,0.000029592653,0.4426895,0.00009796826,0.00007915123,0.000057314952,0.0000020033547,0.000010454392,0.0005331176],"genre_scores_gemma":[0.94541657,0.000003914878,0.054342672,0.00014619436,0.000050924427,0.0000026850757,0.0000105020845,0.0000036427205,0.000022906816],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989172,0.00010320804,0.00019446979,0.0003694176,0.0001854717,0.0002302134],"domain_scores_gemma":[0.99935085,0.000018431641,0.000052647854,0.0003385557,0.00017065523,0.0000688436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005145004,0.00010058086,0.00016906405,0.000094408526,0.00012834764,0.000026705278,0.00042424485,0.000058568552,0.000043134973],"category_scores_gemma":[0.00003396473,0.00008756128,0.00008041857,0.0007410642,0.002710042,0.0000038502076,0.00028393994,0.000055970606,0.0000031180437],"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":[0.00010912535,0.000083494335,0.0028548052,0.000019063396,0.00006685196,5.718353e-7,0.000030070754,0.0009891485,0.4938728,0.49832103,0.00036749884,0.0032855687],"study_design_scores_gemma":[0.00030024874,0.00017413641,0.0042930176,0.000013841909,0.000027986596,0.0000045562747,0.0000039862416,0.26531586,0.656283,0.072951645,0.00048195105,0.0001497687],"about_ca_topic_score_codex":0.0000022321165,"about_ca_topic_score_gemma":9.995413e-7,"teacher_disagreement_score":0.42536938,"about_ca_system_score_codex":0.000014474093,"about_ca_system_score_gemma":0.00009982829,"threshold_uncertainty_score":0.99852633},"labels":[],"label_agreement":null},{"id":"W4411333582","doi":"10.1017/9781009546508.006","title":"Chance","year":2025,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Alberta","funders":"","keywords":"Philosophy","score_opus":0.009408174154365546,"score_gpt":0.18670868882367844,"score_spread":0.1773005146693129,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411333582","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00028693545,0.0010627842,0.0007901585,0.000011277728,0.00015379395,0.000181564,0.00011488588,0.000031545096,0.9973671],"genre_scores_gemma":[0.0024129252,0.00045262187,0.00009202385,0.0000919443,0.0002606738,6.2172626e-7,0.00021922251,0.000031639393,0.9964383],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989061,0.00002554209,0.00013023682,0.0005783799,0.00013734607,0.00022239212],"domain_scores_gemma":[0.9988442,0.0000069914718,0.00013987713,0.000772035,0.00013411047,0.00010275154],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00005429433,0.00030790802,0.00029433207,0.00010537301,0.00011270544,0.000015499301,0.00044342238,0.00047820358,0.0000036785596],"category_scores_gemma":[0.000005170439,0.00039170825,0.0003220175,0.000007855548,0.00014039842,0.0000013957903,0.00046675382,0.00018307556,0.0000076161923],"study_design_candidate":"not_applicable","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":[0.00014720684,0.000012086028,0.000008491163,0.000117532756,0.0011262534,0.0001117408,0.000005400667,0.000049428247,0.004906806,0.5102547,0.47923592,0.0040244446],"study_design_scores_gemma":[0.00023982684,0.000034688775,0.0000074366003,0.00006106627,0.00029118775,0.0000044811454,0.0000035517303,0.00003467949,0.0063853953,0.0000026691455,0.9925875,0.0003475041],"about_ca_topic_score_codex":0.000015463927,"about_ca_topic_score_gemma":0.000004030638,"teacher_disagreement_score":0.51335156,"about_ca_system_score_codex":0.000054829026,"about_ca_system_score_gemma":0.00013695605,"threshold_uncertainty_score":0.9998535},"labels":[],"label_agreement":null},{"id":"W4411695244","doi":"10.1103/rtzp-9kc5","title":"Efficiency-fluctuation trade-offs in biomolecular assembly processes","year":2025,"lang":"en","type":"article","venue":"Physical review. E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada; University of Toronto","keywords":"Biochemical engineering; Nanotechnology; Computer science; Materials science; Engineering","score_opus":0.007926890899209898,"score_gpt":0.30451189930544137,"score_spread":0.2965850084062315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411695244","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":[0.9101344,0.078463666,0.007133566,0.0013892314,0.000065335036,0.00048418326,0.0000029621908,0.000021171443,0.00230553],"genre_scores_gemma":[0.99308515,0.005771728,0.00007740815,0.0007660037,0.00009277536,0.000052269075,0.00005611351,0.0000110947285,0.000087461754],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989405,0.00009146508,0.00022955891,0.00037945472,0.00015126266,0.00020775417],"domain_scores_gemma":[0.9994714,0.00001812635,0.00006633462,0.0003452865,0.000054896736,0.000043954158],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015589333,0.00015248923,0.00027126065,0.000054544544,0.00003706308,0.0000131133065,0.00020996721,0.000049307906,0.000003910078],"category_scores_gemma":[0.00025447714,0.0001367658,0.0001488917,0.0008734662,0.000043229895,0.0000034714553,0.000064028296,0.00006742733,0.000013489172],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016174814,0.00038884606,0.0013188018,0.0013006437,0.00009267935,0.000003595247,0.000024276611,0.000483357,0.96990055,0.00073183107,0.0035011151,0.022238143],"study_design_scores_gemma":[0.0007468234,0.00022181812,0.008811361,0.0015442631,0.00042519713,0.0000040238624,0.00002421363,0.004738846,0.891342,0.0025130238,0.088933215,0.0006952487],"about_ca_topic_score_codex":0.0000037217833,"about_ca_topic_score_gemma":0.000014423519,"teacher_disagreement_score":0.0854321,"about_ca_system_score_codex":0.00001944286,"about_ca_system_score_gemma":0.00013659807,"threshold_uncertainty_score":0.55771476},"labels":[],"label_agreement":null},{"id":"W4412073242","doi":"10.1103/q5sd-tpms","title":"Joint Distribution of Nuclear and Cytoplasmic mRNA Levels in Stochastic Models of Gene Expression: Analytical Results and Parameter Inference","year":2025,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Science and Technology Innovation Plan Of Shanghai Science and Technology Commission; Leverhulme Trust","keywords":"Inference; Statistical physics; Gene expression; Joint (building); Expression (computer science); Joint probability distribution; Physics; Distribution (mathematics); Biology; Computational biology; Gene; Statistics; Mathematics; Computer science; Genetics; Mathematical analysis; Artificial intelligence","score_opus":0.021687328200920102,"score_gpt":0.28068542232932325,"score_spread":0.25899809412840313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412073242","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":[0.9884396,0.0031674858,0.00761834,0.0006016483,0.000007525115,0.00012558443,0.000028166407,0.0000018113291,0.000009826127],"genre_scores_gemma":[0.9981209,0.0011736802,0.00023640694,0.0004095412,0.000015502199,0.0000057038046,0.0000311963,0.0000047847866,0.0000022974962],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913293,0.0000800482,0.00031366316,0.0002635066,0.00009463248,0.00011523259],"domain_scores_gemma":[0.99952376,0.000047891655,0.00010798704,0.0002425459,0.0000361901,0.00004165182],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014214647,0.00010862182,0.00036817952,0.000027600281,0.000014294118,0.0000044529766,0.00007057384,0.00002429522,8.162541e-7],"category_scores_gemma":[0.00014975488,0.000092499715,0.00008557326,0.00014398585,0.00013669657,0.000005104777,0.00009718023,0.000066366585,2.4260922e-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":[0.00008331994,0.000103298924,0.00041804166,0.00064994773,0.000101549034,0.0000014091767,0.000037456106,0.015646523,0.9798159,0.0003724222,0.00068983034,0.0020802943],"study_design_scores_gemma":[0.004077786,0.0005970736,0.09148414,0.0106750345,0.0014480181,0.000013225007,0.000045324807,0.5981073,0.287971,0.0034930315,0.00084638834,0.0012417234],"about_ca_topic_score_codex":0.00000470528,"about_ca_topic_score_gemma":9.173604e-7,"teacher_disagreement_score":0.6918449,"about_ca_system_score_codex":0.000009444059,"about_ca_system_score_gemma":0.000016464915,"threshold_uncertainty_score":0.37720287},"labels":[],"label_agreement":null},{"id":"W4412346475","doi":"10.1109/kse63888.2024.11063540","title":"Simulation-Based Methods for Optimal Sampling Design in Systems Biology","year":2024,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Dalhousie University","funders":"","keywords":"Computer science; Sampling (signal processing)","score_opus":0.05642420140062456,"score_gpt":0.3930170799548753,"score_spread":0.33659287855425074,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412346475","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":[0.013674132,0.0036894435,0.9820575,0.000039658556,0.00019056139,0.00028130735,0.0000042240513,0.000026082784,0.00003707513],"genre_scores_gemma":[0.7255227,0.00000734334,0.27394268,0.000035251887,0.00015070623,0.000066265915,0.00007608534,0.00001802146,0.00018094982],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99899596,0.0001933606,0.00022103389,0.00035524918,0.000029918176,0.00020447875],"domain_scores_gemma":[0.9991674,0.00051439897,0.000025836645,0.00020154446,0.000052202977,0.000038630227],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008011891,0.00011545063,0.000155891,0.00010951706,0.00003209297,0.000036190388,0.00009717731,0.0001600735,0.000012794401],"category_scores_gemma":[0.00015316982,0.00010246895,0.000115449766,0.00017230389,0.000024502506,0.0000014747707,0.000022513766,0.000038807142,0.0000031026918],"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":[0.000022491035,0.000008060917,0.0001625519,0.00002695516,0.0000581603,2.5498608e-7,0.0000046358086,0.88779753,0.10691325,0.0003290906,0.00005685814,0.00462017],"study_design_scores_gemma":[0.00015884901,0.00008771784,0.000017066875,0.000012134092,0.0000312542,4.12151e-7,0.000014006154,0.9590951,0.022998316,0.00010047315,0.01735925,0.00012541206],"about_ca_topic_score_codex":0.000011695135,"about_ca_topic_score_gemma":0.000004341757,"teacher_disagreement_score":0.71184856,"about_ca_system_score_codex":0.000021583892,"about_ca_system_score_gemma":0.00009407532,"threshold_uncertainty_score":0.41785625},"labels":[],"label_agreement":null},{"id":"W4412348144","doi":"10.1007/s11071-025-11575-5","title":"Controllability of switched boolean networks with constraints by dynamic logic-based switching","year":2025,"lang":"en","type":"article","venue":"Nonlinear Dynamics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Science Foundation of Jiangxi Province; National Natural Science Foundation of China","keywords":"Controllability; Control theory (sociology); Computer science; Mathematics; Topology (electrical circuits); Combinatorics; Artificial intelligence; Control (management); Applied mathematics","score_opus":0.0027916007843839146,"score_gpt":0.22843340062981243,"score_spread":0.2256417998454285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412348144","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":[0.6126449,0.00046719683,0.38591745,0.00020824547,0.000064799795,0.00023380826,0.000058765963,0.000022310884,0.0003825002],"genre_scores_gemma":[0.9893342,0.000035466815,0.009234294,0.00037655918,0.000037319947,0.00001065615,0.000736369,0.00002793292,0.00020718107],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99848175,0.0001043319,0.00041695856,0.0004978864,0.00016677323,0.00033230946],"domain_scores_gemma":[0.9987581,0.00004683488,0.00021671005,0.000670201,0.00022483067,0.000083334366],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033743202,0.00026617316,0.00041561335,0.00006885315,0.00008124497,0.000020687814,0.00028647733,0.00026968028,0.00001273957],"category_scores_gemma":[0.000064558306,0.00023717259,0.00018041687,0.00031183055,0.000269808,0.0000030249546,0.00007661653,0.00018376295,8.6840487e-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":[0.0017489374,0.0009846574,0.113558345,0.0002516725,0.0019429997,0.000012348789,0.000024867253,0.5368912,0.3131097,0.0005491661,0.000608873,0.030317215],"study_design_scores_gemma":[0.0016808547,0.00020660934,0.0015138863,0.00004479937,0.00019271638,0.0000027618994,0.00007471428,0.98967904,0.005872377,0.000071478105,0.000381398,0.0002793397],"about_ca_topic_score_codex":0.000020437148,"about_ca_topic_score_gemma":0.0006311737,"teacher_disagreement_score":0.45278785,"about_ca_system_score_codex":0.000074379735,"about_ca_system_score_gemma":0.00025075348,"threshold_uncertainty_score":0.9671617},"labels":[],"label_agreement":null},{"id":"W4412655048","doi":"10.1093/nar/gkaf703","title":"Genetic “expiry-date” circuits control lifespan of synthetic scavenger bacteria for safe bioremediation","year":2025,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"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":"National Research Foundation of Korea","keywords":"Synthetic biology; Biology; Bacteria; Escherichia coli; Biotechnology; Lysis; Computational biology; Biochemical engineering; Genetics; Gene; Biochemistry","score_opus":0.02071150352959706,"score_gpt":0.30758368787800866,"score_spread":0.2868721843484116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412655048","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":[0.9901259,0.0011156318,0.0065347627,0.000506855,0.00015910718,0.000663599,0.000047377514,0.000011558792,0.0008352091],"genre_scores_gemma":[0.9974175,0.00019560973,0.00070849597,0.00007565705,0.00029140455,0.0001238529,0.000071352486,0.00003175267,0.0010843745],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9978862,0.000325441,0.00039353812,0.0005110353,0.00036620712,0.00051760656],"domain_scores_gemma":[0.99832577,0.000107792985,0.000089684916,0.00074607873,0.00061479694,0.00011585787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010428492,0.0001654363,0.00029306454,0.000300321,0.00016036739,0.000035528486,0.000447475,0.000270167,0.00007861145],"category_scores_gemma":[0.0004684496,0.00016437264,0.0001928641,0.00046763275,0.00025119964,0.0000044871763,0.00014507111,0.00013479158,0.00002179005],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013720969,0.000088987814,0.012288677,0.00011132096,0.00027023492,9.1539323e-7,0.000032094365,0.00023495522,0.9636904,0.00016409281,0.0043615196,0.018619617],"study_design_scores_gemma":[0.0034950634,0.00087331986,0.15294291,0.0001299353,0.00027116184,0.00000517257,0.00019529354,0.0071934527,0.7254495,0.00082207716,0.108095214,0.0005268816],"about_ca_topic_score_codex":0.000010738903,"about_ca_topic_score_gemma":0.000019853207,"teacher_disagreement_score":0.23824085,"about_ca_system_score_codex":0.00003974198,"about_ca_system_score_gemma":0.00026054835,"threshold_uncertainty_score":0.6702922},"labels":[],"label_agreement":null},{"id":"W4412775502","doi":"10.1101/2025.07.30.667606","title":"Phenotypic heterogeneity in a batch culture of <i>Chlamydomonas reinhardtii</i> with different light tolerances","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chlamydomonas reinhardtii; Phenotype; Chlamydomonas; Biology; Genetics; Evolutionary biology; Computational biology; Gene","score_opus":0.006240989997841985,"score_gpt":0.2080823502216099,"score_spread":0.20184136022376792,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412775502","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":[0.99006593,0.007958953,0.0008051342,0.000079858655,0.00029588156,0.00056818844,0.00014676499,0.00004755325,0.000031760905],"genre_scores_gemma":[0.997117,0.0009122947,0.0012492603,0.00011991881,0.00030944805,0.00018569679,0.0000035116345,0.00006818816,0.000034719356],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99681187,0.00022942954,0.0006905964,0.0013438404,0.00038588594,0.0005383932],"domain_scores_gemma":[0.9971445,0.000012620313,0.00050555245,0.0017423149,0.0004197805,0.00017519022],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002900074,0.00072521,0.0009794354,0.00021683212,0.00007794725,0.000059141705,0.00075184624,0.0007863668,0.000009623101],"category_scores_gemma":[0.000040499555,0.00063771755,0.00032611913,0.0005398234,0.00013691379,0.0000075064218,0.0006333968,0.00050260796,0.0000024008775],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024815166,0.0002661651,0.085001595,0.00059556635,0.00070544437,0.000018541994,0.000014478383,0.0024294618,0.91028565,0.000041431227,0.0003894167,0.000004074495],"study_design_scores_gemma":[0.0007807964,0.00014451845,0.057766043,0.0006088401,0.00026523427,2.3043123e-8,0.0000039819606,0.0001718565,0.93599194,0.0000016020713,0.0035335305,0.0007316124],"about_ca_topic_score_codex":0.00003938139,"about_ca_topic_score_gemma":0.0001269468,"teacher_disagreement_score":0.02723555,"about_ca_system_score_codex":0.00010698095,"about_ca_system_score_gemma":0.00044756336,"threshold_uncertainty_score":0.9996074},"labels":[],"label_agreement":null},{"id":"W4413051320","doi":"10.1109/tcyb.2025.3589571","title":"Asymptotic Feedback Stabilization of Boolean Control Networks With Random Impulsive Disturbances","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"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 Waterloo","funders":"Natural Science Foundation of Jiangxi Province; National Natural Science Foundation of China; National Science Foundation","keywords":"Subsequence; Markov chain; Partition (number theory); Mathematics; State space; State (computer science); Control theory (sociology); Domain (mathematical analysis); Probabilistic logic; Markov process; Sequence (biology); Set (abstract data type); Applied mathematics; Computer science; Algorithm; Control (management); Combinatorics; Mathematical analysis; Bounded function","score_opus":0.0030728550768612545,"score_gpt":0.20498520659032402,"score_spread":0.20191235151346276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413051320","genre_codex":"methods","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":[0.19786364,0.00069221616,0.8004806,0.00005406938,0.00023033141,0.0002926621,0.000024074641,0.00001501347,0.0003474198],"genre_scores_gemma":[0.9980436,0.00031758856,0.0003272344,0.00011414061,0.000070811286,0.000031916305,0.000027394739,0.000023776685,0.0010435208],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99886507,0.00010371032,0.0003106554,0.00033802525,0.0001616142,0.00022092502],"domain_scores_gemma":[0.9990425,0.00005471911,0.00013159927,0.00042518254,0.00028463663,0.00006134702],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010967355,0.00020670914,0.00029049403,0.00008521526,0.000096317024,0.000018657844,0.00015845642,0.00015415286,0.000021562822],"category_scores_gemma":[0.00000954536,0.00018150959,0.00016611858,0.00033775356,0.00017982032,0.000003963453,0.000001860278,0.000115635354,0.0000018759727],"study_design_candidate":"simulation_or_modeling","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":[0.0007619028,0.00016530577,0.0017068294,0.000026154668,0.0005708355,6.648921e-7,0.000024541929,0.9863598,0.006027968,0.000028147706,0.00043461172,0.003893267],"study_design_scores_gemma":[0.024860516,0.0032802944,0.01714193,0.0004979404,0.00419827,0.00001391564,0.00057741173,0.22810066,0.709876,0.00028694738,0.009427787,0.0017383262],"about_ca_topic_score_codex":0.000014973756,"about_ca_topic_score_gemma":0.00026788356,"teacher_disagreement_score":0.80017996,"about_ca_system_score_codex":0.000027301583,"about_ca_system_score_gemma":0.000079527694,"threshold_uncertainty_score":0.74017465},"labels":[],"label_agreement":null},{"id":"W4413423780","doi":"10.1098/rsfs.2025.0011","title":"Genetic network structure and dynamics: identifying simple negative feedback loops","year":2025,"lang":"en","type":"article","venue":"Interface Focus","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"University of Victoria; McGill University; Ottawa Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Computer science; Simple (philosophy); Dynamics (music); Data science; Physics","score_opus":0.004816220529453243,"score_gpt":0.24617682468541907,"score_spread":0.24136060415596583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413423780","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":[0.9497975,0.013711786,0.035413623,0.00014970182,0.00021302434,0.00015882231,0.000021419943,0.000018504386,0.0005156278],"genre_scores_gemma":[0.99681026,0.000134996,0.0015099575,0.000055790544,0.00019803522,0.0000074125946,0.0000133935855,0.000023383964,0.001246751],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99879724,0.000078276855,0.00024007086,0.00047295573,0.000090687245,0.00032079188],"domain_scores_gemma":[0.99932474,0.000018938445,0.000089959256,0.00041194478,0.00008351992,0.00007090014],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000072133815,0.00021608206,0.000218392,0.000054145123,0.00012425783,0.00007430094,0.00022835241,0.00017755134,0.000058934624],"category_scores_gemma":[0.00003540364,0.00021583616,0.00009103764,0.00023034115,0.00011084046,0.00000409821,0.00025221021,0.00012551538,0.0000068904237],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004102728,0.00008594069,0.15406501,0.00019893394,0.0029409162,0.000020436413,0.00036028906,0.09479901,0.57069564,0.00060242927,0.04567034,0.13015078],"study_design_scores_gemma":[0.0023741294,0.00044852466,0.08261217,0.00025206423,0.000765543,0.00007169894,0.0010319457,0.027156856,0.81165165,0.03386446,0.0382059,0.0015650556],"about_ca_topic_score_codex":0.00006966219,"about_ca_topic_score_gemma":0.0014319716,"teacher_disagreement_score":0.24095601,"about_ca_system_score_codex":0.000034957327,"about_ca_system_score_gemma":0.000043935168,"threshold_uncertainty_score":0.8801543},"labels":[],"label_agreement":null},{"id":"W4413814888","doi":"10.1103/vlx8-spc6","title":"Noise equals control","year":2025,"lang":"en","type":"article","venue":"Physical review. E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Noise (video); Acoustics; Mathematics; Physics; Computer science; Artificial intelligence","score_opus":0.006516623576450027,"score_gpt":0.31035609216156806,"score_spread":0.303839468585118,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413814888","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":[0.7987172,0.17017964,0.010149153,0.004008593,0.00020948316,0.00079496467,0.000017660195,0.000045354005,0.015877936],"genre_scores_gemma":[0.9904123,0.0050409175,0.000038552993,0.0032194576,0.0002602765,0.00004177844,0.000027316066,0.00000919682,0.0009502175],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99920356,0.000091115624,0.00016620173,0.00026847256,0.000096085096,0.00017454982],"domain_scores_gemma":[0.99936205,0.000019375138,0.000053703414,0.00044183,0.000064211,0.00005884453],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013820759,0.00012299855,0.0002932139,0.000016531107,0.000037925744,0.0000083425375,0.0001764745,0.000033707154,0.000019266796],"category_scores_gemma":[0.00011404651,0.000103933206,0.00028079163,0.00018113191,0.000039279577,0.0000012407992,0.00006399384,0.0000541069,0.00007302401],"study_design_candidate":"not_applicable","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":[0.00003896877,0.00027978994,0.0027210412,0.0006376844,0.00060187094,0.0000025137463,0.0000055280066,0.00036025955,0.84522843,0.0078103645,0.10137634,0.04093718],"study_design_scores_gemma":[0.0009839225,0.00014428854,0.0031424663,0.0006156849,0.0009633395,0.0000018850129,0.000004430779,0.0034598364,0.11971273,0.0044188225,0.866044,0.00050862733],"about_ca_topic_score_codex":0.0000019610434,"about_ca_topic_score_gemma":0.0000018711861,"teacher_disagreement_score":0.76466763,"about_ca_system_score_codex":0.000008449079,"about_ca_system_score_gemma":0.00004172813,"threshold_uncertainty_score":0.42382732},"labels":[],"label_agreement":null},{"id":"W4413916998","doi":"10.47749/t/unicamp.2025.1506235","title":"Bell nonclassicality in networks","year":2025,"lang":"en","type":"dissertation","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Computer science","score_opus":0.0055806834803450705,"score_gpt":0.2503656036365162,"score_spread":0.24478492015617115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413916998","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":[0.8353069,0.0069038644,0.0020106684,0.00009786415,0.0009810742,0.00043467127,0.000009763148,0.00003154689,0.1542237],"genre_scores_gemma":[0.8249383,0.00059740874,0.0001722918,0.00015166638,0.0003340425,0.000036455083,0.0047619794,0.000025802521,0.16898203],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99873585,0.00007317619,0.0003123513,0.0005167601,0.000112175796,0.0002496935],"domain_scores_gemma":[0.9992833,0.000008991506,0.00009532141,0.0004897148,0.00006891725,0.000053769854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015369321,0.00023512579,0.0002977036,0.00009832556,0.00003641731,0.00001747878,0.00023425216,0.0006705117,0.00007945255],"category_scores_gemma":[0.000025236444,0.00023627923,0.00021593344,0.00025846314,0.000014723272,7.1026005e-7,0.00005459765,0.00019820814,0.0000067190663],"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":[0.0020926332,0.0016722654,0.07666673,0.0013588773,0.0042172545,0.00008941479,0.0002424016,0.158008,0.11094407,0.0035584674,0.420289,0.22086087],"study_design_scores_gemma":[0.0036712254,0.0004754086,0.18546285,0.00074811105,0.0014204502,0.0000062057065,0.0009529727,0.049047995,0.15061384,0.0012811102,0.6013276,0.004992207],"about_ca_topic_score_codex":0.000055536126,"about_ca_topic_score_gemma":0.008217548,"teacher_disagreement_score":0.21586865,"about_ca_system_score_codex":0.00002716332,"about_ca_system_score_gemma":0.00016034661,"threshold_uncertainty_score":0.9635187},"labels":[],"label_agreement":null},{"id":"W4413968204","doi":"10.1073/pnas.2417416122","title":"Nonlinear memory in cell-division dynamics across species","year":2025,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Toronto Metropolitan University","funders":"MathWorks; National Science Foundation; Alfred P. Sloan Foundation; Schmidt Futures","keywords":"Cell division; Nonlinear system; Biology; Division (mathematics); Biological system; Computer science; Mathematics; Cell; Genetics; Physics","score_opus":0.01465100534736453,"score_gpt":0.2933061183327029,"score_spread":0.2786551129853384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413968204","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":[0.9931511,0.0002689661,0.0000047125873,0.0008003069,0.000014327664,0.00006627369,0.0000098196115,0.0000018180801,0.005682665],"genre_scores_gemma":[0.9976323,0.000056721994,0.0007850808,0.00011827956,0.000038110127,0.0000024878757,6.880169e-7,0.0000020319846,0.0013642772],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99906427,0.0000050084213,0.00022170691,0.00020396512,0.00038610902,0.00011892928],"domain_scores_gemma":[0.99963975,0.000016190628,0.00016947181,0.000010262336,0.00015123976,0.000013072414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007766873,0.00006580559,0.00010296827,0.00008513232,0.00009516209,0.00001213443,0.00055257045,0.00008870614,0.0000021873097],"category_scores_gemma":[0.0001458781,0.000048186954,0.00007596656,0.0006790178,0.0004403483,0.000010137728,0.00024204155,0.00007276386,2.89126e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012492499,0.000058350983,0.06819793,0.000049710034,0.000016527953,2.7762959e-9,0.00005160234,0.00300704,0.9254965,0.0018834439,0.0007311014,0.0004952668],"study_design_scores_gemma":[0.00015520355,0.000022238242,0.11795441,0.000040332823,0.000007007943,5.0878305e-7,0.00036143188,0.008186739,0.870488,0.0022821743,0.00043866265,0.00006332586],"about_ca_topic_score_codex":0.000002991094,"about_ca_topic_score_gemma":9.923314e-7,"teacher_disagreement_score":0.055008564,"about_ca_system_score_codex":0.000022761697,"about_ca_system_score_gemma":0.00003219124,"threshold_uncertainty_score":0.19650069},"labels":[],"label_agreement":null},{"id":"W4414084902","doi":"10.1093/bioinformatics/btaf497","title":"PEtab.jl: advancing the efficiency and utility of dynamic modelling","year":2025,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Medical Research Council; Stiftelsen för Strategisk Forskning; Deutsche Forschungsgemeinschaft; Wellcome Trust; Francis Crick Institute; Vetenskapsrådet; Cancer Research UK","keywords":"R package; Software package; Software; Dynamic programming","score_opus":0.005400617714703178,"score_gpt":0.22796683724358083,"score_spread":0.22256621952887765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414084902","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":[0.6639266,0.0017052792,0.33246124,0.000058501642,0.000050553204,0.00010325495,0.000004593765,0.0000061779397,0.0016838019],"genre_scores_gemma":[0.99335593,0.00030380714,0.0060533173,0.000064971464,0.000009777008,0.0000023745176,0.000013108091,0.0000037673192,0.00019294156],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99940467,0.000018704355,0.00026489302,0.00009096504,0.00008105843,0.000139717],"domain_scores_gemma":[0.9994746,0.000015805634,0.00009321483,0.0003348421,0.000056983372,0.000024543915],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027498847,0.000084947016,0.00011619074,0.000037044356,0.000085975225,0.0000116136225,0.0001391276,0.000058521586,0.0000027415863],"category_scores_gemma":[0.000029935205,0.00006184894,0.00006383312,0.00014670996,0.00009538539,0.0000035324376,0.000116634765,0.000044943834,8.052847e-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":[0.00034977836,0.0004882873,0.040976107,0.0033427954,0.0018820304,0.0000021612207,0.0040048263,0.55438566,0.1016679,0.0035460435,0.00875409,0.28060034],"study_design_scores_gemma":[0.00012494347,0.000020906522,0.00073283835,0.000017696271,0.000052393272,0.0000017056808,0.00031138683,0.9905298,0.005646283,0.00011838593,0.0023740656,0.00006961997],"about_ca_topic_score_codex":0.0000042317924,"about_ca_topic_score_gemma":0.00001263652,"teacher_disagreement_score":0.43614414,"about_ca_system_score_codex":0.0000053984336,"about_ca_system_score_gemma":0.000055213215,"threshold_uncertainty_score":0.25221267},"labels":[],"label_agreement":null},{"id":"W4414491377","doi":"10.1063/5.0285101","title":"Collective directional switches of swarming systems with higher-order interactions","year":2025,"lang":"en","type":"article","venue":"Chaos An Interdisciplinary Journal of Nonlinear Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Waterloo","funders":"National Natural Science Foundation of China","keywords":"Generality; Collective behavior; Pairwise comparison; Swarming (honey bee); Collective motion; Control theory (sociology); Mechanism (biology)","score_opus":0.012070501472502637,"score_gpt":0.31439518599357685,"score_spread":0.3023246845210742,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414491377","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":[0.98552674,0.0004894807,0.011766894,0.00022559214,0.0007431527,0.00008186588,0.00000856401,0.000004076041,0.0011536191],"genre_scores_gemma":[0.9938921,0.000014626853,0.0038098434,0.000017330636,0.00032880134,0.0000037232091,0.000004542792,0.000009045325,0.0019199961],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998812,0.000047342917,0.00041168628,0.0002599385,0.00029147198,0.00017754117],"domain_scores_gemma":[0.9981219,0.000023320721,0.00038691884,0.00025732646,0.0011113697,0.00009917183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004932331,0.00013048535,0.00024636812,0.0003689799,0.00031809288,0.00004753447,0.00043158888,0.000046571327,0.00001377002],"category_scores_gemma":[0.000034812358,0.00009949674,0.00010901855,0.000981861,0.00045850314,0.000042210857,0.00028865042,0.00014308805,7.331275e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00088003883,0.00065787835,0.015213826,0.00006505209,0.00062948896,0.000017743698,0.001122656,0.05025854,0.92823386,0.000101128906,0.00074109365,0.002078715],"study_design_scores_gemma":[0.0032414107,0.0074084233,0.0813289,0.0020535674,0.00076298066,0.0016983435,0.015097988,0.06380582,0.8131317,0.0007229769,0.00955642,0.0011915028],"about_ca_topic_score_codex":0.0000042083448,"about_ca_topic_score_gemma":0.00002577887,"teacher_disagreement_score":0.11510217,"about_ca_system_score_codex":0.000120102166,"about_ca_system_score_gemma":0.0011216745,"threshold_uncertainty_score":0.40573594},"labels":[],"label_agreement":null},{"id":"W4414800130","doi":"10.1093/neuonc/noaf193.466","title":"P14.05.B CAR T-CELL THERAPY DOES NOT LEAD TO MEDIUM-TERM NEUROCOGNITIVE DETERIORATION IN PATIENTS WITH CENTRAL NERVOUS SYSTEM LYMPHOMAS. A LOC NETWORK STUDY","year":2025,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Neurocognitive; Neuropsychology; Neurotoxicity; Central nervous system; Lymphoma; Primary central nervous system lymphoma","score_opus":0.005836706736002294,"score_gpt":0.23210302602825794,"score_spread":0.22626631929225566,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414800130","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":[0.99689764,0.000107604865,0.00024441618,0.00017164185,0.0007622397,0.0015582684,0.000012590522,0.00003479637,0.00021077799],"genre_scores_gemma":[0.9974794,0.00003689076,0.00009895518,0.0016586037,0.0003204278,0.00022106653,0.00007600237,0.00004786267,0.00006080703],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99702084,0.0007178788,0.0004958938,0.000886917,0.00023907867,0.00063940487],"domain_scores_gemma":[0.9988382,0.000062409315,0.00020846161,0.00052690704,0.00021542037,0.00014858825],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002029127,0.0003638917,0.00053614547,0.00016200816,0.00012961778,0.000039649727,0.00033693443,0.00024769106,0.0000049093924],"category_scores_gemma":[0.000031883046,0.0002891883,0.000108015534,0.0005066452,0.00007614457,0.0000086860155,0.00019434054,0.00016692518,0.0000068062927],"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":[0.0037511713,0.0012210043,0.629108,0.000044772416,0.0002642034,0.0001789391,0.0005414838,0.0060144328,0.33557865,0.0000045845513,0.00086231274,0.022430448],"study_design_scores_gemma":[0.01212247,0.011127237,0.8711086,0.00005995949,0.00031731956,0.000014442367,0.0009455171,0.00046017583,0.09583071,0.000005697177,0.0072498852,0.00075796805],"about_ca_topic_score_codex":0.000044165365,"about_ca_topic_score_gemma":0.0010166625,"teacher_disagreement_score":0.24200064,"about_ca_system_score_codex":0.00020398494,"about_ca_system_score_gemma":0.00034619236,"threshold_uncertainty_score":0.999956},"labels":[],"label_agreement":null},{"id":"W4414805233","doi":"10.1016/j.coisb.2025.100560","title":"Machine-learned summary statistics for Bayesian inference of systems biology–model parameters: Opportunities and challenges","year":2025,"lang":"en","type":"article","venue":"Current Opinion in Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft; Deutsches Forschungszentrum für Künstliche Intelligenz","keywords":"Interpretability; Overfitting; Inference; Identifiability; Selection (genetic algorithm); Model selection; Bayesian inference; Deep learning","score_opus":0.12776490900862641,"score_gpt":0.35945076192980907,"score_spread":0.23168585292118266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414805233","genre_codex":"review","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":[0.0297422,0.583232,0.37692368,0.0003734404,0.006298695,0.0015248782,0.0016308465,0.00003440674,0.00023989314],"genre_scores_gemma":[0.9148954,0.08280119,0.0006254786,0.000008431585,0.00013943006,0.00023222156,0.0011917499,0.000016306809,0.00008974614],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980997,0.0003862954,0.00064962765,0.00051003456,0.0000513729,0.00030299468],"domain_scores_gemma":[0.9989154,0.00016993884,0.00028713793,0.00039443167,0.00016592276,0.00006722275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005375247,0.00023946995,0.00055555376,0.00024119411,0.000051684256,0.00001619692,0.00022851664,0.0003182089,6.714386e-7],"category_scores_gemma":[0.00014132289,0.00022089567,0.00007673443,0.000095515745,0.00024525062,0.0000043963996,0.00015121403,0.000094033465,2.8407356e-7],"study_design_candidate":"theoretical_or_conceptual","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":[0.00067466334,0.00054552674,0.12595971,0.01786069,0.0015486146,8.5108934e-7,0.0004597514,0.02381254,0.016025556,0.66251934,0.0079945605,0.14259818],"study_design_scores_gemma":[0.004886804,0.0019873036,0.002579777,0.00294998,0.00028529638,0.000019520507,0.0027704472,0.5610018,0.0008703904,0.0116361715,0.409225,0.0017875304],"about_ca_topic_score_codex":0.000060345403,"about_ca_topic_score_gemma":0.00001919482,"teacher_disagreement_score":0.88515323,"about_ca_system_score_codex":0.00002305328,"about_ca_system_score_gemma":0.00015593476,"threshold_uncertainty_score":0.90078646},"labels":[],"label_agreement":null},{"id":"W4414824146","doi":"10.1177/15578666251382251","title":"Bayesian Validation of Dynamic Systems for Biological Networks","year":2025,"lang":"en","type":"article","venue":"Journal of Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Simon Fraser University","funders":"National Research Foundation of Korea","keywords":"Ode; Bayesian probability; Set (abstract data type); Process (computing); Biological data; Ordinary differential equation; Biological network; Bayesian network; Interpretation (philosophy)","score_opus":0.008340144347964068,"score_gpt":0.2789221383341564,"score_spread":0.2705819939861923,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414824146","genre_codex":"methods","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":[0.36878225,0.0026189066,0.6280565,0.00011704639,0.00030022068,0.00008341341,0.00000806294,0.0000016577858,0.000031922875],"genre_scores_gemma":[0.99519795,0.00015566415,0.004169766,0.000064302665,0.00017600156,0.0000044522762,0.00018139838,0.0000049335267,0.000045519304],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990345,0.00013801867,0.0005230218,0.00013182907,0.00005693468,0.00011568904],"domain_scores_gemma":[0.9988336,0.00011875241,0.00044007748,0.00009026089,0.00048502142,0.000032270837],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004172393,0.000089344176,0.00026751345,0.00013022263,0.00003839177,0.0000072005964,0.00015839683,0.00017479455,0.0000033503302],"category_scores_gemma":[0.00008860143,0.00007258789,0.00020003722,0.00013406364,0.00008058137,0.0000023944415,0.000033274104,0.000056355428,2.1159026e-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":[0.00022569639,0.00006212462,0.00852736,0.000021542384,0.00049064535,4.89696e-7,0.0000045250504,0.9588752,0.025557507,0.002207401,0.0013141487,0.002713364],"study_design_scores_gemma":[0.0048514074,0.0039714347,0.04023485,0.0001794009,0.0005502044,0.00019077126,0.00016566446,0.86292773,0.01537338,0.044375192,0.026539389,0.00064058363],"about_ca_topic_score_codex":0.0000010350304,"about_ca_topic_score_gemma":6.6152563e-7,"teacher_disagreement_score":0.6264157,"about_ca_system_score_codex":0.000019334128,"about_ca_system_score_gemma":0.000117766416,"threshold_uncertainty_score":0.29600483},"labels":[],"label_agreement":null},{"id":"W4414910998","doi":"10.1073/pnas.2501324122","title":"Dynamic sensor selection for biomarker discovery","year":2025,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Air Force Research Laboratory; Air Force Office of Scientific Research; National Institute of General Medical Sciences; National Science Foundation","keywords":"Observability; Biomarker discovery; Biomarker; Selection (genetic algorithm); Generality","score_opus":0.015894059133617335,"score_gpt":0.2995811773455037,"score_spread":0.28368711821188636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414910998","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":[0.99727225,0.00020720762,0.00014167342,0.0012069719,0.000016853437,0.00012734956,0.000007711609,0.000002536589,0.0010174633],"genre_scores_gemma":[0.9967604,0.000023027675,0.0015270507,0.00012867572,0.000025636971,0.000010159816,5.2256803e-7,0.000002114894,0.0015223732],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999338,0.000003446248,0.0001557455,0.00018355569,0.00023329307,0.00008597662],"domain_scores_gemma":[0.9996201,0.000018126608,0.00015804301,0.000005590531,0.00018899179,0.000009151747],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004965742,0.000054401127,0.000075831886,0.00009052797,0.000116956166,0.000013371043,0.00027741402,0.00006863079,0.0000010296902],"category_scores_gemma":[0.0001813236,0.000038498285,0.00010107631,0.00049059745,0.00026197886,0.000012993557,0.00006951373,0.000028625684,8.656846e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001910403,0.000013487242,0.0073818937,0.000028415845,0.000044551914,8.3359396e-11,0.000003199703,0.0004106507,0.98664206,0.0038299207,0.0013538459,0.00027286194],"study_design_scores_gemma":[0.0001413443,0.000031498414,0.056482367,0.000024191366,0.000036074212,0.0000014387801,0.00004347095,0.010944438,0.9190876,0.0117506385,0.0013952967,0.0000616616],"about_ca_topic_score_codex":0.0000010346997,"about_ca_topic_score_gemma":2.0427505e-7,"teacher_disagreement_score":0.06755449,"about_ca_system_score_codex":0.000014291662,"about_ca_system_score_gemma":0.000034444594,"threshold_uncertainty_score":0.15699145},"labels":[],"label_agreement":null},{"id":"W4415053529","doi":"10.1101/2025.10.08.681135","title":"Synchronized path-integration recalibration but distinct landmark-control dynamics in head direction and CA1 place cells","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"National Institutes of Health; Japan Student Services Organization; Johns Hopkins University; Masason Foundation; Quad Fellowship","keywords":"Path integration; Dynamics (music); Displacement (psychology); Position (finance); Process (computing); Head (geology); Path (computing); Cognition; Differential (mechanical device)","score_opus":0.004466270017397669,"score_gpt":0.19973538555043155,"score_spread":0.1952691155330339,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415053529","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":[0.9727054,0.0019113912,0.023458397,0.00014891695,0.0006298232,0.00069944694,0.0003447268,0.000083164385,0.000018733685],"genre_scores_gemma":[0.99738765,0.0006750608,0.0012041667,0.000076324606,0.0003490866,0.0001695629,0.000016416605,0.00005661878,0.00006509526],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99746066,0.00035641476,0.00054631126,0.0010581076,0.00020425692,0.00037427538],"domain_scores_gemma":[0.99843144,0.00003925471,0.00034217437,0.00083191565,0.00023627271,0.00011892681],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005717142,0.0004923306,0.0005431843,0.00022881392,0.000121325116,0.00014439128,0.00023568262,0.00077689486,0.0000066057723],"category_scores_gemma":[0.00013664119,0.0005393183,0.0001562794,0.00033458698,0.00007724651,0.000014295186,0.00023086589,0.00041013103,0.0000029244623],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027761862,0.00013450204,0.03771199,0.0002998783,0.00028573457,0.000014674096,0.0000052713667,0.0033085828,0.9574471,0.00008389935,0.0003743626,0.00005639507],"study_design_scores_gemma":[0.003385632,0.00019826347,0.107866555,0.00088376354,0.0006632569,9.378983e-8,0.000014696709,0.27636963,0.6056112,0.000005906842,0.003148578,0.0018524348],"about_ca_topic_score_codex":0.0002496786,"about_ca_topic_score_gemma":0.0008250002,"teacher_disagreement_score":0.3518359,"about_ca_system_score_codex":0.0004257819,"about_ca_system_score_gemma":0.000422069,"threshold_uncertainty_score":0.99970585},"labels":[],"label_agreement":null},{"id":"W4415288116","doi":"10.1007/s11538-025-01532-z","title":"Generation of Virtual Populations for Quantitative Systems Pharmacology Through Advanced Sampling Methods","year":2025,"lang":"en","type":"article","venue":"Bulletin of Mathematical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Sampling (signal processing); Parametric statistics; Markov chain; Markov chain Monte Carlo; Adaptive sampling; Population; In silico; Gibbs sampling; Monte Carlo method","score_opus":0.10677364621684642,"score_gpt":0.43655893888189745,"score_spread":0.329785292665051,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415288116","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":[0.15022026,0.0016395185,0.8466603,0.0003816674,0.00027793032,0.0003861949,0.000031531876,0.000007123738,0.00039546026],"genre_scores_gemma":[0.5007805,0.000057801357,0.49820635,0.00012989888,0.00009584516,0.00013118755,0.00017185166,0.000013152603,0.00041337239],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998641,0.00029239923,0.0005727583,0.00027884863,0.00004340571,0.0001715693],"domain_scores_gemma":[0.9989648,0.0003045584,0.00025291747,0.0002217729,0.00023204836,0.00002394403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005225477,0.00013022708,0.0004311928,0.000060095266,0.000054269738,0.0000031872694,0.000150715,0.00020122994,0.00005690623],"category_scores_gemma":[0.00048744888,0.00011699444,0.00016539454,0.000101179605,0.00018084527,0.0000010580685,0.00007662592,0.000044130793,0.000002603319],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008952193,0.00008793595,0.000034008724,0.00011154086,0.00022435276,3.6292423e-8,0.000025721456,0.005707164,0.79641134,0.19318138,0.0029998596,0.0011271619],"study_design_scores_gemma":[0.0017808097,0.0015523153,0.000056332967,0.00007591377,0.0005828189,0.0000047826643,0.00038426032,0.014579406,0.81070036,0.025214467,0.14471412,0.0003543838],"about_ca_topic_score_codex":0.000005741762,"about_ca_topic_score_gemma":0.0000015714164,"teacher_disagreement_score":0.35056028,"about_ca_system_score_codex":0.000010691147,"about_ca_system_score_gemma":0.000041354328,"threshold_uncertainty_score":0.47708946},"labels":[],"label_agreement":null},{"id":"W4415588730","doi":"10.1101/2025.10.23.683559","title":"Design principles underlying nearly-homeostatic biological networks","year":2025,"lang":"","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Process (computing); Design elements and principles; Systems design; State (computer science); Complex system; Biological network; Design process; Work (physics)","score_opus":0.03874484699966224,"score_gpt":0.24837148639223475,"score_spread":0.2096266393925725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415588730","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":[0.50335,0.026376782,0.46452013,0.0002532981,0.00233353,0.002621906,0.00017997356,0.0003325231,0.000031865962],"genre_scores_gemma":[0.96329194,0.011082677,0.023147983,0.0005061443,0.00112576,0.0004897335,0.000006915287,0.00025005062,0.00009877255],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.98876566,0.0018489392,0.002176926,0.0041324715,0.00072979945,0.0023461892],"domain_scores_gemma":[0.991793,0.00028678426,0.001478663,0.00431021,0.0011910875,0.0009402812],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.0025842532,0.002207169,0.002084757,0.0005702644,0.0009279716,0.0006591213,0.0023311994,0.0033675937,0.00014133529],"category_scores_gemma":[0.0005722975,0.0023859027,0.0010962324,0.0017701022,0.0007918235,0.000028218297,0.0027229611,0.0017165933,0.00009744665],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043199933,0.000636054,0.014184809,0.00065196614,0.004275976,0.00012430696,0.000015416996,0.2670498,0.71130085,0.00046234092,0.00082111935,0.000045365614],"study_design_scores_gemma":[0.0048177564,0.0018715683,0.11735188,0.0031001105,0.004562255,4.070262e-7,0.00005176601,0.25621113,0.537577,0.000018416908,0.063017674,0.011420049],"about_ca_topic_score_codex":0.00003173818,"about_ca_topic_score_gemma":0.000005178577,"teacher_disagreement_score":0.45994198,"about_ca_system_score_codex":0.0005341692,"about_ca_system_score_gemma":0.0025208483,"threshold_uncertainty_score":0.9990668},"labels":[],"label_agreement":null},{"id":"W4415615039","doi":"10.1093/biomtc/ujaf141","title":"A Bayesian collocation integral method for system identification of ordinary differential equations","year":2025,"lang":"en","type":"article","venue":"Biometrics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Ode; Ordinary differential equation; Frequentist inference; Collocation (remote sensing); Collocation method; Identification (biology); Trajectory; Bayesian probability; System identification","score_opus":0.013096959576466546,"score_gpt":0.3031745698066669,"score_spread":0.29007761023020034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415615039","genre_codex":"methods","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":[0.04520554,0.00060927385,0.9534821,0.00004013071,0.0002576775,0.00028036846,0.00004129454,0.000011549037,0.000072099225],"genre_scores_gemma":[0.9849618,0.000016471986,0.01353412,0.000009241422,0.00007961783,0.00007367576,0.00040309696,0.000009441293,0.0009125514],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991,0.000075444856,0.0003579312,0.0002426697,0.00011021796,0.00011372243],"domain_scores_gemma":[0.99907804,0.00006165916,0.00018751777,0.00032475227,0.0003183781,0.000029673198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003597979,0.000090527814,0.0001564133,0.0007840535,0.00007433997,0.000019457637,0.00016305946,0.00013307255,0.0000021231035],"category_scores_gemma":[0.00030693103,0.00009121247,0.0001516384,0.0023539208,0.000027424772,0.0000025078243,0.00005022786,0.000023043336,8.639685e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005223351,0.00009624068,0.0007598445,0.00019714244,0.00026105525,7.497783e-8,0.000011815381,0.00054990966,0.9706885,0.004307797,0.0016964155,0.021378955],"study_design_scores_gemma":[0.0009080093,0.00021630684,0.008297973,0.00004523503,0.00062695215,0.0000017500224,0.00029895332,0.2812969,0.7015807,0.00026631556,0.0061976374,0.00026321964],"about_ca_topic_score_codex":0.000013828296,"about_ca_topic_score_gemma":0.0000075748358,"teacher_disagreement_score":0.93994796,"about_ca_system_score_codex":0.000052758194,"about_ca_system_score_gemma":0.00008583973,"threshold_uncertainty_score":0.37195364},"labels":[],"label_agreement":null},{"id":"W4415961898","doi":"10.48550/arxiv.2510.17126","title":"Practicalities of State-Dependent and Threshold Delay Differential Equations","year":2025,"lang":"","type":"preprint","venue":"ArXiv.org","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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","keywords":"Linearization; Heuristic; Delay differential equation; Simple (philosophy); Term (time); Constant (computer programming); Numerical analysis; Discrete time and continuous time; Control theory (sociology)","score_opus":0.027019832720248726,"score_gpt":0.2794393776962465,"score_spread":0.2524195449759978,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415961898","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":[0.9736617,0.0061444873,0.017988572,0.00027616625,0.00054384896,0.000478603,0.0002505584,0.000014698671,0.0006413231],"genre_scores_gemma":[0.986185,0.005552105,0.00017765028,0.00008217938,0.00030806518,0.00006930775,0.00044438877,0.00004116286,0.0071401517],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9963194,0.0003164599,0.0011258139,0.0012689559,0.00041902272,0.0005503086],"domain_scores_gemma":[0.9970027,0.00013455687,0.0007147983,0.0014587728,0.00046162098,0.00022755389],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00038895197,0.00063371554,0.0008701324,0.00018783163,0.00021393118,0.00007236646,0.0005114369,0.0007442829,0.00020010426],"category_scores_gemma":[0.0002310651,0.0006627516,0.0004896637,0.00018553887,0.0004812716,0.0000091819575,0.0019971407,0.0005577241,0.000011393864],"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":[0.00067171454,0.001221369,0.7278854,0.001544991,0.009826342,0.000027300594,0.000828361,0.021145042,0.2313041,0.0012127992,0.00080724026,0.0035253102],"study_design_scores_gemma":[0.004486233,0.0011900876,0.21309942,0.0010183441,0.0098711215,0.000042493113,0.0016410433,0.021038434,0.7286966,0.0027778235,0.012049771,0.0040886374],"about_ca_topic_score_codex":0.00012540289,"about_ca_topic_score_gemma":0.00023801543,"teacher_disagreement_score":0.514786,"about_ca_system_score_codex":0.00005679615,"about_ca_system_score_gemma":0.00057389535,"threshold_uncertainty_score":0.99958235},"labels":[],"label_agreement":null},{"id":"W4416019844","doi":"10.1101/2025.11.07.684636","title":"Collective parameter estimation of related models with an initial stability constraint","year":2025,"lang":"","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Deutsche Forschungsgemeinschaft; European Commission; HORIZON EUROPE Framework Programme; Ministère de l'Économie, de la Science et de l'Innovation - Québec","keywords":"Estimation theory; Parameter space; Constraint (computer-aided design); Stability (learning theory); Set (abstract data type); Series (stratigraphy); Perturbation (astronomy); Experimental data; Control theory (sociology); Systems biology","score_opus":0.015334712188732608,"score_gpt":0.23341713374989967,"score_spread":0.21808242156116706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416019844","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":[0.938993,0.0008349594,0.057347234,0.000044803175,0.000342262,0.001602594,0.0006948608,0.00007617616,0.00006410954],"genre_scores_gemma":[0.9729064,0.00017348971,0.02637496,0.000054800872,0.00012484811,0.00023289483,0.000010064713,0.00011005134,0.00001246895],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99350804,0.0010012337,0.001622842,0.0024196643,0.00062272913,0.0008255139],"domain_scores_gemma":[0.99285513,0.0001147298,0.0013997979,0.0029947,0.0021746925,0.00046097237],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0012898819,0.0011382935,0.0014744991,0.00039969236,0.00029131875,0.00013819331,0.00080248737,0.0016791985,0.000078670484],"category_scores_gemma":[0.00032816682,0.001225963,0.00048167256,0.0013137558,0.0011353431,0.000047976195,0.0005818989,0.0008315654,0.0000038034636],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020744503,0.0017520726,0.008524599,0.0013662536,0.0061655054,0.00003924274,0.00016024506,0.34651998,0.6321103,0.0012010252,0.000033649325,0.00005265293],"study_design_scores_gemma":[0.0017634459,0.0010143876,0.0076370332,0.00054353604,0.0015701392,8.8987385e-8,0.000025911506,0.18688416,0.7990307,0.000064369386,0.000046270892,0.0014199117],"about_ca_topic_score_codex":0.000063608815,"about_ca_topic_score_gemma":0.000018856863,"teacher_disagreement_score":0.16692042,"about_ca_system_score_codex":0.00061065843,"about_ca_system_score_gemma":0.007383352,"threshold_uncertainty_score":0.9996168},"labels":[],"label_agreement":null},{"id":"W4416078518","doi":"10.1371/journal.pcbi.1013662","title":"Optimization of experimental designs for biological rhythm discovery","year":2025,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Natural Sciences and Engineering Research Council of Canada; Lietuvos Mokslo Taryba; Krembil Foundation","keywords":"Range (aeronautics); Sampling (signal processing); Rhythm; Design of experiments; Protocol (science); Construct (python library); Experimental research","score_opus":0.027234458164158815,"score_gpt":0.2874016844313032,"score_spread":0.2601672262671444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416078518","genre_codex":"methods","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":[0.4338566,0.0007279124,0.564966,0.00007440411,0.0000625404,0.00016418961,0.000031659045,0.000007067718,0.000109594694],"genre_scores_gemma":[0.9637276,0.0000211051,0.034685295,0.00016006513,0.00008190273,0.000054344604,0.0011623383,0.000006412216,0.000100963945],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992698,0.000072596216,0.00022138744,0.00027072048,0.000039010865,0.00012652365],"domain_scores_gemma":[0.99959254,0.00007018346,0.00008451826,0.00011594857,0.000116194846,0.000020608895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007509261,0.0000999512,0.000168199,0.00006552804,0.00005399943,0.000006657397,0.000101448895,0.00013161606,0.000012856857],"category_scores_gemma":[0.000056430064,0.00008991984,0.00011382319,0.00010527299,0.000119747754,0.000002800263,0.000069586255,0.000023063716,7.7502784e-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":[0.00019477282,0.0002057317,0.0046393266,0.000012170703,0.00031736848,1.738612e-7,0.000008772287,0.52483064,0.45993137,0.008987132,0.0005522057,0.00032033958],"study_design_scores_gemma":[0.001957926,0.0013330595,0.002972943,0.000026547092,0.00011168882,0.000007655213,0.000089151705,0.25190508,0.7316269,0.007533144,0.0020185965,0.0004173101],"about_ca_topic_score_codex":0.0000010839829,"about_ca_topic_score_gemma":5.428649e-7,"teacher_disagreement_score":0.5302807,"about_ca_system_score_codex":0.000013542054,"about_ca_system_score_gemma":0.00007224413,"threshold_uncertainty_score":0.36668247},"labels":[],"label_agreement":null},{"id":"W4416097704","doi":"10.48550/arxiv.2505.04912","title":"Using random perturbations to infer the structure of feedback control in gene expression","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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","keywords":"Perturbation (astronomy); Negative feedback; Feedback control; Stochastic process; Expression (computer science); Infinitesimal; Control theory (sociology); Gene expression","score_opus":0.0191029562005935,"score_gpt":0.26980606203784646,"score_spread":0.25070310583725297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416097704","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":[0.9884015,0.0014198099,0.009152352,0.00021924172,0.000202833,0.00046211388,0.00008650352,0.000005256007,0.000050410632],"genre_scores_gemma":[0.99802303,0.00007678793,0.00084384024,0.0003505522,0.00024886185,0.000017082912,0.00014092214,0.000017017337,0.00028192165],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9986296,0.0001997066,0.00038320405,0.00045168895,0.00013633359,0.00019941019],"domain_scores_gemma":[0.99870914,0.000033984128,0.00018625248,0.00086079945,0.00015737889,0.000052453222],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015289879,0.00023448182,0.000382065,0.00010469304,0.00006974702,0.000014864198,0.00038747655,0.0003706286,0.000030818937],"category_scores_gemma":[0.00011687649,0.00017644097,0.00022252146,0.00018312102,0.000054951255,0.0000017582523,0.0005252408,0.00023832191,0.0000012935658],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008396436,0.000015746311,0.12621148,0.000024067633,0.00012800758,4.5946646e-7,0.000070834416,0.15811573,0.7150313,0.0000016209542,0.0002527316,0.00006404229],"study_design_scores_gemma":[0.0020092486,0.000033767727,0.10449648,0.00021254116,0.00033384102,0.000002261116,0.000072958595,0.004474275,0.88615483,0.00013374577,0.0016805858,0.00039549224],"about_ca_topic_score_codex":0.00006335385,"about_ca_topic_score_gemma":0.000118132004,"teacher_disagreement_score":0.17112347,"about_ca_system_score_codex":0.00003339858,"about_ca_system_score_gemma":0.00019036939,"threshold_uncertainty_score":0.71950537},"labels":[],"label_agreement":null},{"id":"W4416295096","doi":"10.1101/2025.11.13.688103","title":"Analytical Solutions for the Time-Dependent Dynamics of Stochastic Gene Expression with mRNA-sRNA Interactions","year":2025,"lang":"","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Queen's University","funders":"","keywords":"Inference; Translation (biology); Stochastic process; Dynamics (music); Expression (computer science); Stochastic modelling; Messenger RNA; Transcription (linguistics); Gene expression","score_opus":0.010346007669586498,"score_gpt":0.2295046116647739,"score_spread":0.2191586039951874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416295096","genre_codex":"methods","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":[0.2228816,0.0037936503,0.76689726,0.00073355425,0.0010974609,0.0024095383,0.0020985093,0.00007422898,0.000014224852],"genre_scores_gemma":[0.993458,0.00042945394,0.0045389757,0.000069624795,0.0006227856,0.00053968735,0.000012182136,0.00012775227,0.00020158177],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99526864,0.0002830867,0.0011722861,0.0016810705,0.000561484,0.0010334043],"domain_scores_gemma":[0.9936862,0.00027098073,0.001057183,0.0029502779,0.0016956461,0.0003396928],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010060348,0.0009284003,0.001023359,0.00035661555,0.00079628645,0.00014885148,0.0012364947,0.00077842834,0.00007150997],"category_scores_gemma":[0.00031314496,0.0007886951,0.0007635234,0.00076981523,0.00055138976,0.000019006478,0.0013211252,0.00074101106,0.000012472704],"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":[0.0004981399,0.0005274885,0.00077515305,0.00031328938,0.003446292,0.0000045840225,0.00000650897,0.25168598,0.74186945,0.00033390918,0.0005249448,0.000014267837],"study_design_scores_gemma":[0.0015487234,0.0003802274,0.00216573,0.0009152294,0.005219151,2.191579e-7,0.00003318954,0.54471546,0.44220686,0.000003956326,0.0014122374,0.0013990075],"about_ca_topic_score_codex":0.000047015164,"about_ca_topic_score_gemma":0.00006431146,"teacher_disagreement_score":0.77057636,"about_ca_system_score_codex":0.00042480847,"about_ca_system_score_gemma":0.0017080727,"threshold_uncertainty_score":0.9994564},"labels":[],"label_agreement":null},{"id":"W4416644676","doi":"10.7554/elife.92497.3","title":"Exploiting fluctuations in gene expression to detect causal interactions between genes","year":2025,"lang":"","type":"article","venue":"eLife","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Connaught Fund; University of Toronto","keywords":"Relation (database); Set (abstract data type); Gene; Population; Gene regulatory network; Gene expression; Regulation of gene expression; Process (computing)","score_opus":0.015152563941564851,"score_gpt":0.2934880861137157,"score_spread":0.27833552217215085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416644676","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":[0.94826806,0.003816109,0.045763787,0.00060035824,0.0005183678,0.00037627429,0.000033714492,0.00002092529,0.00060238695],"genre_scores_gemma":[0.9903151,0.0005747685,0.0058500823,0.00033272686,0.0010665238,0.00011911219,0.00017582717,0.000040006707,0.0015258876],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99724305,0.00027542666,0.0007935666,0.00087013945,0.00026069913,0.00055714324],"domain_scores_gemma":[0.9985012,0.00007528924,0.00016516155,0.0008150028,0.00021698164,0.00022639062],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00038491987,0.00036232074,0.00043711648,0.00049360294,0.00031844495,0.0000803215,0.00037588488,0.00024434362,0.00006642338],"category_scores_gemma":[0.0002739165,0.0004198754,0.00025814195,0.0009787283,0.000057857204,0.0000123303,0.0005364429,0.00024823117,0.00005915167],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034603538,0.000043484863,0.023266494,0.00002367561,0.0002314765,0.0000041350418,0.0001167556,0.010960272,0.93690425,0.0000058815244,0.0018663619,0.026542595],"study_design_scores_gemma":[0.0003874379,0.00006473672,0.021026237,0.0001519476,0.00018408848,0.0000020416205,0.00024199598,0.00051490794,0.9488247,0.00004008143,0.028179754,0.0003820592],"about_ca_topic_score_codex":0.000054589556,"about_ca_topic_score_gemma":0.0004507069,"teacher_disagreement_score":0.04204699,"about_ca_system_score_codex":0.00014650414,"about_ca_system_score_gemma":0.0003125476,"threshold_uncertainty_score":0.9998253},"labels":[],"label_agreement":null},{"id":"W4416789847","doi":"10.1007/s00285-025-02320-y","title":"On the reduction of stochastic chemical reaction networks","year":2025,"lang":"en","type":"article","venue":"Journal of Mathematical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Eigenvalues and eigenvectors; Projection (relational algebra); Reduction (mathematics); Noise (video); Master equation; Manifold (fluid mechanics); Stochastic process; Oblique projection","score_opus":0.00819157788579076,"score_gpt":0.25580056959129754,"score_spread":0.2476089917055068,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416789847","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":[0.88807684,0.00036135668,0.11003018,0.0007583477,0.00019281091,0.000072029776,6.74179e-7,0.0000021255573,0.0005056394],"genre_scores_gemma":[0.99917597,0.000027725184,0.00040364958,0.00007630399,0.00021170234,0.0000024593883,0.0000033511224,0.000005221319,0.00009362566],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991715,0.00011242033,0.0004203331,0.000104765146,0.000075928925,0.00011503485],"domain_scores_gemma":[0.99918693,0.00013192125,0.00029517704,0.00021623334,0.00013759681,0.000032113887],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051192095,0.00008736783,0.00023474387,0.00006255137,0.000027669643,0.000003857257,0.00017212867,0.00016789824,0.000023537164],"category_scores_gemma":[0.00044056,0.00005269166,0.00018593091,0.00012974099,0.00014663281,0.0000014828836,0.000042210093,0.00015674639,0.0000022704667],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025133355,0.00015923829,0.000022689246,0.000017310904,0.00035260397,4.994562e-7,0.0000126500545,0.0022970797,0.9574709,0.03382401,0.003598332,0.0019933863],"study_design_scores_gemma":[0.0019485424,0.0022819508,0.0005386194,0.0005019924,0.0010610785,0.0005464785,0.00038630923,0.013428715,0.6431163,0.3335182,0.0021817698,0.0004900605],"about_ca_topic_score_codex":3.0331154e-7,"about_ca_topic_score_gemma":1.4668613e-7,"teacher_disagreement_score":0.3143546,"about_ca_system_score_codex":0.000016566397,"about_ca_system_score_gemma":0.00004162302,"threshold_uncertainty_score":0.21487035},"labels":[],"label_agreement":null},{"id":"W4416875187","doi":"10.1109/qce65121.2025.00247","title":"Identifying Protein Co-Regulatory Network Logic by Solving B-Sat Problems Through Gate-Based Quantum Computing","year":2025,"lang":"","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Saskatchewan","funders":"","keywords":"Context (archaeology); Heuristic; Constraint satisfaction problem; Boolean satisfiability problem; Domain (mathematical analysis); Constraint (computer-aided design); Quantum computer; Computational complexity theory","score_opus":0.015974756076648416,"score_gpt":0.2716584514084316,"score_spread":0.25568369533178315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416875187","genre_codex":"methods","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":[0.45776078,0.062682204,0.46886492,0.0010929463,0.0012102124,0.0026696625,0.0000338894,0.00021672684,0.00546867],"genre_scores_gemma":[0.98563904,0.00030707644,0.0056857984,0.0016062276,0.0007761997,0.000080843434,0.0007359391,0.00013826329,0.005030596],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99211705,0.00085182587,0.0018651314,0.0023514864,0.0006910748,0.002123444],"domain_scores_gemma":[0.9964121,0.00008932874,0.0009081595,0.0018772708,0.000415834,0.00029730648],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0016576026,0.0012205282,0.0012549631,0.00017985627,0.0013878129,0.0004902189,0.0011345611,0.0011663154,0.00024868222],"category_scores_gemma":[0.00008913472,0.0012896856,0.0009970302,0.0013637254,0.0006349271,0.00002839351,0.0007569159,0.00064798363,0.00007628923],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020880307,0.0006177086,0.0119838845,0.0016367135,0.0026498951,0.000019861513,0.00012411368,0.3487131,0.5545622,0.0035086484,0.072347246,0.0036278076],"study_design_scores_gemma":[0.0050562993,0.0007210465,0.001177382,0.0033911776,0.0017015326,0.000015598449,0.0006719807,0.42255273,0.45202348,0.0072054625,0.10122951,0.0042538024],"about_ca_topic_score_codex":0.00010901474,"about_ca_topic_score_gemma":0.000099586025,"teacher_disagreement_score":0.5278783,"about_ca_system_score_codex":0.00026750306,"about_ca_system_score_gemma":0.000841315,"threshold_uncertainty_score":0.99991226},"labels":[],"label_agreement":null},{"id":"W4417131431","doi":"10.1007/s10928-025-10009-4","title":"Identification and characterization of virtual sub-populations through phenotype-guided filtering. The challenging case of nonidentifiable models in the context of therapeutic evaluation","year":2025,"lang":"en","type":"article","venue":"Journal of Pharmacokinetics and Pharmacodynamics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Identification (biology); Context (archaeology); Quality (philosophy); Parametric statistics; Parametric model; Context model","score_opus":0.033905671217423494,"score_gpt":0.3319367555655703,"score_spread":0.2980310843481468,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417131431","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":[0.9739692,0.0025268341,0.022886524,0.00018997568,0.00015582828,0.0002282375,0.000023407345,7.0383555e-7,0.000019276556],"genre_scores_gemma":[0.99572426,0.0040507317,0.00006236242,0.00006350047,0.00004760058,0.0000051982265,0.00002709251,0.0000079645715,0.000011296656],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99875283,0.00021101636,0.0006586366,0.00011009216,0.00018416553,0.000083285675],"domain_scores_gemma":[0.9987411,0.00004092355,0.0006396079,0.000147065,0.00041459655,0.000016687387],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010618655,0.00009929747,0.00019673033,0.00010689975,0.000059863694,0.000016095302,0.0001445505,0.00004803943,0.0000033403066],"category_scores_gemma":[0.000016903705,0.00007355307,0.000073152136,0.00022860247,0.00009376056,0.000023636543,0.00004458173,0.00009627428,1.8685421e-8],"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":[0.000064294596,0.00007258503,0.0004090097,0.00006874572,0.00017219404,0.0000013692027,0.00072685943,0.047686514,0.9418339,0.00068039267,0.000019915782,0.008264179],"study_design_scores_gemma":[0.0011609106,0.000071565686,0.0028278118,0.00005537724,0.0007746621,0.000063652195,0.00066820625,0.7487007,0.24462521,0.0008752438,0.000092382485,0.00008428975],"about_ca_topic_score_codex":0.000016317306,"about_ca_topic_score_gemma":0.000017113245,"teacher_disagreement_score":0.70101416,"about_ca_system_score_codex":0.000012582801,"about_ca_system_score_gemma":0.00005245692,"threshold_uncertainty_score":0.29994074},"labels":[],"label_agreement":null},{"id":"W4417198384","doi":"10.1016/j.cels.2025.101475","title":"Low-burden and precursor-free cell-cell communication in mammalian cells enabled by de novo design of super-sensitive intercellular signals","year":2025,"lang":"en","type":"article","venue":"Cell Systems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Science Foundation of Beijing Municipality; Jilin University; Center for Life Sciences; Ministry of Science and Technology of the People's Republic of China; Chinese Academy of Sciences; National Natural Science Foundation of China; National Key Research and Development Program of China; Peking University; Canadian Anesthesiologists' Society","keywords":"Morphogen; Intracellular; Cell signaling; Endogeny; SIGNAL (programming language); Signal transduction; Synthetic biology; Immunogenicity","score_opus":0.0055272604951949736,"score_gpt":0.2010700448700628,"score_spread":0.19554278437486783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417198384","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":[0.966259,0.01458168,0.016572252,0.00003807448,0.00007462798,0.0006236706,0.00002335912,0.000009609897,0.0018177459],"genre_scores_gemma":[0.99305797,0.000594954,0.00051352655,0.000027194208,0.00004729438,0.000032612843,0.00009460325,0.000028068198,0.005603757],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9979323,0.00073344464,0.0004844463,0.00041181032,0.00012491697,0.00031304933],"domain_scores_gemma":[0.99862677,0.00007318602,0.00019370415,0.0008943055,0.00012570947,0.00008630365],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007226176,0.00023110003,0.00038602066,0.00011990934,0.00005318706,0.00003906674,0.00044994813,0.00028460057,0.0000077836885],"category_scores_gemma":[0.000016572281,0.0002479126,0.00009364964,0.0002227024,0.00010153238,0.000005920698,0.00024527186,0.00012162721,0.0000060943385],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000063379106,0.00008511851,0.0005281756,0.00035505928,0.000050768882,0.000004109903,0.00030272987,0.015058564,0.97891366,0.000003578976,0.0045643537,0.0000704795],"study_design_scores_gemma":[0.0009929144,0.00010382808,0.00002700235,0.0001389118,0.00008831716,0.0000025120157,0.00096066867,0.0072967694,0.9881962,0.000020437212,0.001958705,0.00021375348],"about_ca_topic_score_codex":0.0003792888,"about_ca_topic_score_gemma":0.000042214404,"teacher_disagreement_score":0.02679901,"about_ca_system_score_codex":0.000057876943,"about_ca_system_score_gemma":0.00009928161,"threshold_uncertainty_score":0.9999973},"labels":[],"label_agreement":null},{"id":"W4417250660","doi":"10.1371/journal.pcbi.1013217","title":"How cells tame noise while maintaining ultrasensitive transcriptional responses","year":2025,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Université de Montréal","funders":"Samsung Science and Technology Foundation; Institute for Basic Science; National Research Foundation of Korea; Inha University","keywords":"Robustness (evolution); Psychological repression; Bistability; Regulation of gene expression; microRNA; Gene regulatory network; Noise (video); Systems biology; Transcriptional regulation","score_opus":0.012596330582453978,"score_gpt":0.23828014422260518,"score_spread":0.2256838136401512,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417250660","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":[0.926491,0.0006394257,0.06936629,0.0024052989,0.00018713645,0.00017391561,0.00014827719,0.00003189026,0.0005567458],"genre_scores_gemma":[0.9916339,0.0000286689,0.004732202,0.0009807181,0.00020107417,0.000022766153,0.0010537358,0.000013607084,0.0013333518],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9986963,0.00026141296,0.00020560289,0.0004665023,0.000105257765,0.0002649166],"domain_scores_gemma":[0.9992973,0.00014368683,0.000077938814,0.00017816854,0.00023759062,0.000065301494],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015317675,0.000181435,0.00021283128,0.00015077219,0.00014090359,0.000034898738,0.00015150972,0.00017724818,0.00002703741],"category_scores_gemma":[0.000076683216,0.00018462936,0.0001551013,0.00020165934,0.00019366226,0.0000046835776,0.000054843786,0.000098379016,0.000012896037],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022632384,0.00009122104,0.0033790702,0.000009352096,0.00045470358,0.000004324088,0.000029297928,0.021549726,0.96624047,0.0057445723,0.0016001827,0.00067078404],"study_design_scores_gemma":[0.0031612907,0.0008612168,0.05188996,0.00008918502,0.00047809127,0.000059546994,0.00062952994,0.03723599,0.8184812,0.019087126,0.06670353,0.0013233549],"about_ca_topic_score_codex":0.000003224803,"about_ca_topic_score_gemma":0.0000086560685,"teacher_disagreement_score":0.14775926,"about_ca_system_score_codex":0.000031734744,"about_ca_system_score_gemma":0.00019084284,"threshold_uncertainty_score":0.7528967},"labels":[],"label_agreement":null},{"id":"W4417421875","doi":"10.1016/j.ifacol.2025.12.189","title":"Implementation and Mathematical Modeling of a Copper Controller in Yeast","year":2025,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Copper; Yeast; Controller (irrigation); Control theory (sociology); Control system; Genetic algorithm; Control (management)","score_opus":0.007652632345166222,"score_gpt":0.2805905372987694,"score_spread":0.2729379049536032,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417421875","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":[0.99439865,0.0008103671,0.0038390064,0.00022840964,0.000011196785,0.00012323228,0.000010296614,0.0000032731366,0.00057557627],"genre_scores_gemma":[0.98770267,0.00006360712,0.01170572,0.000094673946,0.000031771488,0.000009658026,0.000038467093,0.000006587944,0.00034687467],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993976,0.000028974038,0.00021871831,0.00017441873,0.0000646412,0.00011566229],"domain_scores_gemma":[0.9997759,0.000006556394,0.000036884016,0.000116897965,0.000038357484,0.000025441503],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013219197,0.0000824689,0.00017079455,0.000058037513,0.000018145065,0.0000057223897,0.000052408617,0.00006579117,0.000040909177],"category_scores_gemma":[0.000017430044,0.000076106735,0.00005315493,0.00009499105,0.000029571107,0.0000018844187,0.000045230012,0.00003526889,0.000001923712],"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":[0.0003031162,0.00020643332,0.020655394,0.00014161611,0.00042606567,0.0000024322205,0.00021796748,0.01891672,0.93988717,0.0010489397,0.000051911782,0.018142236],"study_design_scores_gemma":[0.00875192,0.00034300424,0.007808482,0.00018048665,0.00039610403,0.000012723855,0.003481637,0.91816837,0.057954375,0.0013861379,0.0009209811,0.00059581024],"about_ca_topic_score_codex":0.000017995388,"about_ca_topic_score_gemma":0.00013371737,"teacher_disagreement_score":0.89925164,"about_ca_system_score_codex":0.000008777862,"about_ca_system_score_gemma":0.000030954783,"threshold_uncertainty_score":0.31035423},"labels":[],"label_agreement":null},{"id":"W4417453587","doi":"10.7554/elife.92497.4","title":"Exploiting fluctuations in gene expression to detect causal interactions between genes","year":2025,"lang":"en","type":"article","venue":"eLife","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Relation (database); Gene; Gene regulatory network; Regulation of gene expression; Gene expression; Set (abstract data type); Population; Systems biology; Process (computing)","score_opus":0.014167945919278922,"score_gpt":0.29073147408312366,"score_spread":0.2765635281638447,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417453587","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":[0.96888596,0.00043508929,0.02992227,0.00019477156,0.00011531033,0.00011380908,0.0000061413007,0.000015214381,0.00031143578],"genre_scores_gemma":[0.99319935,0.000048343747,0.005349053,0.0001968132,0.00034460388,0.000056457236,0.00007938798,0.000012628955,0.00071334664],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99912596,0.000066171364,0.00023003314,0.00029516613,0.000097219236,0.00018542999],"domain_scores_gemma":[0.99949694,0.00002156938,0.000040639166,0.0003093256,0.000064788816,0.00006671429],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013717829,0.00010760442,0.00013212113,0.00016721485,0.000097784075,0.000018986788,0.00013569724,0.0000624849,0.000015427086],"category_scores_gemma":[0.000100687554,0.00011388408,0.00007258777,0.00031466322,0.000014397077,0.0000037524374,0.00015254493,0.000067851324,0.000018646479],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007674232,0.000008824562,0.01957601,0.0000033166689,0.000039124636,8.3115026e-7,0.000028010603,0.0037793897,0.96925145,0.0000037809289,0.0015127358,0.005788831],"study_design_scores_gemma":[0.00013678189,0.000019510439,0.034266658,0.000022766113,0.00002606458,7.280485e-7,0.00006326998,0.00010707703,0.95276403,0.000028062044,0.012450359,0.00011471693],"about_ca_topic_score_codex":0.000022814607,"about_ca_topic_score_gemma":0.00022202662,"teacher_disagreement_score":0.024573216,"about_ca_system_score_codex":0.000031530115,"about_ca_system_score_gemma":0.00005914527,"threshold_uncertainty_score":0.4644058},"labels":[],"label_agreement":null},{"id":"W578413142","doi":"10.1007/s00285-015-0906-z","title":"Using sign patterns to detect the possibility of periodicity in biological systems","year":2015,"lang":"en","type":"article","venue":"Journal of Mathematical Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Jacobian matrix and determinant; Eigenvalues and eigenvectors; Sign (mathematics); Mathematics; Hopf bifurcation; Matrix (chemical analysis); Bifurcation; Dynamical systems theory; Mathematical analysis; Applied mathematics; Physics; Nonlinear system","score_opus":0.07155089833501191,"score_gpt":0.3204908683585444,"score_spread":0.2489399700235325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W578413142","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":[0.9614934,0.0006052036,0.03755879,0.000089520705,0.000086802465,0.00012810678,0.000005125005,0.0000014247071,0.000031670817],"genre_scores_gemma":[0.997293,0.000015143914,0.0024659235,0.00005142478,0.00015950062,0.0000023869486,0.0000014533715,0.0000061943733,0.000004959313],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99832267,0.00049484125,0.00070021435,0.00015818959,0.00012509343,0.00019902174],"domain_scores_gemma":[0.99897456,0.00008800992,0.00031664773,0.00027734,0.00021073547,0.0001326817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001893575,0.000118564756,0.00044738763,0.00007015105,0.000020992324,0.000009116429,0.00031544245,0.0001857085,0.00001205582],"category_scores_gemma":[0.00076886674,0.00006519333,0.00016572398,0.00013932525,0.0001462114,0.0000023474959,0.00012513614,0.00012921802,0.0000025247423],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005770342,0.00032923833,0.20874508,0.00009391755,0.00033833575,0.000020245936,0.00045990723,0.007908405,0.7788234,0.0006859053,0.00022843055,0.0017901536],"study_design_scores_gemma":[0.013274593,0.033840273,0.2560608,0.0015516056,0.0014550515,0.0061694104,0.015302756,0.03612792,0.5260936,0.09847868,0.007864637,0.0037806693],"about_ca_topic_score_codex":0.000015791562,"about_ca_topic_score_gemma":0.000011540755,"teacher_disagreement_score":0.25272974,"about_ca_system_score_codex":0.000036436064,"about_ca_system_score_gemma":0.000097381126,"threshold_uncertainty_score":0.2658507},"labels":[],"label_agreement":null},{"id":"W58115671","doi":"10.1007/978-3-642-29066-4_16","title":"Measuring Gene Expression Noise in Early Drosophila Embryos: The Highly Dynamic Compartmentalized Micro-environment of the Blastoderm Is One of the Main Sources of Noise","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"British Columbia Institute of Technology","funders":"","keywords":"Blastoderm; Noise (video); Multicellular organism; Gene expression; Biology; Computer science; Gene; Embryo; Cell biology; Genetics; Artificial intelligence; Embryogenesis","score_opus":0.010752752912701754,"score_gpt":0.19849437548690016,"score_spread":0.1877416225741984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W58115671","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":[0.9731004,0.0034603064,0.022608265,0.00019326033,0.00016587478,0.0004161863,0.00002369422,0.0000022661075,0.00002972324],"genre_scores_gemma":[0.9963392,0.00014388029,0.0032172364,0.00012233907,0.00007813739,0.000006085686,0.0000047749245,0.000022804516,0.00006554461],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9979442,0.00011842129,0.00052137853,0.0005109356,0.0006154374,0.00028964435],"domain_scores_gemma":[0.99801284,0.00004854129,0.0005983029,0.0012548442,0.00004168526,0.00004377426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005035675,0.00029383172,0.0004210353,0.000108346576,0.000112792564,0.00001612912,0.0014279247,0.00020628874,0.000009125499],"category_scores_gemma":[0.000011916335,0.00017244046,0.00027453623,0.00018305925,0.0011855495,0.0000070144915,0.0010955529,0.00023737088,7.269983e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002575065,0.000060367536,0.005923043,0.000028492726,0.000046009547,3.8761982e-7,0.00056924584,0.04904249,0.942615,0.000006388178,0.000003065359,0.0016797921],"study_design_scores_gemma":[0.00032556057,0.00005324843,0.021259414,0.00030403092,0.00006570495,0.0000061673727,0.0000016062554,0.0030950115,0.9739981,0.000619839,0.00007556228,0.00019574886],"about_ca_topic_score_codex":0.000023297476,"about_ca_topic_score_gemma":0.00004537763,"teacher_disagreement_score":0.04594748,"about_ca_system_score_codex":0.000083079445,"about_ca_system_score_gemma":0.00009945872,"threshold_uncertainty_score":0.70319176},"labels":[],"label_agreement":null},{"id":"W6243263","doi":"10.5555/1999416.1999480","title":"Applying the TPS method to modeling and simulation of biological systems","year":2010,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Carleton University","funders":"","keywords":"Impulse (physics); Visualization; Biological system; Particle system; Particle (ecology); Computer science; Immersed boundary method; Finite element method; Mechanics; Physics; Boundary (topology); Computer graphics (images); Classical mechanics; Artificial intelligence; Mathematics","score_opus":0.025589927388287415,"score_gpt":0.3003336740355521,"score_spread":0.2747437466472647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6243263","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":[0.60223687,0.00013482945,0.39728916,0.000019300078,0.000026962553,0.00016283992,6.0175495e-7,0.0000033836839,0.0001260453],"genre_scores_gemma":[0.98929524,0.0000072617336,0.010416848,0.000051875217,0.00011194853,0.000043766126,0.000005700095,0.0000051260417,0.00006220307],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99950296,0.00005578781,0.00013258522,0.00016626353,0.000056249522,0.000086159096],"domain_scores_gemma":[0.99964285,0.000024255323,0.00003277443,0.00020642769,0.00005605066,0.000037662583],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039710858,0.00006190122,0.000094118004,0.000019289226,0.000046712303,0.000011135356,0.00008181616,0.00009037914,0.0000045350102],"category_scores_gemma":[0.000031891865,0.000037538317,0.000039118728,0.00006566718,0.00001880909,7.8868396e-7,0.00007563221,0.0000426551,8.686074e-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":[0.0000055868204,0.000002255905,0.00051747734,0.0000020089906,0.000016437043,2.8388515e-8,0.000005833494,0.5432456,0.4532244,0.000096744385,0.000008543418,0.0028750747],"study_design_scores_gemma":[0.00005941119,0.000031837313,0.00015369608,0.0000018152249,0.000017370246,0.0000025444485,0.00008659795,0.9696687,0.026372567,0.000051181283,0.003488226,0.000066050925],"about_ca_topic_score_codex":0.00002243445,"about_ca_topic_score_gemma":0.000013176056,"teacher_disagreement_score":0.4268518,"about_ca_system_score_codex":0.0000012635265,"about_ca_system_score_gemma":0.00000739146,"threshold_uncertainty_score":0.15307681},"labels":[],"label_agreement":null},{"id":"W6901855127","doi":"10.60692/tjee8-r3y22","title":"Collapsing chaos","year":2017,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Victoria; McGill University","funders":"","keywords":"Lyapunov exponent; Trajectory; Control theory (sociology); Function (biology); Plane (geometry); Dynamics (music); Phase plane; Simple (philosophy); Lyapunov function","score_opus":0.020251867081043883,"score_gpt":0.2172734013215661,"score_spread":0.19702153424052224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6901855127","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":[0.9853654,0.0000054981497,0.006126452,0.000031288626,0.0002864799,0.0001279012,0.000016718372,0.000028003451,0.008012243],"genre_scores_gemma":[0.9988034,1.9855165e-7,0.00020229544,0.000057825557,0.00022042354,0.000016024565,0.000020054293,0.0000075776456,0.00067223876],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993247,0.000023560735,0.00024385106,0.000117804586,0.00013001531,0.00016008988],"domain_scores_gemma":[0.9987546,4.4466435e-7,0.0003006474,0.00077386113,0.000108171844,0.00006225971],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018718609,0.00010780597,0.000121586476,0.00005547503,0.0003768354,0.00021910058,0.00024485675,0.000101441634,0.00000786663],"category_scores_gemma":[0.00002115815,0.000096694814,0.000084517174,0.00003095598,0.00003384133,0.000019657708,0.00010954436,0.000027241354,0.00023645056],"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":[0.00013635973,0.0000031738355,0.9789521,0.00031352154,0.0004566928,0.0000051063266,0.010397318,0.0021195328,0.001365961,0.0002000197,0.0033834458,0.0026667772],"study_design_scores_gemma":[0.005071432,0.00026323908,0.741227,0.00031697543,0.00032210394,0.00022991809,0.012317828,0.017609432,0.14384028,0.0000038834337,0.076994464,0.0018034742],"about_ca_topic_score_codex":0.0000028651891,"about_ca_topic_score_gemma":4.0202744e-7,"teacher_disagreement_score":0.23772512,"about_ca_system_score_codex":0.000021551237,"about_ca_system_score_gemma":0.000025688107,"threshold_uncertainty_score":0.39431003},"labels":[],"label_agreement":null},{"id":"W6901991063","doi":"10.6084/m9.figshare.1308791.v2","title":"Regularized Semiparametric Estimation for Ordinary Differential Equations","year":2015,"lang":"en","type":"article","venue":"Figshare","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Ode; Ordinary differential equation; Constant (computer programming); Variation of parameters; Estimation theory; Estimation; Constant coefficients","score_opus":0.050327244360857316,"score_gpt":0.28838623057512325,"score_spread":0.23805898621426594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6901991063","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":[0.4251707,0.009957618,0.32866356,0.0008893141,0.0012004133,0.0059282603,0.22368665,0.0005212196,0.00398227],"genre_scores_gemma":[0.7731187,0.0000010741952,0.0028009026,0.00003935027,0.00028623102,0.00027634588,0.22218618,0.00002216338,0.0012690687],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99929655,0.00003528528,0.00014223794,0.00023808253,0.00012345318,0.0001643767],"domain_scores_gemma":[0.9992826,0.000030095127,0.00008370193,0.00029644673,0.0002028047,0.00010434581],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000051130635,0.00010825312,0.00011541959,0.0000710897,0.0000624666,0.00003069425,0.00013910719,0.00012823765,0.002117175],"category_scores_gemma":[0.0013625246,0.00010915312,0.00012345763,0.00021176077,0.0000053689364,0.000004046873,0.00008019678,0.000033536846,0.00012286345],"study_design_candidate":"not_applicable","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":[0.00008241445,0.000073278665,0.000046624675,0.000053149517,0.00014806411,0.0000010225858,0.000020441892,0.012731502,0.01565663,0.000025270803,0.96497554,0.0061860885],"study_design_scores_gemma":[0.0036983062,0.0007121482,0.0015417329,0.00021314685,0.0002906868,0.000017404182,0.000051817922,0.61262816,0.08578631,0.0007398272,0.29334462,0.0009758122],"about_ca_topic_score_codex":0.000001165246,"about_ca_topic_score_gemma":0.0000034966206,"teacher_disagreement_score":0.6716309,"about_ca_system_score_codex":0.00002194731,"about_ca_system_score_gemma":0.000091652044,"threshold_uncertainty_score":0.99879503},"labels":[],"label_agreement":null},{"id":"W6902273626","doi":"10.6084/m9.figshare.26696337","title":"Additional file 6 of Cell4D: a general purpose spatial stochastic simulator for cellular pathways","year":2024,"lang":"en","type":"article","venue":"Figshare","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"SickKids Foundation; University of Toronto","funders":"","keywords":"General purpose; Saturation (graph theory); Table (database); Lipid microdomain","score_opus":0.01410848696594209,"score_gpt":0.21721441422413,"score_spread":0.2031059272581879,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6902273626","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008005119,0.00056704815,0.00037046164,0.0000055655273,0.000045561017,0.00022346828,0.99784714,0.000022578995,0.00011767129],"genre_scores_gemma":[0.11631796,4.5749056e-7,0.0004990859,0.000031352418,0.00095014833,0.0008014818,0.8797821,0.000037201382,0.0015802125],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99906915,0.00002087627,0.00019582214,0.00035617963,0.00014440602,0.00021353299],"domain_scores_gemma":[0.9992937,0.00016880852,0.00006789065,0.00025823875,0.00012854597,0.00008283757],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000020283498,0.00015805924,0.00015551847,0.000055703465,0.000048178437,0.000026025356,0.00015706412,0.0001504677,0.8924132],"category_scores_gemma":[0.00045007275,0.0001592544,0.00029630837,0.00010735472,0.000011784261,0.0000031515433,0.00009146388,0.00005559698,0.0003606299],"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":[0.000013397599,0.000020467458,1.6418217e-7,0.00011252617,0.000087335626,0.00000385355,0.000005926787,0.0056627453,0.017378842,0.000002752672,0.97544813,0.0012638338],"study_design_scores_gemma":[0.00011365066,0.00011662121,0.00001980301,0.00033246257,0.00003128769,0.0000031775571,0.000004173703,0.0548093,0.022663187,0.000043100725,0.92167693,0.00018632082],"about_ca_topic_score_codex":0.0000013429807,"about_ca_topic_score_gemma":0.000006565971,"teacher_disagreement_score":0.8920526,"about_ca_system_score_codex":0.000014528877,"about_ca_system_score_gemma":0.00019651583,"threshold_uncertainty_score":0.6494206},"labels":[],"label_agreement":null},{"id":"W6902300779","doi":"10.6084/m9.figshare.26696343.v1","title":"Additional file 8 of Cell4D: a general purpose spatial stochastic simulator for cellular pathways","year":2024,"lang":"en","type":"article","venue":"Figshare","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"SickKids Foundation; University of Toronto","funders":"","keywords":"General purpose; Table (database); Key (lock); Class (philosophy)","score_opus":0.014119476393338002,"score_gpt":0.21727345593764016,"score_spread":0.20315397954430217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6902300779","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008089777,0.0005661999,0.0003704457,0.000005569736,0.00004555793,0.00022315484,0.9978406,0.000022429691,0.000117058255],"genre_scores_gemma":[0.116405435,4.527665e-7,0.0004993646,0.000031352945,0.0009496997,0.0008004144,0.87968934,0.000037144764,0.0015867921],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990692,0.000020875828,0.00019581747,0.0003561634,0.00014437598,0.00021353834],"domain_scores_gemma":[0.9992937,0.00016882007,0.000067890796,0.0002582346,0.00012854749,0.000082835315],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000020283036,0.00015806421,0.00015552086,0.000055692486,0.000048185346,0.000026022619,0.00015704733,0.00015046925,0.89327294],"category_scores_gemma":[0.00045009877,0.00015925505,0.0002963116,0.00010728548,0.000011784229,0.0000031511315,0.000091444585,0.00005559588,0.00036278405],"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":[0.000013329304,0.000020365775,1.6341156e-7,0.00011252606,0.000087335284,0.000003855296,0.00000591534,0.0057547395,0.017259078,0.000002711518,0.97545683,0.0012831698],"study_design_scores_gemma":[0.00011357695,0.00011684831,0.000019581857,0.0003327674,0.000031288055,0.0000031803854,0.0000041655053,0.055525683,0.02313481,0.000043097752,0.92048866,0.00018632272],"about_ca_topic_score_codex":0.0000013274022,"about_ca_topic_score_gemma":0.0000064478354,"teacher_disagreement_score":0.8929102,"about_ca_system_score_codex":0.000014549557,"about_ca_system_score_gemma":0.00019656753,"threshold_uncertainty_score":0.6494233},"labels":[],"label_agreement":null},{"id":"W6902413790","doi":"10.6084/m9.figshare.26696343","title":"Additional file 8 of Cell4D: a general purpose spatial stochastic simulator for cellular pathways","year":2024,"lang":"en","type":"article","venue":"Figshare","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"SickKids Foundation; University of Toronto","funders":"","keywords":"General purpose; Table (database); Key (lock); Class (philosophy)","score_opus":0.014119476393338002,"score_gpt":0.21727345593764016,"score_spread":0.20315397954430217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6902413790","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008089777,0.0005661999,0.0003704457,0.000005569736,0.00004555793,0.00022315484,0.9978406,0.000022429691,0.000117058255],"genre_scores_gemma":[0.116405435,4.527665e-7,0.0004993646,0.000031352945,0.0009496997,0.0008004144,0.87968934,0.000037144764,0.0015867921],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990692,0.000020875828,0.00019581747,0.0003561634,0.00014437598,0.00021353834],"domain_scores_gemma":[0.9992937,0.00016882007,0.000067890796,0.0002582346,0.00012854749,0.000082835315],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000020283036,0.00015806421,0.00015552086,0.000055692486,0.000048185346,0.000026022619,0.00015704733,0.00015046925,0.89327294],"category_scores_gemma":[0.00045009877,0.00015925505,0.0002963116,0.00010728548,0.000011784229,0.0000031511315,0.000091444585,0.00005559588,0.00036278405],"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":[0.000013329304,0.000020365775,1.6341156e-7,0.00011252606,0.000087335284,0.000003855296,0.00000591534,0.0057547395,0.017259078,0.000002711518,0.97545683,0.0012831698],"study_design_scores_gemma":[0.00011357695,0.00011684831,0.000019581857,0.0003327674,0.000031288055,0.0000031803854,0.0000041655053,0.055525683,0.02313481,0.000043097752,0.92048866,0.00018632272],"about_ca_topic_score_codex":0.0000013274022,"about_ca_topic_score_gemma":0.0000064478354,"teacher_disagreement_score":0.8929102,"about_ca_system_score_codex":0.000014549557,"about_ca_system_score_gemma":0.00019656753,"threshold_uncertainty_score":0.6494233},"labels":[],"label_agreement":null},{"id":"W6903364672","doi":"10.11575/pplt.v2i.42671","title":"iGEM Team Meetings: Settings for Conversations on Teaching &amp; Learning","year":2017,"lang":"en","type":"article","venue":"University of Calgary","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Subject (documents); Higher education; Enabling; Graduate students","score_opus":0.008910718602625434,"score_gpt":0.2252154560420943,"score_spread":0.21630473743946887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6903364672","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":[0.9626338,0.000046533016,0.014661635,0.00032426327,0.000052335705,0.00013271521,0.000006444449,0.000015516438,0.02212675],"genre_scores_gemma":[0.9864234,0.000018917694,0.004786273,0.000054486056,0.000068452224,2.2644366e-7,0.000093309005,0.000009195309,0.008545795],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99949676,0.00004290443,0.00006428123,0.00019824397,0.00007598566,0.00012181402],"domain_scores_gemma":[0.9993718,0.000020852784,0.00017203476,0.0003227239,0.00006582811,0.00004673194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022645546,0.00007452615,0.00010849582,0.00003700632,0.0006886577,0.000013211977,0.00024155401,0.00008733402,0.000020033864],"category_scores_gemma":[0.00016497151,0.00009145378,0.00013869659,0.0000120773875,0.00009915885,0.000004862098,0.000112836635,0.00008640969,0.000007356235],"study_design_candidate":"not_applicable","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":[0.0010689374,0.00035993155,0.20301694,0.00023754298,0.0016484864,0.000009615708,0.0030125806,0.010076641,0.5731461,0.003663274,0.15352374,0.05023623],"study_design_scores_gemma":[0.0013128765,0.00026097783,0.013889101,0.000060000133,0.00021433302,0.000002557002,0.0010677264,0.0032111583,0.0138135925,0.00008377236,0.965763,0.0003209144],"about_ca_topic_score_codex":0.00007207164,"about_ca_topic_score_gemma":0.000066320645,"teacher_disagreement_score":0.8122392,"about_ca_system_score_codex":0.000012749426,"about_ca_system_score_gemma":0.00003218007,"threshold_uncertainty_score":0.5296668},"labels":[],"label_agreement":null},{"id":"W6926334294","doi":"10.25316/ir-13724","title":"The Nanaimo Free Press [Friday, September 25, 1891]","year":2019,"lang":"en","type":"other","venue":"VIURRSpace (Vancouver Island University)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Free press; Free enterprise; Gloom; George (robot)","score_opus":0.005353205913434684,"score_gpt":0.18798045392006787,"score_spread":0.18262724800663319,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6926334294","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000019117866,0.0031302604,0.0006410245,0.00008139843,0.0010446694,0.0003426277,0.00013069098,0.000056891353,0.9945533],"genre_scores_gemma":[0.001136296,0.0019707156,0.00010270082,0.0000495721,0.0006447184,0.000001857833,0.000005508847,0.00026577295,0.99582285],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99825186,0.0001496404,0.00013023404,0.00069859694,0.00029399636,0.00047567382],"domain_scores_gemma":[0.99774486,0.00002487567,0.0002846557,0.0017365413,0.00008201649,0.00012705587],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009582908,0.0004408142,0.00037104648,0.00017044088,0.00019397489,0.00004911563,0.0010416922,0.0005942549,0.00015874588],"category_scores_gemma":[0.000018267741,0.00036956897,0.00036004547,0.0002601353,0.00017299848,0.0000051569873,0.00059277524,0.00022663982,0.00012725477],"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":[0.00004336313,0.000023477012,0.000008428459,0.000030942967,0.0006707604,0.000020688645,0.000011069115,0.00020983987,0.00018344837,0.00017266611,0.99839455,0.00023077325],"study_design_scores_gemma":[0.0008208079,0.000064889304,0.0000041791973,0.000045345136,0.00028332812,0.000002357462,0.00013521826,0.000045695324,0.0003337142,0.000011122386,0.9977758,0.00047756013],"about_ca_topic_score_codex":0.00020812149,"about_ca_topic_score_gemma":0.009588346,"teacher_disagreement_score":0.009380224,"about_ca_system_score_codex":0.000058464368,"about_ca_system_score_gemma":0.00015260832,"threshold_uncertainty_score":0.9998756},"labels":[],"label_agreement":null},{"id":"W6929548650","doi":"10.5061/dryad.j9kd51cq4","title":"Retrospective data collected on SATURN, a public domain self-administered cognitive screening test","year":2025,"lang":"en","type":"dataset","venue":"Open MIND","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; National Institute on Aging","keywords":"Neurocognitive; Dementia; Cognition; Montreal Cognitive Assessment; Test (biology); Cognitive test; Effects of sleep deprivation on cognitive performance; Cognitive impairment","score_opus":0.03777042894854381,"score_gpt":0.31683233811467076,"score_spread":0.27906190916612694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6929548650","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0031528575,0.0002780166,0.000038785176,0.0001486427,0.00014003665,0.0009862003,0.992902,0.0000030922322,0.0023504011],"genre_scores_gemma":[0.0039193262,0.00016290096,0.0022405188,0.00021858691,0.00034601832,0.00006361595,0.9905405,0.00002382081,0.0024847274],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9963519,0.00032551814,0.00049606274,0.0019364696,0.0003704289,0.00051962904],"domain_scores_gemma":[0.9960767,0.000103227896,0.0004829976,0.0028017175,0.0003340665,0.00020128656],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006178625,0.0005722475,0.0007240398,0.00024174139,0.00031318376,0.00053097546,0.0028042865,0.00074532226,0.00066813605],"category_scores_gemma":[0.00094493246,0.0005859746,0.00016004403,0.0007992809,0.000116945725,0.000012366239,0.0035594362,0.00047837506,0.000055625995],"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":[0.00018563645,0.00030910227,0.00019841666,0.000016634813,0.0013986699,0.00003708846,0.000011106194,0.000001106737,0.00028285108,2.3417893e-7,0.99569035,0.0018687833],"study_design_scores_gemma":[0.0012605555,0.00051900826,0.00035606933,0.00018591371,0.0006907746,0.000016864033,0.00010107297,0.000023836768,0.0012352737,0.0000032967073,0.99498457,0.00062274555],"about_ca_topic_score_codex":0.00003996482,"about_ca_topic_score_gemma":0.0019527752,"teacher_disagreement_score":0.0023614832,"about_ca_system_score_codex":0.000096457596,"about_ca_system_score_gemma":0.0010974993,"threshold_uncertainty_score":0.9996592},"labels":[],"label_agreement":null},{"id":"W6929679987","doi":"10.5061/dryad.ns1rn8pth","title":"Data from: Resource exploitation collapses the home range of an apex predator","year":2021,"lang":"en","type":"dataset","venue":"Open MIND","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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 Alberta; University of Saskatchewan; Alberta Biodiversity Monitoring Institute","funders":"","keywords":"Home range; Resource (disambiguation); Range (aeronautics); Foraging; Productivity; Linear model; Linear density; Resource allocation","score_opus":0.05052304872454031,"score_gpt":0.31212635158718427,"score_spread":0.26160330286264394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6929679987","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07620092,0.0020746377,0.000007730206,0.000039913728,0.00008941764,0.00030290606,0.9212121,3.455548e-7,0.00007205455],"genre_scores_gemma":[0.00095550745,0.0003129727,0.0008908832,0.000054220476,0.0004424004,0.000022456283,0.9966466,0.000021715228,0.00065328815],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99810916,0.00034466534,0.00034110324,0.0007952084,0.00024483033,0.00016503442],"domain_scores_gemma":[0.99581534,0.000040822888,0.00033858806,0.003633353,0.00009811502,0.000073788884],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004417836,0.00022148942,0.00036331225,0.000034260585,0.00008504067,0.00014322586,0.002731863,0.00029510306,0.0013627571],"category_scores_gemma":[0.00010959256,0.0001805801,0.000080944,0.0001699868,0.00009607363,0.000011245229,0.0019114037,0.000113066824,0.000055763627],"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":[0.000071056464,0.00007364453,0.000023347291,0.000010719261,0.00035180777,0.0000061829624,0.000017123826,0.000050396455,0.0032443574,2.1698307e-8,0.9936835,0.0024678328],"study_design_scores_gemma":[0.0003054569,0.000070367605,0.00011014218,0.000035763405,0.00046166842,0.000003255282,0.0003085665,0.000053661555,0.005111757,0.0000021078813,0.9933224,0.0002148818],"about_ca_topic_score_codex":0.000156755,"about_ca_topic_score_gemma":0.0028039697,"teacher_disagreement_score":0.075434476,"about_ca_system_score_codex":0.000010629637,"about_ca_system_score_gemma":0.0002538724,"threshold_uncertainty_score":0.9995501},"labels":[],"label_agreement":null},{"id":"W6929783280","doi":"10.5061/dryad.82gg4","title":"Data from: Modeling of the larval response of green sea urchins to thermal stratification using a random walk approach","year":2013,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Dalhousie University","funders":"","keywords":"Strongylocentrotus droebachiensis; Larva; Stratification (seeds); Random walk; Thermal stratification; Thermal; Horizontal and vertical","score_opus":0.0404069850289701,"score_gpt":0.2705366370944729,"score_spread":0.2301296520655028,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6929783280","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45156884,0.0006093367,0.0020626956,0.000015086707,0.000054997607,0.00029093443,0.5453907,0.000003842258,0.0000035335959],"genre_scores_gemma":[0.23088618,0.00012817884,0.0017295509,0.00005288711,0.00035312265,0.000012642417,0.766787,0.000032894946,0.000017545315],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99629235,0.0012013771,0.0006605525,0.001105912,0.00040815744,0.00033162488],"domain_scores_gemma":[0.99361455,0.00010498926,0.0005512632,0.0055412487,0.000068082096,0.00011985895],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0014090197,0.00038090278,0.00057304645,0.00009533491,0.00025671645,0.000055391167,0.0039700717,0.00019829189,0.0000059028916],"category_scores_gemma":[0.000029807072,0.00029829374,0.00010632252,0.0002621721,0.00011777959,0.000023091838,0.0056998595,0.00030059356,0.0000012253286],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002978671,0.0002528117,0.0011896439,0.00064532,0.0016243337,0.0000021930307,0.0005933548,0.7845417,0.100842714,4.8160314e-7,0.10631757,0.0010111757],"study_design_scores_gemma":[0.00047565997,0.00004596204,0.000904356,0.00019536805,0.0006783958,0.000007753366,0.00022612234,0.98786944,0.00016375238,0.000010037663,0.009099876,0.0003233047],"about_ca_topic_score_codex":0.007299635,"about_ca_topic_score_gemma":0.0031294387,"teacher_disagreement_score":0.22139625,"about_ca_system_score_codex":0.000011410104,"about_ca_system_score_gemma":0.0001691491,"threshold_uncertainty_score":0.9999469},"labels":[],"label_agreement":null},{"id":"W6929791417","doi":"10.5061/dryad.2fqz612qn","title":"Data from: Multi-decadal changes in phytoplankton biomass in northern temperate lakes as seen through the prism of landscape properties","year":2022,"lang":"en","type":"dataset","venue":"Open MIND","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Western University","funders":"","keywords":"Littoral zone; Wetland; Temperate climate; Phytoplankton; Biomass (ecology); Subarctic climate; Sediment; Nutrient","score_opus":0.055832993479300264,"score_gpt":0.3010224289568398,"score_spread":0.24518943547753952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6929791417","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43572158,0.0035710398,6.0955915e-7,0.0001464682,0.00007118182,0.00046093302,0.5599897,4.2114095e-7,0.000038053488],"genre_scores_gemma":[0.02709907,0.0009824221,0.0001114944,0.00004973255,0.00014290286,0.00008128254,0.9709666,0.000026549176,0.00053996185],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99804103,0.00030436678,0.00037710197,0.0007904619,0.00022814599,0.0002589042],"domain_scores_gemma":[0.9978841,0.000018059556,0.00028082338,0.001757597,0.000028831852,0.000030594456],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00043718913,0.00029505414,0.00047139538,0.00007326124,0.00007268039,0.000056182133,0.0024153246,0.00027310324,0.0018863847],"category_scores_gemma":[0.000048098213,0.00021391003,0.000055766784,0.00024308453,0.00009711394,0.000010957563,0.002370963,0.00024757363,0.000028563893],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044476733,0.0005009947,0.019448362,0.000080153295,0.000841305,0.00007471898,0.00055318023,0.00039498514,0.059529316,3.0506406e-8,0.91529775,0.0028344393],"study_design_scores_gemma":[0.0006351013,0.000090087284,0.0008694905,0.000056524157,0.000108509565,0.000004347674,0.00039649507,0.0001050479,0.0164076,0.0000013229876,0.9810291,0.00029635325],"about_ca_topic_score_codex":0.0044900975,"about_ca_topic_score_gemma":0.35234246,"teacher_disagreement_score":0.4109769,"about_ca_system_score_codex":0.000020699337,"about_ca_system_score_gemma":0.0002565331,"threshold_uncertainty_score":0.999026},"labels":[],"label_agreement":null},{"id":"W6929991553","doi":"10.5281/zenodo.10917808","title":"Playful Hybrid Education: Surveys","year":2024,"lang":"en","type":"report","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Bachelor; Perception; Survey data collection; Higher education; Survey research; Survey instrument; Focus group","score_opus":0.029297868292061793,"score_gpt":0.2727024529797656,"score_spread":0.2434045846877038,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6929991553","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025608378,0.013742741,0.00353431,0.0007135803,0.002263638,0.0009856018,0.0015112462,0.00079889933,0.9508416],"genre_scores_gemma":[0.777028,0.004617427,0.0002534936,0.00021177252,0.0050870255,3.9467614e-7,0.087357976,0.007729456,0.11771444],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99698156,0.00062777876,0.00039492978,0.0009106355,0.0006842635,0.00040084528],"domain_scores_gemma":[0.996976,0.000006726521,0.00019236114,0.0010476626,0.0015533462,0.00022389545],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0019708443,0.00031214443,0.0002839121,0.00029751242,0.0007977598,0.00067096035,0.0010962345,0.0002411797,0.0057707257],"category_scores_gemma":[0.0005358087,0.00034152527,0.00023378746,0.00043503195,0.00014617364,0.000007791424,0.0016184567,0.00039617662,0.0061570066],"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":[0.000008626714,0.00007528801,0.000003266804,0.00017182488,0.00029654472,0.000014052409,0.000023452172,0.000060722006,0.0041074413,0.00006728722,0.8802317,0.11493981],"study_design_scores_gemma":[0.000093799965,0.00012428671,0.00013701773,0.00007187778,0.00012191795,0.00045357546,0.000040183902,0.000025833731,0.0020989045,0.00007168012,0.9964153,0.00034560237],"about_ca_topic_score_codex":0.00002849543,"about_ca_topic_score_gemma":0.0000016069025,"teacher_disagreement_score":0.83312714,"about_ca_system_score_codex":0.00023861436,"about_ca_system_score_gemma":0.00014343623,"threshold_uncertainty_score":0.9999037},"labels":[],"label_agreement":null},{"id":"W6930180351","doi":"10.5281/zenodo.10123329","title":"Fig. 30 in A revision of Scipopus Enderlein including the subgenera Scipopus s. str., Phaeopterina Frey and Parascipopus subgen. nov. (Diptera, Micropezidae, Taeniapterinae)","year":2023,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 Guelph","funders":"","keywords":"Subgenus; White (mutation); Sexual behavior; Taxonomy (biology)","score_opus":0.028718256748957137,"score_gpt":0.2593326832266003,"score_spread":0.23061442647764316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6930180351","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":[0.88100654,0.020451032,0.0012610293,0.00068539806,0.00077509903,0.002980276,0.0010936101,0.0010469112,0.09070013],"genre_scores_gemma":[0.9608907,0.006048867,0.00037111266,0.00006725679,0.0005178753,3.5202933e-7,0.001480888,0.006302868,0.024320059],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99733835,0.00046521318,0.00048778165,0.00084305654,0.00038542214,0.0004801483],"domain_scores_gemma":[0.9983752,0.0000112356065,0.00034631346,0.00095835427,0.00016529592,0.00014364897],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008528112,0.00035904942,0.00041540625,0.00044501448,0.0006123656,0.00024712787,0.0010764197,0.00027068608,0.0019513766],"category_scores_gemma":[0.00023286903,0.0003297048,0.00012682317,0.0006669354,0.00032500701,0.000013452362,0.0022060385,0.00027514205,0.00042327566],"study_design_candidate":"not_applicable","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":[0.00024620912,0.00017742203,0.00030261572,0.00044081948,0.0005582164,0.00006265849,0.0005715595,0.00019418458,0.048697196,0.00018545242,0.46564946,0.4829142],"study_design_scores_gemma":[0.0004831901,0.0002654726,0.00032696227,0.00019800373,0.000052144667,0.000054748405,0.000079719466,0.00009473036,0.0022752034,0.000005972772,0.9958348,0.0003290394],"about_ca_topic_score_codex":0.00023622572,"about_ca_topic_score_gemma":0.000080271886,"teacher_disagreement_score":0.53018534,"about_ca_system_score_codex":0.00008229369,"about_ca_system_score_gemma":0.000011769872,"threshold_uncertainty_score":0.9999155},"labels":[],"label_agreement":null},{"id":"W6930589443","doi":"10.5281/zenodo.15218000","title":"FIGURES 91–93 in Revision of the western Nearctic species of Empis subgenus Enoplempis (Diptera: Empididae)","year":2025,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Canadian Food Inspection Agency","funders":"","keywords":"Subgenus; Nearctic ecozone; Terminalia; Taxonomy (biology); Key (lock)","score_opus":0.015603807162468505,"score_gpt":0.23846899599458662,"score_spread":0.22286518883211812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6930589443","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06775516,0.009093809,0.0010146755,0.0008346711,0.00040252565,0.0018125747,0.0011193223,0.00021195032,0.9177553],"genre_scores_gemma":[0.5998802,0.002279883,0.00011136304,0.000098471035,0.0002890688,6.1611814e-8,0.0014702412,0.002361043,0.39350966],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981894,0.00044911957,0.00037487806,0.0004296116,0.00031710393,0.00023987093],"domain_scores_gemma":[0.9984384,0.000009857592,0.00031238399,0.00092085684,0.00026416482,0.00005431854],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00036858677,0.00020135166,0.0003198745,0.00027971156,0.0002029143,0.000064775246,0.0010751616,0.00020331329,0.004977354],"category_scores_gemma":[0.00029777558,0.0001774345,0.00016458717,0.00055285473,0.00025838875,0.0000043085934,0.0012932849,0.00018160944,0.00016237795],"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":[0.0000635596,0.00012999431,0.0005500021,0.0005304715,0.00025937107,0.0000033301299,0.00025920197,0.00014545527,0.022130834,0.000107948734,0.9586011,0.017218705],"study_design_scores_gemma":[0.0002684754,0.000100109006,0.0021932302,0.00030351031,0.000050106304,0.0000054449,0.000055345452,0.000012769546,0.0066244495,0.000008831243,0.99023086,0.0001468476],"about_ca_topic_score_codex":0.0000851729,"about_ca_topic_score_gemma":0.000020360296,"teacher_disagreement_score":0.53212506,"about_ca_system_score_codex":0.00004227173,"about_ca_system_score_gemma":0.000017915407,"threshold_uncertainty_score":0.9959322},"labels":[],"label_agreement":null},{"id":"W6931010656","doi":"10.5281/zenodo.15109070","title":"SwanHubX/SwanLab: v0.5.4","year":2025,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Xanadu Quantum Technologies (Canada)","funders":"","keywords":"Callback; Feature (linguistics); Architecture; Frame (networking)","score_opus":0.01273637549978748,"score_gpt":0.2294286627709774,"score_spread":0.21669228727118992,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931010656","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00012752373,0.001821345,0.0033481724,0.00022580108,0.00012781296,0.00032335936,0.0004165846,0.00044059238,0.99316883],"genre_scores_gemma":[0.010754845,0.00089718285,0.0004147676,0.00023147496,0.0009396799,6.933545e-8,0.010035867,0.0077928216,0.9689333],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982723,0.00025443968,0.00020932907,0.00064976636,0.00026338,0.00035077418],"domain_scores_gemma":[0.9986563,0.000003251144,0.00014811478,0.0007719489,0.00028216405,0.00013825668],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00027901478,0.00024844517,0.00022802837,0.00028858669,0.0006161764,0.00024910914,0.0010617118,0.00029564256,0.02298703],"category_scores_gemma":[0.00020177422,0.0002758649,0.00014224266,0.00038573836,0.00013891129,0.0000030071744,0.0013528786,0.00019612591,0.004650118],"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":[0.000017094533,0.000044380235,0.0000012067994,0.00005833599,0.00023857216,0.000004426957,0.000017011107,0.00003162528,0.006635959,0.00033333045,0.9695894,0.023028646],"study_design_scores_gemma":[0.00025903873,0.000090302936,0.0000312189,0.000048929232,0.00006315132,0.000014542656,0.00002374084,0.000026367852,0.00082369463,0.000027856942,0.9983327,0.00025847726],"about_ca_topic_score_codex":0.000021114498,"about_ca_topic_score_gemma":0.0000023937585,"teacher_disagreement_score":0.028743267,"about_ca_system_score_codex":0.000049402854,"about_ca_system_score_gemma":0.000012425796,"threshold_uncertainty_score":0.99996936},"labels":[],"label_agreement":null},{"id":"W6931862734","doi":"10.5281/zenodo.7384968","title":"Tanytarsus oscillans Johannsen 1932","year":2022,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Holotype; Taxonomy (biology); DNA; DNA sequencing","score_opus":0.017670290463648337,"score_gpt":0.22332217170461954,"score_spread":0.2056518812409712,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931862734","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":[0.85515434,0.0011118597,0.0039217845,0.001435219,0.0003574092,0.0006636099,0.0005641119,0.0005670976,0.13622458],"genre_scores_gemma":[0.9928358,0.00006508589,0.00012353784,0.00020092112,0.00021927709,9.189629e-8,0.002868979,0.0007498532,0.0029364051],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.998435,0.0003670517,0.0001658497,0.00041767533,0.00031215916,0.00030224075],"domain_scores_gemma":[0.99907863,0.0000037432224,0.000074245734,0.000532211,0.00018848397,0.00012269487],"candidate_categories":["sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00049760286,0.00011387059,0.00010366086,0.00011217391,0.002269845,0.00015623945,0.0008126736,0.000041462106,0.008745301],"category_scores_gemma":[0.00011555052,0.00013303866,0.000086217915,0.00040857104,0.000083888255,0.000004953854,0.0017911708,0.00015255544,0.00083288935],"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":[0.00016838667,0.00018424998,0.000052687992,0.000021643753,0.0002339389,0.000023850958,0.00036475871,0.0060932087,0.2495032,0.00077588414,0.70322526,0.039352916],"study_design_scores_gemma":[0.00029670537,0.00026912976,0.00029146986,0.0000015078689,0.00001794929,0.000108622706,0.00022896192,0.00031675363,0.0024838536,0.000050153874,0.99577844,0.00015647028],"about_ca_topic_score_codex":0.0000069743405,"about_ca_topic_score_gemma":5.7554115e-7,"teacher_disagreement_score":0.29255316,"about_ca_system_score_codex":0.00007544278,"about_ca_system_score_gemma":0.000005391726,"threshold_uncertainty_score":0.9999451},"labels":[],"label_agreement":null},{"id":"W6958358450","doi":"10.6084/m9.figshare.26696337.v1","title":"Additional file 6 of Cell4D: a general purpose spatial stochastic simulator for cellular pathways","year":2024,"lang":"en","type":"article","venue":"Figshare","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"SickKids Foundation; University of Toronto","funders":"","keywords":"General purpose; Saturation (graph theory); Table (database); Lipid microdomain","score_opus":0.01410848696594209,"score_gpt":0.21721441422413,"score_spread":0.2031059272581879,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6958358450","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008005119,0.00056704815,0.00037046164,0.0000055655273,0.000045561017,0.00022346828,0.99784714,0.000022578995,0.00011767129],"genre_scores_gemma":[0.11631796,4.5749056e-7,0.0004990859,0.000031352418,0.00095014833,0.0008014818,0.8797821,0.000037201382,0.0015802125],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99906915,0.00002087627,0.00019582214,0.00035617963,0.00014440602,0.00021353299],"domain_scores_gemma":[0.9992937,0.00016880852,0.00006789065,0.00025823875,0.00012854597,0.00008283757],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000020283498,0.00015805924,0.00015551847,0.000055703465,0.000048178437,0.000026025356,0.00015706412,0.0001504677,0.8924132],"category_scores_gemma":[0.00045007275,0.0001592544,0.00029630837,0.00010735472,0.000011784261,0.0000031515433,0.00009146388,0.00005559698,0.0003606299],"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":[0.000013397599,0.000020467458,1.6418217e-7,0.00011252617,0.000087335626,0.00000385355,0.000005926787,0.0056627453,0.017378842,0.000002752672,0.97544813,0.0012638338],"study_design_scores_gemma":[0.00011365066,0.00011662121,0.00001980301,0.00033246257,0.00003128769,0.0000031775571,0.000004173703,0.0548093,0.022663187,0.000043100725,0.92167693,0.00018632082],"about_ca_topic_score_codex":0.0000013429807,"about_ca_topic_score_gemma":0.000006565971,"teacher_disagreement_score":0.8920526,"about_ca_system_score_codex":0.000014528877,"about_ca_system_score_gemma":0.00019651583,"threshold_uncertainty_score":0.6494206},"labels":[],"label_agreement":null},{"id":"W6960658332","doi":"10.14288/1.0115730","title":"[Meeting minutes of the Senate of The University of British Columbia]","year":2015,"lang":"en","type":"article","venue":"Open Collections","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Work (physics); Agency (philosophy); Legislation","score_opus":0.010260203907478891,"score_gpt":0.19427125700310863,"score_spread":0.18401105309562973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6960658332","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":[0.9753414,0.00020998335,0.000029381847,0.000058057354,0.00008863973,0.00020096634,0.00008627987,0.0000013245815,0.023983974],"genre_scores_gemma":[0.8626694,0.00001865284,0.00015598498,0.0000074884874,0.000012964692,7.584463e-7,0.0000019955994,0.0000036415072,0.13712908],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99957424,0.000094198,0.00009834278,0.00009614293,0.00007840501,0.000058685586],"domain_scores_gemma":[0.999379,0.0000062277427,0.00013469168,0.00027148981,0.00018750152,0.00002111915],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014524962,0.00002829378,0.00009455714,0.000004988002,0.00027794522,0.000021862927,0.00035807438,0.000042949287,0.000026080572],"category_scores_gemma":[0.000046888068,0.00003170033,0.000101124235,0.00046623396,0.00012915539,0.0000020016887,0.00035798314,0.000028155617,1.2841993e-7],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018086184,0.000118344455,0.01858961,0.000014075268,0.00025101568,3.0272665e-7,0.000084368294,0.0036183507,0.06586629,0.0000015122821,0.91119134,0.00024669454],"study_design_scores_gemma":[0.003704777,0.00040207108,0.07701954,0.00040153007,0.0009998123,0.0000776862,0.0073025296,0.0018850006,0.47459173,0.0007465635,0.4323045,0.0005642541],"about_ca_topic_score_codex":0.052720997,"about_ca_topic_score_gemma":0.21795015,"teacher_disagreement_score":0.47888684,"about_ca_system_score_codex":0.000011639576,"about_ca_system_score_gemma":0.00018992185,"threshold_uncertainty_score":0.953587},"labels":[],"label_agreement":null},{"id":"W6961118167","doi":"10.14288/1.0155055","title":"View of Vancouver School of Theology","year":2004,"lang":"en","type":"other","venue":"Open Collections","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Field (mathematics); Context (archaeology); Key (lock); Perspective (graphical)","score_opus":0.006788223265918455,"score_gpt":0.24337782201414526,"score_spread":0.2365895987482268,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6961118167","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00002290607,0.0021304416,0.00069623376,0.0000070767333,0.0002485947,0.00040067625,0.00006655962,0.0000062009726,0.99642134],"genre_scores_gemma":[0.001517238,0.0007760357,0.0012717629,0.000029925402,0.00014525793,0.000048914528,0.00005341174,0.00012132033,0.9960361],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99922895,0.000067334084,0.00023324779,0.0002705781,0.00007831383,0.00012157967],"domain_scores_gemma":[0.9990442,0.0000048747706,0.0002780126,0.00054661,0.000076841745,0.000049462407],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000082739694,0.00014792902,0.0003822039,0.000088260575,0.00009824136,0.000018323552,0.00038372597,0.00029994745,0.007971735],"category_scores_gemma":[0.000027211945,0.0001448028,0.00016711181,0.0004423694,0.00010839225,9.408041e-7,0.00022012042,0.0000664616,0.000009530079],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001441934,0.0000688237,0.0000396789,0.000033271015,0.0004870835,3.8674233e-7,0.0000015884146,0.0002827183,0.0015747148,0.000020108879,0.99736756,0.00010965781],"study_design_scores_gemma":[0.00040006518,0.00013121059,0.000016783926,0.00007750017,0.00017326724,0.0000033992299,0.0000138860305,0.0000029075454,0.0061543803,0.00030162022,0.99257535,0.00014960332],"about_ca_topic_score_codex":0.0029133006,"about_ca_topic_score_gemma":0.025471672,"teacher_disagreement_score":0.02255837,"about_ca_system_score_codex":0.000020163588,"about_ca_system_score_gemma":0.0004422084,"threshold_uncertainty_score":0.9929351},"labels":[],"label_agreement":null},{"id":"W6961974647","doi":"10.15468/dl.bw8zkh","title":"Occurrence Download","year":2024,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Alien; Range (aeronautics); State (computer science)","score_opus":0.007976846531990657,"score_gpt":0.21249095636297838,"score_spread":0.20451410983098772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6961974647","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020587908,0.000268494,0.000005572068,0.00007070324,0.00049688,0.00016732802,0.9968339,0.000032226922,0.000066062676],"genre_scores_gemma":[0.00011176872,0.00023038365,0.0000014423235,0.00028671412,0.000008037008,0.0000038245817,0.99935716,2.9031233e-8,6.132767e-7],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987088,0.000053241518,0.00031677313,0.00033408176,0.00032156555,0.00026556064],"domain_scores_gemma":[0.9988413,0.0000026899438,0.00016338924,0.00067195226,0.0001797966,0.00014087425],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00019771524,0.0002944856,0.00022692508,0.0000705263,0.0001367199,0.000119838754,0.00045208322,0.0004886659,0.0005046982],"category_scores_gemma":[0.000052562787,0.00030204057,0.00028797754,0.00027241217,0.00013470634,0.000018943632,0.0005101571,0.0001824068,0.24568386],"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":[0.000030695046,0.000015702273,0.0004322935,0.00013199059,0.00014738835,0.0000016911912,0.000005201542,0.00007220563,0.0000024716385,1.7862927e-8,0.9985626,0.0005977614],"study_design_scores_gemma":[0.00013376607,0.00004295525,0.000025526862,0.0000023592202,0.0001719181,0.0000067219744,0.00003607986,3.547014e-7,0.000050917184,5.9347985e-7,0.9992339,0.000294902],"about_ca_topic_score_codex":0.000063404004,"about_ca_topic_score_gemma":0.000027384034,"teacher_disagreement_score":0.24517916,"about_ca_system_score_codex":0.00010586182,"about_ca_system_score_gemma":0.00017173045,"threshold_uncertainty_score":0.9999432},"labels":[],"label_agreement":null},{"id":"W6962105353","doi":"10.15468/dl.tdanz3","title":"Occurrence Download","year":2023,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); Identification (biology); Sequence (biology)","score_opus":0.010643367697043384,"score_gpt":0.21708617247000508,"score_spread":0.2064428047729617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6962105353","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027018639,0.00005225248,0.000007057431,0.000056028483,0.00041391188,0.00018010184,0.9965199,0.00004437433,0.000024498353],"genre_scores_gemma":[0.000037733324,0.00023020667,0.0000011604748,0.00023886291,0.000006625186,0.000004533011,0.99947995,3.3449492e-8,8.718897e-7],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986423,0.00006669328,0.00032693316,0.0003107233,0.00035206764,0.0003012538],"domain_scores_gemma":[0.99865484,0.0000045302236,0.00024511066,0.0007266179,0.0002211838,0.00014772256],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00023917599,0.00027932914,0.0002404157,0.00007317606,0.0001935807,0.00007386356,0.0005105271,0.00049351424,0.00016153489],"category_scores_gemma":[0.00010712347,0.00030251883,0.0002579126,0.00034527047,0.00013368357,0.00001882554,0.0005098125,0.00014325442,0.21326162],"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":[0.000034495726,0.000015392056,0.0008431029,0.00006369869,0.00011571391,0.0000012055348,0.0000036100464,0.00015605555,0.0000020751947,9.257755e-9,0.9983139,0.0004507491],"study_design_scores_gemma":[0.0002081702,0.000041875664,0.00016256746,0.0000013753921,0.000094180665,0.000003010841,0.000041451156,2.9401906e-7,0.000033777644,3.0020018e-7,0.999119,0.00029399674],"about_ca_topic_score_codex":0.00022260963,"about_ca_topic_score_gemma":0.00006120878,"teacher_disagreement_score":0.21310009,"about_ca_system_score_codex":0.00009465237,"about_ca_system_score_gemma":0.00014803499,"threshold_uncertainty_score":0.9999427},"labels":[],"label_agreement":null},{"id":"W6976903724","doi":"10.6068/dp14ba88dbeef22","title":"Trend 2007 - 2012. Statistics Canada. CANSIM: Labor - Wages, Salaries and Other Earnings | Country: Canada | Table: Labour statistics consistent with the System of National Accounts (SNA), by province and territory, job category and North American Industry Classification System (NAICS) | Variable: Data processing, hosting, and related services, Total number of jobs | Units: , 2007-2012. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-145.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Earnings; Economic statistics; Census; Official statistics; Summary statistics; Wages and salaries; National accounts; Socioeconomic status; Statistics education; Population statistics","score_opus":0.009854798299744167,"score_gpt":0.21938179866435212,"score_spread":0.20952700036460795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6976903724","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00033261243,0.007495381,0.00001259439,0.0000030313893,0.00009417056,0.0003940847,0.9914108,0.000014950923,0.00024241052],"genre_scores_gemma":[0.0036066573,0.00044166914,0.00022948065,0.00006728346,0.00010547519,0.000010069068,0.9938684,0.00011843927,0.0015525264],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9970043,0.0002858488,0.0006540549,0.0009481021,0.0007351062,0.0003726437],"domain_scores_gemma":[0.9965216,0.00014535557,0.0014563485,0.0013224259,0.00028200523,0.0002722756],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005280736,0.00048795444,0.00071289047,0.000040067975,0.00016119346,0.00015957508,0.0007547928,0.00034707185,0.000056925197],"category_scores_gemma":[0.000035473644,0.00040023582,1.9096309e-7,0.0001912799,0.00068864226,0.000059111087,0.0005724253,0.0004530569,4.4862173e-7],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008110919,0.000022656877,0.0061931745,0.002148978,0.0005601093,0.000026150436,0.0000041991775,0.00001888999,0.000015410218,0.00012266602,0.9907387,0.000067969006],"study_design_scores_gemma":[0.0004898586,0.000061752624,0.0006116068,0.00010575918,0.00063538057,0.00031804322,0.0009969597,0.004706363,1.2296e-7,2.265726e-8,0.99164015,0.0004340067],"about_ca_topic_score_codex":0.9859464,"about_ca_topic_score_gemma":0.98154676,"teacher_disagreement_score":0.007053712,"about_ca_system_score_codex":0.00008827146,"about_ca_system_score_gemma":0.0069468934,"threshold_uncertainty_score":0.99984497},"labels":[],"label_agreement":null},{"id":"W6977215812","doi":"10.6084/m9.figshare.1308791.v3","title":"Regularized Semiparametric Estimation for Ordinary Differential Equations","year":2015,"lang":"en","type":"article","venue":"Figshare","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Ode; Ordinary differential equation; Constant (computer programming); Variation of parameters; Estimation theory; Estimation; Constant coefficients","score_opus":0.050327244360857316,"score_gpt":0.28838623057512325,"score_spread":0.23805898621426594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6977215812","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":[0.4251707,0.009957618,0.32866356,0.0008893141,0.0012004133,0.0059282603,0.22368665,0.0005212196,0.00398227],"genre_scores_gemma":[0.7731187,0.0000010741952,0.0028009026,0.00003935027,0.00028623102,0.00027634588,0.22218618,0.00002216338,0.0012690687],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99929655,0.00003528528,0.00014223794,0.00023808253,0.00012345318,0.0001643767],"domain_scores_gemma":[0.9992826,0.000030095127,0.00008370193,0.00029644673,0.0002028047,0.00010434581],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000051130635,0.00010825312,0.00011541959,0.0000710897,0.0000624666,0.00003069425,0.00013910719,0.00012823765,0.002117175],"category_scores_gemma":[0.0013625246,0.00010915312,0.00012345763,0.00021176077,0.0000053689364,0.000004046873,0.00008019678,0.000033536846,0.00012286345],"study_design_candidate":"not_applicable","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":[0.00008241445,0.000073278665,0.000046624675,0.000053149517,0.00014806411,0.0000010225858,0.000020441892,0.012731502,0.01565663,0.000025270803,0.96497554,0.0061860885],"study_design_scores_gemma":[0.0036983062,0.0007121482,0.0015417329,0.00021314685,0.0002906868,0.000017404182,0.000051817922,0.61262816,0.08578631,0.0007398272,0.29334462,0.0009758122],"about_ca_topic_score_codex":0.000001165246,"about_ca_topic_score_gemma":0.0000034966206,"teacher_disagreement_score":0.6716309,"about_ca_system_score_codex":0.00002194731,"about_ca_system_score_gemma":0.000091652044,"threshold_uncertainty_score":0.99879503},"labels":[],"label_agreement":null},{"id":"W6977650023","doi":"10.6084/m9.figshare.19350021.v1","title":"Additional file 4 of The cellular response to drug perturbation is limited: comparison of large-scale chemogenomic fitness signatures","year":2022,"lang":"en","type":"article","venue":"Figshare","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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 British Columbia","funders":"","keywords":"Drug; Drug discovery; Pattern recognition (psychology); Drug response; Gene","score_opus":0.009719225456762112,"score_gpt":0.22587827752506678,"score_spread":0.21615905206830466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6977650023","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.088861674,0.0003080308,9.4696236e-7,0.00009567322,0.000017475706,0.00013299895,0.9104791,0.0000039426527,0.00010011163],"genre_scores_gemma":[0.485541,1.7095566e-7,0.0000748883,0.00016845168,0.00005118734,0.00021764605,0.5114684,0.000011758883,0.0024665375],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99905246,0.00015154679,0.0001965069,0.00022754478,0.00023913522,0.00013278105],"domain_scores_gemma":[0.99911624,0.00013792385,0.00019376236,0.00039216198,0.000120285644,0.000039628067],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000060764327,0.000100235644,0.00014651743,0.00004629077,0.00013534869,0.0000050593885,0.0003365803,0.00006359217,0.8813525],"category_scores_gemma":[0.00041064317,0.00009236788,0.00018764847,0.00024685424,0.000009791917,0.0000017377283,0.00038803733,0.00009383022,0.00003739404],"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":[0.000094056704,0.00005672478,0.00001624462,0.000016809374,0.00003463156,2.0708663e-7,0.00016384017,0.005087745,0.07663562,1.7038123e-7,0.9178342,0.000059715436],"study_design_scores_gemma":[0.00009379558,0.00005245469,0.0017417407,0.00005939639,0.00001232279,6.013937e-7,0.00020045658,0.001393059,0.20932287,0.000003461736,0.7870251,0.000094717434],"about_ca_topic_score_codex":8.383316e-7,"about_ca_topic_score_gemma":0.0000074545915,"teacher_disagreement_score":0.8813151,"about_ca_system_score_codex":0.000024598734,"about_ca_system_score_gemma":0.00011090484,"threshold_uncertainty_score":0.3766653},"labels":[],"label_agreement":null},{"id":"W6980959027","doi":"","title":"Decoding cytokine dynamics with biochemical networks","year":2020,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"McGill University","funders":"","keywords":"Interpretability; Context (archaeology); Cytokine; Decoding methods; ENCODE; Immune system; Ligand (biochemistry); Simple (philosophy)","score_opus":0.007084400969554736,"score_gpt":0.2154041703113927,"score_spread":0.20831976934183796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6980959027","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":[0.98519665,0.0010843319,0.00002980525,0.000024631341,0.0004684675,0.0004763742,0.00040384303,0.00012884676,0.012187061],"genre_scores_gemma":[0.97968084,0.0006417639,0.0015501489,0.00027899267,0.00031535537,0.000090609785,0.014375542,0.00035653258,0.0027102337],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9957584,0.00020802928,0.0007866852,0.0017520073,0.00061433564,0.00088051194],"domain_scores_gemma":[0.9973349,0.000038924005,0.0006094267,0.0010843135,0.0003863747,0.0005460812],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00033053305,0.0010274341,0.0008975617,0.00018804413,0.00060654903,0.0000848718,0.00085411896,0.0014541638,0.00007254442],"category_scores_gemma":[0.0001973935,0.0010461459,0.00057088543,0.00072489394,0.00009363782,0.000019465835,0.0002500152,0.001187948,0.000050359402],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024506948,0.00038965026,0.00066725345,0.0005930424,0.0042322576,0.0002731069,0.0000052727246,0.008385329,0.8865871,0.00943489,0.0002529542,0.08672844],"study_design_scores_gemma":[0.0028008397,0.0011423688,0.0010058612,0.00065780414,0.002599558,0.00018047534,0.00032584605,0.011402503,0.8792513,0.001080967,0.094639644,0.0049128165],"about_ca_topic_score_codex":0.000029641076,"about_ca_topic_score_gemma":0.0011250427,"teacher_disagreement_score":0.09438669,"about_ca_system_score_codex":0.00033514982,"about_ca_system_score_gemma":0.00009442398,"threshold_uncertainty_score":0.99984217},"labels":[],"label_agreement":null},{"id":"W6990501922","doi":"","title":"Dynamics of a state-dependent delay model of repressible and inducible operons","year":2020,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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","keywords":"Hopf bifurcation; Dynamics (music); Steady state (chemistry); Stability (learning theory); Control theory (sociology); Constant (computer programming); Variable (mathematics); Operon","score_opus":0.013555610350726081,"score_gpt":0.2364367120567904,"score_spread":0.22288110170606432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6990501922","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":[0.9910115,0.0011122699,0.000010602617,0.000009196728,0.000116965064,0.00034491793,0.0013168207,0.000021473807,0.006056246],"genre_scores_gemma":[0.9913761,0.0012180546,0.0014989093,0.000036202422,0.000017944083,0.000041094256,0.0021510557,0.00014023304,0.0035204138],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9969454,0.00018049304,0.0009078474,0.0010913219,0.0004886469,0.00038633085],"domain_scores_gemma":[0.99754226,0.000022686178,0.00079119415,0.0009679004,0.00042403935,0.00025190238],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00042613235,0.00051783654,0.0008157378,0.00020277828,0.00019690051,0.0000202303,0.00052278663,0.000723029,0.00002209734],"category_scores_gemma":[0.00019227495,0.00056585245,0.00033652945,0.00031292744,0.00008567348,0.000020588192,0.00030787947,0.00050431315,0.0000041594853],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003589582,0.00015523462,0.00019932796,0.00049877184,0.00089572254,0.000008605371,0.0000123940945,0.018032394,0.9630538,0.002769873,0.0000064126066,0.014008478],"study_design_scores_gemma":[0.0007138663,0.0002802925,0.00016309229,0.00017339164,0.0005603102,0.000009590353,0.00019830937,0.008520362,0.9845242,0.0036238376,0.00055233797,0.00068039563],"about_ca_topic_score_codex":0.00013236268,"about_ca_topic_score_gemma":0.0018321903,"teacher_disagreement_score":0.021470388,"about_ca_system_score_codex":0.000096253454,"about_ca_system_score_gemma":0.00014173528,"threshold_uncertainty_score":0.99967927},"labels":[],"label_agreement":null},{"id":"W6995835599","doi":"","title":"PMC Film Canada Inc v. Shintech Inc","year":2008,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"","score_opus":0.006380502483774717,"score_gpt":0.19426295245529843,"score_spread":0.1878824499715237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6995835599","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":[0.99119335,0.00060060224,0.00047676507,0.00016885178,0.00008797713,0.000052759995,0.00000725862,0.000013838889,0.0073986156],"genre_scores_gemma":[0.9917341,0.00015127368,0.0006240728,0.00047283084,0.00017758762,0.0000059577615,0.00010114521,0.000015551279,0.0067175124],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991734,0.000029028828,0.00015420596,0.00026491808,0.00015471915,0.00022375368],"domain_scores_gemma":[0.9994055,0.000004918382,0.00003940374,0.00039042704,0.000055002965,0.0001047596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000047872418,0.00012527633,0.00012400214,0.000022847926,0.00010258537,0.0000054976936,0.00019133891,0.000095586714,0.00021952296],"category_scores_gemma":[0.000021585927,0.00011352079,0.000059133206,0.00010864819,0.0000503148,0.0000011349445,0.000111029476,0.000057315836,0.00001383341],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042809963,0.00007589915,0.11926568,0.000015226648,0.00042098848,0.000082929255,0.000047291174,0.0028303652,0.481312,0.00008284634,0.39399704,0.0018269066],"study_design_scores_gemma":[0.0003404277,0.00008005938,0.021157393,0.0000036052388,0.00003469864,0.00010506247,0.00010175533,0.0005290493,0.6557763,0.000016956912,0.32143056,0.00042413233],"about_ca_topic_score_codex":0.07821937,"about_ca_topic_score_gemma":0.40236208,"teacher_disagreement_score":0.3241427,"about_ca_system_score_codex":0.000018000355,"about_ca_system_score_gemma":0.0003926525,"threshold_uncertainty_score":0.92791885},"labels":[],"label_agreement":null},{"id":"W6996431511","doi":"","title":"Rural region community cooperation, a Fast Track vocational technical education programme","year":2000,"lang":"en","type":"dissertation","venue":"The Atrium (University of Guelph)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Vocational education; Economic shortage; Position (finance); Rural area; Production (economics); Remedial education; Training (meteorology)","score_opus":0.011283181476662392,"score_gpt":0.23065834635857713,"score_spread":0.21937516488191475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6996431511","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":[0.9949929,0.000892393,0.00027394935,0.0004454484,0.000117235926,0.00037413777,0.000014180697,0.000023254217,0.0028664607],"genre_scores_gemma":[0.97683305,0.0004391705,0.00024309041,0.000037296893,0.00019214457,0.000002711973,0.0076551978,0.000020828014,0.0145765245],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99895316,0.00028143817,0.0001831674,0.0002106456,0.00019347729,0.00017808695],"domain_scores_gemma":[0.998581,0.000017136,0.0002688415,0.0006826087,0.00038244043,0.00006796549],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002492737,0.00019193298,0.00022272582,0.00009194987,0.0004885861,0.000018764522,0.00062365964,0.00036389366,0.000071551236],"category_scores_gemma":[0.000024604284,0.00019936418,0.0002510809,0.0002900982,0.00017141379,0.000009549029,0.00005690864,0.0003129422,0.000017845243],"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":[0.002682793,0.0016587886,0.0012482037,0.00036107763,0.0010563277,0.0000036322645,0.003739566,0.0014064211,0.75159067,0.00083017483,0.077686325,0.15773602],"study_design_scores_gemma":[0.0023096204,0.0011835826,0.78858936,0.00038985646,0.0028872893,0.000150622,0.05816007,0.00048506522,0.00970405,0.00090856,0.13328782,0.0019441023],"about_ca_topic_score_codex":0.00046297637,"about_ca_topic_score_gemma":0.002915877,"teacher_disagreement_score":0.7873412,"about_ca_system_score_codex":0.00005541729,"about_ca_system_score_gemma":0.00057172746,"threshold_uncertainty_score":0.8129835},"labels":[],"label_agreement":null},{"id":"W7000189877","doi":"","title":"Enhancing the Robustness of Random Boolean Networks by Epigenetic Regulation","year":2025,"lang":"en","type":"article","venue":"Cronfa (Swansea University)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Guangxi Normal University; Natural Science Foundation of Guangxi Province; National Natural Science Foundation of China; British Columbia Innovation Council","keywords":"Nucleofection; Gestational period; TSG101; Dysgeusia; Liquation; Diafiltration; Emperipolesis; Triacetin; Hemopericardium","score_opus":0.0031867794026049262,"score_gpt":0.18402570195701964,"score_spread":0.18083892255441472,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7000189877","genre_codex":"methods","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":[0.4844724,0.0020301484,0.5102001,0.000176318,0.0001522332,0.00020091186,0.000005465602,0.000014113291,0.0027483234],"genre_scores_gemma":[0.98409164,0.00022646417,0.00015163278,0.00004147791,0.00007800196,8.701145e-7,0.0000712697,0.000010971733,0.015327685],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990507,0.00016396247,0.00018297101,0.00029107844,0.00010083601,0.00021048191],"domain_scores_gemma":[0.99920815,0.000032731496,0.000116569114,0.00047792605,0.00011859906,0.000046019108],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021597098,0.00013772922,0.0001863197,0.00010003321,0.00020597473,0.000015383534,0.00034261728,0.00014971072,0.000027589635],"category_scores_gemma":[0.000019430838,0.0001288995,0.00016815048,0.00049076154,0.00018899533,0.000004807602,0.00012874322,0.00007788055,8.352243e-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":[0.0005969336,0.00008994396,0.0029705355,0.000054789714,0.0006839841,0.0000033806139,0.000061301704,0.50158376,0.46643808,0.0006765605,0.0212763,0.005564428],"study_design_scores_gemma":[0.003941912,0.00016173717,0.0062506995,0.00011052705,0.00093967136,0.000004012143,0.00092565553,0.037382487,0.67373794,0.00008065318,0.27583998,0.0006246997],"about_ca_topic_score_codex":0.000017254362,"about_ca_topic_score_gemma":0.00012153207,"teacher_disagreement_score":0.51004845,"about_ca_system_score_codex":0.000032873042,"about_ca_system_score_gemma":0.0001036124,"threshold_uncertainty_score":0.52563685},"labels":[],"label_agreement":null},{"id":"W70003281","doi":"10.1007/978-1-61779-400-1_12","title":"Modeling Gene Regulation Networks Using Ordinary Differential Equations","year":2011,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":56,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"National Institute of General Medical Sciences","keywords":"Ode; Ordinary differential equation; Gene regulatory network; Computer science; Consistency (knowledge bases); Mathematics; Differential equation; Applied mathematics; Gene; Gene expression; Biology; Artificial intelligence; Genetics; Mathematical analysis","score_opus":0.05493735865243428,"score_gpt":0.3591306175589689,"score_spread":0.30419325890653465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W70003281","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":[0.28637192,0.0010424602,0.71215576,0.0000054760876,0.0001780271,0.00012646722,0.000001599373,0.000012976398,0.0001053409],"genre_scores_gemma":[0.5289097,0.00003294045,0.47070697,0.000046060923,0.00011622224,0.000016606267,0.00011694679,0.000027554323,0.0000270349],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973331,0.0011296524,0.0004459405,0.00059985544,0.000070983,0.0004204589],"domain_scores_gemma":[0.9991017,0.000020184683,0.00011209804,0.00059719966,0.00008864304,0.00008019996],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00067849405,0.00024334043,0.00030706104,0.00019329462,0.000088475856,0.00001011495,0.00026579385,0.00042857378,0.00006176936],"category_scores_gemma":[0.000117802214,0.00025387853,0.0001986178,0.0003257721,0.00010074209,0.000004007138,0.0002352812,0.00015393615,0.0000015813032],"study_design_candidate":"simulation_or_modeling","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":[0.000039312294,0.000041184067,0.0008775265,0.0000026028968,0.00008760076,0.000003675626,0.000021329335,0.22348185,0.77191705,0.0004929643,0.0000024483543,0.0030324764],"study_design_scores_gemma":[0.00031074512,0.00009372858,0.00030600323,0.000006667443,0.000087118155,0.000013747051,0.000014083925,0.82684374,0.16946581,0.0025153458,0.000059650185,0.00028335664],"about_ca_topic_score_codex":0.00009303886,"about_ca_topic_score_gemma":0.000027243243,"teacher_disagreement_score":0.6033619,"about_ca_system_score_codex":0.00003625769,"about_ca_system_score_gemma":0.00004485935,"threshold_uncertainty_score":0.99999136},"labels":[],"label_agreement":null},{"id":"W70033783","doi":"10.1007/978-3-642-01341-6_8","title":"Markov Decision Process-Based Resource and Information Management for Sensor Networks","year":2009,"lang":"en","type":"book-chapter","venue":"Signals and communication technology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Department of National Defence; Defence Research and Development Canada; General Dynamics (Canada); McMaster University","funders":"","keywords":"Computer science; Sensor fusion; Markov decision process; Wireless sensor network; Process (computing); Markov process; Real-time computing; Distributed computing; Data mining; Artificial intelligence; Computer network","score_opus":0.005268690409078372,"score_gpt":0.22677309279168328,"score_spread":0.2215044023826049,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W70033783","genre_codex":"methods","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":[0.023948044,0.18822734,0.55988485,0.013035266,0.00014552014,0.008920624,0.00020654507,0.00070593343,0.2049259],"genre_scores_gemma":[0.81942457,0.049332395,0.07879895,0.0036050577,0.00022155135,0.00057311513,0.0050126864,0.00019051484,0.04284116],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99910265,0.000019567095,0.0003450848,0.00027715508,0.000094400544,0.00016111117],"domain_scores_gemma":[0.99863636,0.000030489025,0.00030093562,0.00083698065,0.00015106409,0.000044174743],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023756498,0.00022835111,0.00025409684,0.0002621822,0.00018188839,0.00003556726,0.00030501827,0.0006640473,0.0000089834775],"category_scores_gemma":[0.000015317706,0.0002339589,0.00007385596,0.00006361749,0.00016511614,0.000007434769,0.00018772691,0.00015871105,0.0000013623544],"study_design_candidate":"design_other","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":[0.00020598604,0.00002018037,0.00004038458,0.00009900419,0.00022104784,5.3508563e-7,0.000010033311,0.002506388,0.000233695,0.012692727,0.0024213865,0.9815486],"study_design_scores_gemma":[0.0010004771,0.0004057445,0.00006916642,0.0002511228,0.0002907597,0.000013712809,0.00009031196,0.007113018,0.0009641658,0.03885357,0.95041424,0.000533703],"about_ca_topic_score_codex":3.654165e-7,"about_ca_topic_score_gemma":0.000004876526,"teacher_disagreement_score":0.9810149,"about_ca_system_score_codex":0.000013143361,"about_ca_system_score_gemma":0.000018760773,"threshold_uncertainty_score":0.9540567},"labels":[],"label_agreement":null},{"id":"W7011352372","doi":"","title":"70 - 536 - Mario Peluso, 2017 10 02","year":2017,"lang":"fr","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Innocence; Ridiculous; Nomination; Rivalry","score_opus":0.005741507053727166,"score_gpt":0.19007677601966547,"score_spread":0.1843352689659383,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7011352372","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005944729,0.005643481,0.0000026004461,0.00033509123,0.0006452071,0.00044569967,0.00017300522,0.000031609605,0.99212885],"genre_scores_gemma":[0.0060788104,0.0025954684,0.00075070426,0.00021766571,0.0009869882,0.000019087365,0.0009998885,0.00013035149,0.98822105],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99719703,0.00017800817,0.00090696255,0.00055408786,0.0004991422,0.0006647429],"domain_scores_gemma":[0.9960155,0.000042965836,0.0015378172,0.0016614476,0.00043915634,0.00030311503],"candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004111374,0.0007378268,0.00082146475,0.00008319773,0.00030565372,0.00015459982,0.001072253,0.0013558549,0.58790463],"category_scores_gemma":[0.00025658507,0.00079395494,0.00068576884,0.00000738918,0.00052573526,6.669419e-8,0.00044456922,0.000350925,0.03224225],"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":[0.0001584673,0.00007656237,0.00001980022,0.0004634344,0.0005927134,0.000031432282,0.000049814455,0.0018760434,0.000027179974,0.00001634882,0.98377967,0.012908563],"study_design_scores_gemma":[0.0007299035,0.0003104622,0.00007752164,0.00026211725,0.00042130178,0.00015178691,0.00003420012,0.00009640473,0.00033191388,0.0000071233135,0.9967758,0.00080146105],"about_ca_topic_score_codex":0.0021018134,"about_ca_topic_score_gemma":0.004813214,"teacher_disagreement_score":0.5556624,"about_ca_system_score_codex":0.00009006451,"about_ca_system_score_gemma":0.00016870874,"threshold_uncertainty_score":0.9999406},"labels":[],"label_agreement":null},{"id":"W7018547897","doi":"","title":"DynGFN: Towards bayesian inference of gene regulatory networks with gflownets","year":2024,"lang":"","type":"article","venue":"Research Explorer (The University of Manchester)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Samsung; Compute Canada; Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Leverage (statistics); Directed acyclic graph; Inference; Bayesian network; Gene regulatory network; Bayesian inference; Graphical model; Directed graph; Bayesian probability","score_opus":0.03133430847293542,"score_gpt":0.27214379436165703,"score_spread":0.2408094858887216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7018547897","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":[0.9242477,0.019872129,0.05352251,0.0009933069,0.00018313435,0.00066608866,0.00003164168,0.00002715927,0.0004563455],"genre_scores_gemma":[0.99197024,0.0061920932,0.0009790019,0.000016432723,0.00031884082,0.0000027766273,0.00006987562,0.00006325105,0.00038746645],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9955013,0.0009013546,0.00044523823,0.0010373027,0.0011970702,0.00091777055],"domain_scores_gemma":[0.99670774,0.00017434108,0.00020251253,0.0017981387,0.00078708364,0.00033018232],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0018773281,0.0004247572,0.0006154831,0.00040727828,0.00037493123,0.00007009102,0.0014852164,0.0004689695,0.00023541212],"category_scores_gemma":[0.000051274932,0.00036471078,0.00046761648,0.0013472139,0.002462376,0.000039917417,0.0009061396,0.00074016466,0.000025451973],"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":[0.0073645627,0.0019378274,0.020096585,0.0059969034,0.018783072,0.0014852697,0.078034855,0.21439794,0.23805806,0.0026010077,0.02355986,0.38768405],"study_design_scores_gemma":[0.0061310017,0.009106731,0.07706956,0.007574925,0.0042156572,0.00022239992,0.0702161,0.2977349,0.36963966,0.001219867,0.15244155,0.0044276635],"about_ca_topic_score_codex":0.000029742692,"about_ca_topic_score_gemma":0.000031937972,"teacher_disagreement_score":0.3832564,"about_ca_system_score_codex":0.00017057246,"about_ca_system_score_gemma":0.0009835906,"threshold_uncertainty_score":0.9998805},"labels":[],"label_agreement":null},{"id":"W7020877975","doi":"","title":"Mixed effects modelling for biological systems","year":2022,"lang":"fr","type":"dissertation","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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","keywords":"Population; Statistical analysis; Agrégation; Rail transportation","score_opus":0.00882285113229808,"score_gpt":0.1787802634810084,"score_spread":0.1699574123487103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7020877975","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":[0.82317793,0.152844,0.017681025,0.000057597674,0.0031501725,0.0009880557,0.0001618139,0.000046796184,0.001892608],"genre_scores_gemma":[0.94613814,0.0020820836,0.0016721496,0.000042809428,0.00063744857,0.00026873738,0.005325712,0.00006360699,0.043769322],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9969013,0.00038775083,0.0005072626,0.0010983017,0.00046046096,0.00064496795],"domain_scores_gemma":[0.9981414,0.0001275339,0.00051661115,0.0005595298,0.00031904978,0.00033588588],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.00032391088,0.000599371,0.0006372677,0.00020976547,0.0072618434,0.00005868476,0.0005524708,0.0008986031,0.000025021785],"category_scores_gemma":[0.000054852815,0.00070240244,0.0008679333,0.00028097467,0.00020296256,0.000016248368,0.0002740469,0.0003373614,0.00001262591],"study_design_candidate":"simulation_or_modeling","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":[0.0015460482,0.00030334832,0.004324353,0.0006655717,0.0020815555,0.0004411662,0.0025642458,0.8308252,0.1397529,0.014419733,0.0014258748,0.0016500236],"study_design_scores_gemma":[0.0036153332,0.0014624558,0.0035306662,0.00038444257,0.002910079,0.00095917087,0.031147238,0.30922136,0.08631827,0.00025055304,0.5576554,0.002545067],"about_ca_topic_score_codex":0.005619361,"about_ca_topic_score_gemma":0.0008202349,"teacher_disagreement_score":0.5562295,"about_ca_system_score_codex":0.0028982514,"about_ca_system_score_gemma":0.0010962335,"threshold_uncertainty_score":0.9995427},"labels":[],"label_agreement":null},{"id":"W7021890374","doi":"","title":"Sources","year":2020,"lang":"fr","type":"book-chapter","venue":"Industrias Culturais (Universidade de Coimbra)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Period (music); Commission; Quarter (Canadian coin)","score_opus":0.02474904975145432,"score_gpt":0.22235633527706977,"score_spread":0.19760728552561546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7021890374","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.089647606,0.015200803,0.0014201998,0.051181648,0.0015492815,0.0015667606,0.0012180279,0.0002836834,0.837932],"genre_scores_gemma":[0.5473017,0.0010699088,0.0006717648,0.001096048,0.003270168,0.00000790639,0.0018153827,0.0002096014,0.44455752],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99631596,0.0002235624,0.0005685039,0.0014763734,0.000532839,0.00088275544],"domain_scores_gemma":[0.9971315,0.000055325716,0.00067578745,0.0009342229,0.00032256733,0.0008805845],"candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002323451,0.0010700908,0.00097263406,0.0002197508,0.00048012417,0.00016524072,0.0011414267,0.0031421296,0.0021094703],"category_scores_gemma":[0.00013603331,0.0012312465,0.0011342667,0.0003257244,0.0007673695,0.000024128189,0.00066617207,0.0013239252,0.00068067346],"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":[0.0010401868,0.0003347712,0.003749572,0.00045642327,0.017174829,0.0023631682,0.0011355154,0.012423362,0.2502276,0.22883633,0.42326087,0.058997385],"study_design_scores_gemma":[0.0013118266,0.00041410333,0.0024551712,0.00020354359,0.0015485805,0.00018087548,0.00069564296,0.00036178998,0.010298378,0.00023967851,0.9807561,0.0015343118],"about_ca_topic_score_codex":0.00015089144,"about_ca_topic_score_gemma":0.00016367181,"teacher_disagreement_score":0.55749524,"about_ca_system_score_codex":0.00032887372,"about_ca_system_score_gemma":0.00056845264,"threshold_uncertainty_score":0.9990137},"labels":[],"label_agreement":null},{"id":"W7022524953","doi":"","title":"Notes","year":2018,"lang":"fr","type":"article","venue":"Project Muse (Johns Hopkins University)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Subject (documents); Volume (thermodynamics); Relation (database); Work (physics)","score_opus":0.013974560119712267,"score_gpt":0.2222003230691632,"score_spread":0.20822576294945094,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7022524953","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":[0.32953212,0.00027525812,0.005486334,0.0015171994,0.001570308,0.0005339805,0.00010290849,0.00009057164,0.6608913],"genre_scores_gemma":[0.81991416,0.1744258,0.0018615611,0.00023077182,0.0019415384,0.0000010595297,0.00009377981,0.000056423847,0.0014749108],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978096,0.00027870032,0.00021092559,0.0008077381,0.0002046922,0.00068835303],"domain_scores_gemma":[0.99841744,0.000029835834,0.0001646262,0.0008520179,0.00034782267,0.00018826746],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018556393,0.00038448887,0.00031597284,0.0037429004,0.00029307936,0.00005194024,0.0005637402,0.0004912081,0.0002453062],"category_scores_gemma":[0.00007249131,0.00047518325,0.00037111578,0.006153544,0.0006199669,0.000022494924,0.00048334114,0.00018418097,0.00026501613],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024476985,0.0032345173,0.02821415,0.00083041843,0.009806366,0.0013671957,0.009492361,0.0010031399,0.020993808,0.018399166,0.059391502,0.84481966],"study_design_scores_gemma":[0.0007138304,0.000526578,0.000154981,0.00004725172,0.0004430186,0.000028600747,0.00022876728,0.00048070197,0.028672397,0.0000010519317,0.968192,0.00051081466],"about_ca_topic_score_codex":0.01734496,"about_ca_topic_score_gemma":0.029315092,"teacher_disagreement_score":0.9088005,"about_ca_system_score_codex":0.00015354432,"about_ca_system_score_gemma":0.00064349384,"threshold_uncertainty_score":0.99977},"labels":[],"label_agreement":null},{"id":"W7023213689","doi":"","title":"Introduction générale","year":2023,"lang":"fr","type":"article","venue":"Industrias Culturais (Universidade de Coimbra)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Investment (military)","score_opus":0.017863216410097336,"score_gpt":0.2331498463660237,"score_spread":0.21528662995592637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7023213689","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":[0.8256045,0.0044538365,0.000417859,0.15428342,0.0031019133,0.00045384117,0.0001900621,0.00022704793,0.011267499],"genre_scores_gemma":[0.5995795,0.0012499886,0.00026619044,0.0002690109,0.008142073,0.000011911596,0.00153305,0.000074748976,0.38887352],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99723274,0.00034408527,0.00030686133,0.0008654974,0.0003160904,0.00093473523],"domain_scores_gemma":[0.99842733,0.000027408414,0.00021871497,0.00072239287,0.00023109221,0.00037308983],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00044377107,0.00038601801,0.00036507932,0.0002832251,0.00035913533,0.00011650706,0.00049474096,0.0011969145,0.0011330511],"category_scores_gemma":[0.00018236916,0.0004900172,0.0004085084,0.0021352523,0.00032809327,0.00003981724,0.0003091222,0.00051869237,0.0011467392],"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":[0.00006353218,0.00006913753,0.0010417678,0.000033293156,0.00059986906,0.00009494834,0.00019221535,0.008699918,0.10504115,0.0010813326,0.8717041,0.011378753],"study_design_scores_gemma":[0.0010961529,0.00020686147,0.029173872,0.00004640849,0.00043358924,0.00014225932,0.0022734532,0.0017035651,0.02745362,0.00010102525,0.93670297,0.0006662104],"about_ca_topic_score_codex":0.00019318202,"about_ca_topic_score_gemma":0.00013780837,"teacher_disagreement_score":0.37760603,"about_ca_system_score_codex":0.00027512904,"about_ca_system_score_gemma":0.00029244713,"threshold_uncertainty_score":0.99978006},"labels":[],"label_agreement":null},{"id":"W7025328674","doi":"","title":"Vista Stock Shots: Office Communications and Machines","year":2023,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Phone; Telephone line; Dial; Flash (photography); Shot (pellet); Line (geometry)","score_opus":0.0067185960130298605,"score_gpt":0.205048312569158,"score_spread":0.19832971655612816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7025328674","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00021169218,0.0024254266,0.0000012391124,0.00012870171,0.00007784334,0.0002173491,0.00013528614,0.00009811437,0.99670434],"genre_scores_gemma":[0.0022365104,0.0027241625,0.00075221586,0.00011429072,0.00013451379,0.000016098553,0.0005162154,0.00018967509,0.9933163],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990039,0.000072187744,0.000370654,0.00019981313,0.00017401892,0.00017946075],"domain_scores_gemma":[0.99862826,0.00003411457,0.00033450403,0.0008276285,0.00009323963,0.00008222906],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00014964273,0.00024220003,0.0002754324,0.000058175494,0.00006958164,0.00002974663,0.0003853219,0.00033325347,0.018545272],"category_scores_gemma":[0.000059709528,0.0002494738,0.0001237108,0.00001029436,0.00017233336,1.373637e-8,0.0002868822,0.00012313899,0.0010961393],"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":[0.000025384645,0.000018065732,0.000018457402,0.00011412729,0.00016162405,0.0000012535879,0.000015811816,0.000119762604,0.0000086814125,0.0000068946597,0.99707276,0.0024372074],"study_design_scores_gemma":[0.00021103305,0.000078967416,0.000037542282,0.0000689985,0.000093720904,0.000019342819,0.0000264256,0.000110903675,0.000012282206,0.000001796527,0.99910074,0.00023824128],"about_ca_topic_score_codex":0.0015421949,"about_ca_topic_score_gemma":0.0076275743,"teacher_disagreement_score":0.017449131,"about_ca_system_score_codex":0.000012177562,"about_ca_system_score_gemma":0.000025424588,"threshold_uncertainty_score":0.99999577},"labels":[],"label_agreement":null},{"id":"W7030577336","doi":"","title":"A numerical study of the effects of multiplicative noise on a supercritical delay induced Hopf bifurcation in a gene expression model /","year":2006,"lang":"en","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Hopf bifurcation; Multiplicative noise; Nonlinear system; Convergence (economics); Noise (video); Stochastic differential equation; Context (archaeology); Delay differential equation; Numerical analysis; Multiplicative function","score_opus":0.0025828935624051513,"score_gpt":0.1622527327205597,"score_spread":0.15966983915815455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7030577336","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":[0.98078126,0.00030596106,0.00011658003,0.00007955709,0.0000403839,0.0004858884,0.000076434226,0.0000019934512,0.018111918],"genre_scores_gemma":[0.99481016,0.000032707703,0.00022800786,0.0000775692,0.00003278035,0.000028458031,0.00001546132,0.000056249824,0.004718596],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984511,0.00014025121,0.00025652297,0.00028920895,0.0007165008,0.00014638038],"domain_scores_gemma":[0.9993812,0.000056388748,0.00012397561,0.0003669204,0.000001041282,0.00007048916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00000842425,0.00018539568,0.00030546405,0.000035186265,0.000026563193,0.0000021464493,0.00021197167,0.00007840343,0.0000018608902],"category_scores_gemma":[0.0000071472123,0.00014690266,0.000046653662,0.000085904,0.00005219761,0.0000035575133,0.0001267118,0.000095637784,3.7928718e-10],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002827529,0.00036315896,0.014917937,0.00021400682,0.00013513865,0.0000068553923,0.000060141458,0.0030765864,0.9782405,0.00015910986,0.0021527756,0.00039106436],"study_design_scores_gemma":[0.00072973524,0.00026899963,0.019061865,0.00025484766,0.000058385303,7.581938e-7,0.00019128247,0.003948784,0.9749108,0.000023971677,0.00035712824,0.00019347043],"about_ca_topic_score_codex":0.0033734366,"about_ca_topic_score_gemma":0.018380785,"teacher_disagreement_score":0.015007349,"about_ca_system_score_codex":0.0000053006897,"about_ca_system_score_gemma":0.00050498976,"threshold_uncertainty_score":0.9995312},"labels":[],"label_agreement":null},{"id":"W7038230155","doi":"","title":"Godless Episode 7: Religion and Poverty","year":2009,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Poverty; Religiosity; Prayer; Context (archaeology)","score_opus":0.003032658659871304,"score_gpt":0.17560187324400928,"score_spread":0.172569214584138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7038230155","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00032766492,0.0026336587,0.0000016124577,0.00009212427,0.000074194286,0.00018250108,0.000040890718,0.000036796657,0.9966106],"genre_scores_gemma":[0.0019328872,0.0023433045,0.00062068354,0.00051692914,0.00022490039,0.0000048114775,0.00036672826,0.00008346242,0.9939063],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99892133,0.000053523705,0.00036497947,0.00024309917,0.00020362172,0.00021341168],"domain_scores_gemma":[0.99905527,0.000009355864,0.00035832377,0.0004046099,0.00007420205,0.000098258126],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00011959711,0.0002766625,0.00031716624,0.00004925048,0.000039129693,0.000023783286,0.00018472955,0.0004868017,0.019054798],"category_scores_gemma":[0.00003335862,0.000273639,0.00014443822,0.000005856029,0.00007967684,9.90525e-9,0.00008858933,0.00010843022,0.0007280071],"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":[0.00004107525,0.00001760483,0.000011422603,0.0001083094,0.000088204186,0.0000032540609,0.0000067378496,0.00020706079,0.0000129528,0.000007327889,0.9973033,0.0021927173],"study_design_scores_gemma":[0.00029239125,0.00013016687,0.000023661803,0.00007817952,0.000081006656,0.00004504493,0.0000075074445,0.000016088816,0.00012101303,0.0000076376145,0.99891347,0.0002838548],"about_ca_topic_score_codex":0.0010618044,"about_ca_topic_score_gemma":0.0017050962,"teacher_disagreement_score":0.018326793,"about_ca_system_score_codex":0.0000132873165,"about_ca_system_score_gemma":0.000017461412,"threshold_uncertainty_score":0.99997157},"labels":[],"label_agreement":null},{"id":"W7038465539","doi":"","title":"Hvilke fordeler og ulemper kan karakterer i barneskolen ha på elevers motivasjon for læring?","year":2019,"lang":"no","type":"dissertation","venue":"Duo Research Archive (University of Oslo)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Corporation","score_opus":0.02199901803091362,"score_gpt":0.27613899217838417,"score_spread":0.2541399741474705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7038465539","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":[0.98096895,0.00090117485,0.008556881,0.00030823302,0.00030937057,0.0020190636,0.0010879652,0.000021427168,0.0058269445],"genre_scores_gemma":[0.93922067,0.001615482,0.0027222896,0.000030678406,0.0003000313,0.000011390008,0.011752626,0.0001397496,0.04420711],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9944156,0.0007921055,0.0004560661,0.0017199168,0.0011268856,0.0014894581],"domain_scores_gemma":[0.9958434,0.00030915838,0.00047654257,0.0014795344,0.001390314,0.00050106086],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0013535166,0.00065956614,0.0009952126,0.0010069967,0.00083976454,0.000066158886,0.0017365175,0.00073138595,0.00059832004],"category_scores_gemma":[0.00023673546,0.0008253167,0.001261455,0.0005886958,0.00070272817,0.000037291346,0.00075868994,0.0008971072,0.00017941456],"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":[0.009355452,0.0011573206,0.028324075,0.004218937,0.008587182,0.00011606451,0.0074244803,0.0034991347,0.8362581,0.0013594788,0.076990165,0.022709597],"study_design_scores_gemma":[0.018162033,0.009024102,0.1402513,0.002224625,0.0031828894,0.00003765297,0.07072032,0.03693366,0.08952439,0.004469136,0.6191421,0.0063277874],"about_ca_topic_score_codex":0.0007442898,"about_ca_topic_score_gemma":0.0025345716,"teacher_disagreement_score":0.7467337,"about_ca_system_score_codex":0.00016633028,"about_ca_system_score_gemma":0.0009737438,"threshold_uncertainty_score":0.99941975},"labels":[],"label_agreement":null},{"id":"W7038731589","doi":"","title":"The Impact of Social Media on the Publishing Industry: A Case Study of Author Colleen Hoover","year":2023,"lang":"en","type":"article","venue":"Digital Commons - East Tennessee State University (East Tennessee State University)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Publishing; Social media; Popularity; Consumption (sociology); Romance; Quarter (Canadian coin)","score_opus":0.023454864192424964,"score_gpt":0.22681361070345285,"score_spread":0.2033587465110279,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7038731589","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":[0.9946783,0.000012278039,0.000057037785,0.00046052114,0.00010115266,0.0005107714,0.001802766,0.000067217115,0.0023099228],"genre_scores_gemma":[0.99652356,0.000017417939,0.0000024794326,0.0000052262258,0.00005152182,8.721021e-7,0.00024001871,0.00004822065,0.0031107091],"study_design_codex":"observational","study_design_gemma":"qualitative","domain_scores_codex":[0.9972102,0.0004897392,0.00038844725,0.0006430394,0.0005432887,0.0007252513],"domain_scores_gemma":[0.9971644,0.00031935278,0.0005779,0.0008952192,0.00076821813,0.00027490754],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005118755,0.0004743913,0.0005466537,0.0006789579,0.0011943786,0.00025423212,0.0013979434,0.0002668945,0.000020380177],"category_scores_gemma":[0.000213999,0.00037867302,0.0005466545,0.0034839374,0.00069101,0.00017270027,0.0012491576,0.00058247894,0.000008611797],"study_design_candidate":"qualitative","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":[0.02445915,0.016952783,0.40857914,0.0005049037,0.04238296,0.039320797,0.13206637,0.11725184,0.016177638,0.010111551,0.15647374,0.03571912],"study_design_scores_gemma":[0.008214691,0.0025802273,0.07959352,0.0001167969,0.0009687764,0.0003005693,0.8829706,0.002772511,0.00060616905,0.0003047289,0.019565545,0.0020059033],"about_ca_topic_score_codex":0.0007284616,"about_ca_topic_score_gemma":0.0042806733,"teacher_disagreement_score":0.7509042,"about_ca_system_score_codex":0.00019859821,"about_ca_system_score_gemma":0.00043100512,"threshold_uncertainty_score":0.99986655},"labels":[],"label_agreement":null},{"id":"W7100737683","doi":"","title":"2. Background","year":2014,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"","score_opus":0.008573549262980169,"score_gpt":0.2296660708136146,"score_spread":0.2210925215506344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7100737683","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":[0.9331041,0.0001302199,0.024746723,0.00009436223,0.000055196193,0.000024638155,2.4826963e-7,0.000012239324,0.041832298],"genre_scores_gemma":[0.9900305,0.00001081818,0.0013469231,0.00036586163,0.00027832063,0.0000022412937,0.000019832178,0.000008131311,0.007937333],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996035,0.000026008342,0.00006367688,0.00015139647,0.000050047653,0.00010538573],"domain_scores_gemma":[0.99965423,0.0000025081065,0.00001573781,0.00026164507,0.000022616448,0.00004324964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009756832,0.000055124103,0.000053276442,0.000012800553,0.000028063843,0.0000096741205,0.000081940474,0.00004764708,0.00012058404],"category_scores_gemma":[0.000008044084,0.000048224894,0.00005645785,0.000044227523,0.000020545445,4.377742e-7,0.00004040059,0.000015593147,0.000084388215],"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":[0.00002344371,0.00005785472,0.01843095,0.000009051745,0.00018733245,6.033948e-7,0.000008818778,0.0014524215,0.86150163,0.0067378883,0.08691559,0.024674429],"study_design_scores_gemma":[0.00025400374,0.000106877684,0.007388312,0.0000013200429,0.000024479776,0.000006438911,0.000021466558,0.0015070391,0.125948,0.00032030462,0.86422014,0.00020163883],"about_ca_topic_score_codex":0.0000033306826,"about_ca_topic_score_gemma":0.000022566355,"teacher_disagreement_score":0.77730453,"about_ca_system_score_codex":0.0000022977265,"about_ca_system_score_gemma":0.000007366827,"threshold_uncertainty_score":0.19665541},"labels":[],"label_agreement":null},{"id":"W7105506887","doi":"","title":"Simulation-based Methods for Optimal Sampling Design in Systems Biology","year":2025,"lang":"","type":"article","venue":"ArXiv.org","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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; Canada Research Chairs","keywords":"Sampling (signal processing); Selection (genetic algorithm); Key (lock); Estimation theory; Fisher information; Optimal design; Population; Sampling design; Dynamical systems theory","score_opus":0.0717695924646862,"score_gpt":0.3892551568156382,"score_spread":0.317485564350952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7105506887","genre_codex":"methods","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":[0.27718407,0.00973791,0.71147543,0.00013081523,0.0005967928,0.0008151305,0.000013204678,0.000014251345,0.000032414915],"genre_scores_gemma":[0.91841865,0.00011091915,0.0801335,0.00022400291,0.00032199474,0.00021205378,0.00017844094,0.00004888919,0.0003515321],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99589676,0.0011654736,0.0009804867,0.0011239714,0.00007570048,0.00075758144],"domain_scores_gemma":[0.9966983,0.0016452615,0.0003173952,0.00087858323,0.00033764736,0.00012276624],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002021639,0.00046885147,0.0007437486,0.0003521453,0.00023078505,0.000053558346,0.00045329364,0.00079420384,0.000017344346],"category_scores_gemma":[0.0011825025,0.0005144678,0.00042258724,0.0007279685,0.00017038698,0.000006053095,0.00014847287,0.00019688456,0.000007067023],"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":[0.00022787487,0.000090773785,0.09833605,0.0001237117,0.00038482822,6.6544953e-7,0.000015630116,0.8072361,0.08856248,0.000088169945,0.000029890336,0.004903821],"study_design_scores_gemma":[0.001495246,0.00025971566,0.0033247378,0.00011465935,0.00036475837,3.521095e-7,0.0000763653,0.933438,0.04395,0.00007692388,0.016414491,0.00048477115],"about_ca_topic_score_codex":0.000036846344,"about_ca_topic_score_gemma":0.000011731074,"teacher_disagreement_score":0.6412346,"about_ca_system_score_codex":0.00013709476,"about_ca_system_score_gemma":0.0006183396,"threshold_uncertainty_score":0.9997307},"labels":[],"label_agreement":null},{"id":"W7108687077","doi":"10.5376/cmb.2025.15.0019","title":"Mathematical Modeling of Synthetic Genetic Circuits","year":2025,"lang":"","type":"article","venue":"Computational Molecular Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Synthetic biology; Electronic circuit; Genetic programming; Genetic algorithm; Mathematical model; Stability (learning theory); Experimental data; Synthetic data; Ordinary differential equation","score_opus":0.00918685579768262,"score_gpt":0.26960664880643886,"score_spread":0.26041979300875623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7108687077","genre_codex":"methods","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":[0.21202704,0.010189142,0.7736325,0.000285964,0.00017474749,0.00030320277,0.000027299171,0.000011597854,0.003348505],"genre_scores_gemma":[0.9886163,0.00009101731,0.010325446,0.00026533703,0.00009065626,0.000029950916,0.00022924236,0.000043994365,0.00030804],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99657595,0.00047853676,0.0011544111,0.0010107161,0.00023599721,0.0005443828],"domain_scores_gemma":[0.9980795,0.00009500702,0.00030528722,0.000803367,0.00057354104,0.0001433296],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003195674,0.0004694313,0.00075061846,0.0003571044,0.0001270733,0.000026143203,0.0006110416,0.0006264138,0.00017276546],"category_scores_gemma":[0.00022812173,0.00052677194,0.000580697,0.00057446986,0.00049509143,0.0000029548773,0.00043985478,0.00019488303,0.000057863646],"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":[0.00005324216,0.00027517445,0.00055583764,0.00025432662,0.0013878417,0.000009971177,0.000025479723,0.8738008,0.06435368,0.046912014,0.00007916812,0.012292445],"study_design_scores_gemma":[0.0006940539,0.00026116628,0.00015115093,0.00014716541,0.0005205571,0.000035116944,0.000021450262,0.64420724,0.0052510635,0.3479174,0.00036294598,0.00043069522],"about_ca_topic_score_codex":0.000003947355,"about_ca_topic_score_gemma":0.0000014072847,"teacher_disagreement_score":0.7765893,"about_ca_system_score_codex":0.00005410791,"about_ca_system_score_gemma":0.00063389895,"threshold_uncertainty_score":0.99971837},"labels":[],"label_agreement":null},{"id":"W7111241752","doi":"10.1103/9cp8-vwlj","title":"Using random perturbations to infer the structure of feedback control in gene expression","year":2025,"lang":"en","type":"article","venue":"Physical review. E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Infinitesimal; Perturbation (astronomy); Negative feedback; Expression (computer science); Stochastic process; Limit (mathematics); Feedback loop; Feedback control; Control theory (sociology)","score_opus":0.009615465419016443,"score_gpt":0.3090406940884646,"score_spread":0.29942522866944815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7111241752","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":[0.9790316,0.011050275,0.00895628,0.00048787962,0.000030729694,0.0003535577,0.000009189717,0.000002006399,0.00007848259],"genre_scores_gemma":[0.99795383,0.00063408614,0.0002566538,0.0009837267,0.00009806844,0.000009195948,0.00001491021,0.0000058836845,0.00004364242],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99931794,0.00012823624,0.00018718449,0.00017299257,0.00008702183,0.00010659211],"domain_scores_gemma":[0.999476,0.00003246137,0.00005900088,0.00033506812,0.00006828679,0.000029137875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000865706,0.000092958406,0.00026165025,0.000023501922,0.000034400124,0.000006200496,0.00014771968,0.000032437707,0.000010024033],"category_scores_gemma":[0.00013336445,0.000059429505,0.00014494298,0.00025996906,0.000029961653,0.0000020773564,0.00006741263,0.00005682282,0.0000012194388],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026192129,0.000023941924,0.001080777,0.000054501263,0.000035728215,8.3912965e-8,0.000012180336,0.005323629,0.99191564,0.00006470057,0.0007725446,0.00069007085],"study_design_scores_gemma":[0.0012709959,0.000039868602,0.005276561,0.0006265558,0.00030045296,8.6516656e-7,0.000011747906,0.006302106,0.97468656,0.00122917,0.010069121,0.00018599872],"about_ca_topic_score_codex":0.0000057419334,"about_ca_topic_score_gemma":0.000009021533,"teacher_disagreement_score":0.018922232,"about_ca_system_score_codex":0.000010433109,"about_ca_system_score_gemma":0.000040695017,"threshold_uncertainty_score":0.24234648},"labels":[],"label_agreement":null},{"id":"W7118006033","doi":"10.1145/3712285.3787166","title":"10.1145/3712285.3787166","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Session (web analytics); Session key; Component (thermodynamics); MEDLINE","score_opus":0.0030701445101415175,"score_gpt":0.1718930996687176,"score_spread":0.1688229551585761,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7118006033","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08155093,0.0004577684,0.0000063895145,0.00016187521,0.0000030696056,0.00012796694,0.000008979613,0.000036423575,0.9176466],"genre_scores_gemma":[0.01582401,0.000002755705,0.00017194405,0.000108790846,0.0002908273,0.000013154239,0.00008618557,0.000027027469,0.9834753],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999116,0.000041137253,0.00014540578,0.00031989662,0.00011798921,0.0002595811],"domain_scores_gemma":[0.9993031,0.000004111988,0.000024303943,0.00048199514,0.00004167537,0.00014480425],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00010078511,0.0001420432,0.00013861207,0.00003793766,0.00006047427,0.000019705674,0.00021333725,0.000102894315,0.93690336],"category_scores_gemma":[0.000012564491,0.0001449654,0.00011792504,0.00016034878,0.00002999098,0.0000016592023,0.00005749767,0.00004079934,0.8330219],"study_design_candidate":"not_applicable","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":[0.00010988791,0.000059146252,0.000004293041,0.0000033498,0.00014013052,0.0000042321094,0.0000045393917,0.0023757392,0.040687423,6.8139684e-7,0.3995175,0.5570931],"study_design_scores_gemma":[0.00014763592,0.00013167744,0.00007256409,0.0000031011264,0.000035383237,0.0000067512806,4.2868237e-7,0.00017740164,0.008563153,0.0000023185642,0.9906755,0.00018409197],"about_ca_topic_score_codex":0.0000052939063,"about_ca_topic_score_gemma":4.6611763e-7,"teacher_disagreement_score":0.591158,"about_ca_system_score_codex":0.000010865922,"about_ca_system_score_gemma":0.000027914293,"threshold_uncertainty_score":0.5911517},"labels":[],"label_agreement":null},{"id":"W7132219754","doi":"","title":"Dynamic cellular automata: an alternative to cellular simulation","year":2005,"lang":"","type":"article","venue":"NPARC","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Cellular automaton; Cellular metabolism; Simplicity; Cellular network; Variety (cybernetics); Simple (philosophy); Petri net","score_opus":0.008575050045414602,"score_gpt":0.25849105797326277,"score_spread":0.24991600792784818,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132219754","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":[0.90798664,0.0011001868,0.086593404,0.00077348383,0.00037963924,0.00054504746,0.000049699458,0.00004719937,0.0025247114],"genre_scores_gemma":[0.98513716,0.00016134582,0.009393737,0.00043870936,0.0013956884,0.000028256929,0.00047526738,0.0001139277,0.0028559272],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.996199,0.00034305075,0.0007142192,0.0013642906,0.00054691295,0.0008325063],"domain_scores_gemma":[0.9972073,0.000022522236,0.00028780743,0.0015652365,0.00030426425,0.00061288255],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00048279625,0.00059625326,0.00050486677,0.00021933863,0.00027524354,0.00013006192,0.00070342375,0.0004710423,0.0006501456],"category_scores_gemma":[0.000051767114,0.00068906136,0.00037455925,0.00044539856,0.00012593101,0.00002746792,0.00034581253,0.00022223733,0.0004019303],"study_design_candidate":"simulation_or_modeling","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":[0.00006860933,0.00019949386,0.00008356627,0.000014802267,0.0002197268,0.00000909998,0.00018544703,0.42224038,0.54510367,0.000040990664,0.0002616003,0.03157259],"study_design_scores_gemma":[0.00057826354,0.0003970597,0.00012297377,0.000020998184,0.00022213114,0.0000024972292,0.00006501096,0.65630454,0.2815969,0.00022518952,0.059861768,0.00060268637],"about_ca_topic_score_codex":0.0000098785695,"about_ca_topic_score_gemma":0.000092737995,"teacher_disagreement_score":0.2635068,"about_ca_system_score_codex":0.00022143175,"about_ca_system_score_gemma":0.00016588777,"threshold_uncertainty_score":0.99955606},"labels":[],"label_agreement":null},{"id":"W7132947439","doi":"","title":"Exploration of New Nucleic Acid Factors to Improve the Development of Synthetic Biosensing Switches","year":2022,"lang":"","type":"dissertation","venue":"TSpace","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Nucleic acid; Allosteric regulation; Gene; DNA; Transcription factor; Transcription (linguistics); Synthetic biology; Regulation of gene expression","score_opus":0.024090292249449242,"score_gpt":0.2961500076437484,"score_spread":0.27205971539429913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132947439","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":[0.99466103,0.0016849098,0.0022327318,0.0002058904,0.0004592604,0.00058514555,0.0000076571,0.000007048909,0.00015632281],"genre_scores_gemma":[0.9942678,0.00013180281,0.0015264119,0.000018061648,0.00011057928,0.000022455959,0.00056982716,0.000076284916,0.003276773],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99735206,0.00014894598,0.0009059729,0.00071196194,0.00052100874,0.00036002923],"domain_scores_gemma":[0.99758744,0.000031187883,0.0010420252,0.00091738236,0.00026441627,0.00015757514],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00040163082,0.0004922321,0.000623924,0.00019884568,0.00028861707,0.000027101825,0.00047596882,0.00031601384,0.00016833241],"category_scores_gemma":[0.00013918162,0.00042923196,0.00038358633,0.00057981355,0.00006662987,0.000007537666,0.00024257934,0.00019638169,0.000005665575],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015141637,0.000065796,0.00016663491,0.000136413,0.0005748314,2.480451e-7,0.035373457,0.002104295,0.9471176,0.000007330145,0.00012005001,0.014181873],"study_design_scores_gemma":[0.00017024406,0.00023031364,0.0011050836,0.00008328406,0.00039450097,5.939657e-7,0.057910964,0.00010946,0.9363321,0.000019310168,0.0032603506,0.00038375947],"about_ca_topic_score_codex":0.00010745107,"about_ca_topic_score_gemma":0.0005413319,"teacher_disagreement_score":0.022537507,"about_ca_system_score_codex":0.00009583448,"about_ca_system_score_gemma":0.0009967143,"threshold_uncertainty_score":0.99981594},"labels":[],"label_agreement":null},{"id":"W7132989043","doi":"","title":"Mesoscopic Models of Cellular Signaling Reveal Strategies for Specificity in Crosstalk Signal Pathways","year":2023,"lang":"","type":"dissertation","venue":"TSpace","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Crosstalk; Signal transduction; Robustness (evolution); Mesoscopic physics; SIGNAL (programming language); Cell signaling; Immune system","score_opus":0.03429239878772559,"score_gpt":0.30149264365288053,"score_spread":0.2672002448651549,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132989043","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":[0.96848744,0.005772888,0.023833618,0.000018253153,0.00033677858,0.0009713431,0.00010381097,0.00002163474,0.00045421702],"genre_scores_gemma":[0.9899287,0.00051252556,0.001070762,0.000009563557,0.00046016058,0.0001306371,0.0030865015,0.00016694299,0.0046342085],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99590844,0.00022097111,0.0012460091,0.0012940883,0.00048408413,0.0008463934],"domain_scores_gemma":[0.9975222,0.00009210356,0.00091800746,0.0007897788,0.00051233656,0.00016559886],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007873729,0.0007672357,0.0011952817,0.00033356034,0.00018885429,0.00011002219,0.0005647663,0.0011385317,0.0000701215],"category_scores_gemma":[0.000038493712,0.000901384,0.00079191936,0.0006400241,0.00016847948,0.0000150585465,0.00011902748,0.0003482691,0.0000068435384],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004085173,0.00012352983,0.00013007942,0.000932991,0.00036735713,0.00001172011,0.0030082127,0.20904288,0.7851782,0.00032760127,0.00014739047,0.00032154022],"study_design_scores_gemma":[0.0011792408,0.0005865316,0.00025156705,0.0004987724,0.00045194037,0.0000011890577,0.034117367,0.02696706,0.9304165,0.004402121,0.00014788333,0.0009798314],"about_ca_topic_score_codex":0.00026153243,"about_ca_topic_score_gemma":0.0007221625,"teacher_disagreement_score":0.18207581,"about_ca_system_score_codex":0.00009402032,"about_ca_system_score_gemma":0.0010827753,"threshold_uncertainty_score":0.9993437},"labels":[],"label_agreement":null},{"id":"W7133002540","doi":"","title":"Elucidating gene dynamics in Escherichia coli: Theoretical and practical approaches","year":2007,"lang":"","type":"dissertation","venue":"TSpace","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Canadian Heritage","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Escherichia coli; Gene; Genome; Reporter gene; RNA; Escherichia coli Proteins; Gene expression; Dynamics (music)","score_opus":0.015906088521776947,"score_gpt":0.3175097168152333,"score_spread":0.3016036282934564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7133002540","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":[0.97714853,0.0033134248,0.011638893,0.00042316318,0.0001877078,0.00050781306,0.000007410541,0.000013086965,0.0067599686],"genre_scores_gemma":[0.9804744,0.0013035868,0.014060739,0.00010624205,0.00039134917,0.00003802995,0.0018700765,0.00012275352,0.0016327989],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9961784,0.00040977678,0.0007788541,0.0013500055,0.0004241763,0.0008588282],"domain_scores_gemma":[0.9981698,0.00012213047,0.00048349734,0.0007334024,0.0001563531,0.0003348395],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0012523463,0.0007235887,0.0007759615,0.0002109563,0.00018264576,0.00011789209,0.00021709267,0.0015981223,0.00011148261],"category_scores_gemma":[0.00045299623,0.0008001215,0.00023987092,0.00054899836,0.0005112072,0.0000075755875,0.00022583126,0.0008427883,0.000010212891],"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":[0.0065273037,0.0031486463,0.034364544,0.002444955,0.004956984,0.000713656,0.010246799,0.0066696275,0.7697215,0.11543672,0.0007800952,0.04498919],"study_design_scores_gemma":[0.0033434748,0.0011831498,0.014258055,0.0004053439,0.0024053275,0.0002427001,0.061008062,0.51182646,0.39734828,0.0012590942,0.0022823839,0.004437656],"about_ca_topic_score_codex":0.00006001963,"about_ca_topic_score_gemma":0.0010199232,"teacher_disagreement_score":0.5051568,"about_ca_system_score_codex":0.00019802923,"about_ca_system_score_gemma":0.00041827868,"threshold_uncertainty_score":0.999698},"labels":[],"label_agreement":null},{"id":"W7148561379","doi":"10.1007/978-3-032-07031-9_9","title":"Biochemical Reaction Networks","year":2025,"lang":"en","type":"book-chapter","venue":"Static & dynamic game theory: foundations & applications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières; Innovation and Economic Development Trois Rivières","funders":"","keywords":"Chemical reaction; Stoichiometry; Context (archaeology); Node (physics); Molecule; Representation (politics); Chemical structure; Reaction mechanism","score_opus":0.005611205564930253,"score_gpt":0.2534304886115995,"score_spread":0.24781928304666925,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7148561379","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00037983924,0.0021224227,0.80264634,0.0004065139,0.00020545885,0.0015639556,0.00029247443,0.00013863368,0.19224434],"genre_scores_gemma":[0.16738133,0.0023759643,0.004444774,0.00040352592,0.0005851266,0.0012764268,0.022730885,0.00021699983,0.800585],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976037,0.00008760381,0.0006788153,0.0009865867,0.0002560697,0.00038721095],"domain_scores_gemma":[0.9972087,0.00012546834,0.00046902514,0.0017100647,0.00033381704,0.00015289253],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003686776,0.0005420287,0.0004701131,0.0002743193,0.00030114147,0.00007617295,0.00053427095,0.00061341585,0.00022884793],"category_scores_gemma":[0.00005203706,0.0006174958,0.00039704453,0.0002228518,0.00042886173,0.000007293589,0.00021117218,0.00040916898,0.00019343404],"study_design_candidate":"theoretical_or_conceptual","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":[0.00010041426,0.00017480784,0.000009711528,0.000104534876,0.0024544154,0.0000016710802,0.000045115685,0.0035274967,0.012324802,0.8940629,0.017115882,0.07007827],"study_design_scores_gemma":[0.00039739316,0.00007238056,0.000057279143,0.00009050688,0.0016573028,0.000018312692,0.000047399193,0.009558831,0.00015189615,0.17669687,0.81033194,0.00091990846],"about_ca_topic_score_codex":0.0000068272457,"about_ca_topic_score_gemma":0.00006608933,"teacher_disagreement_score":0.79820156,"about_ca_system_score_codex":0.00021728805,"about_ca_system_score_gemma":0.0003798482,"threshold_uncertainty_score":0.99962765},"labels":[],"label_agreement":null},{"id":"W7162191107","doi":"10.65521/ijeecs.v14i2.2137","title":"A Systematic Review of Mathematical Modelling of Epigenetic Regulatory Mechanisms in Gene Expression: Methods, Architectures, and Future Research Directions","year":2025,"lang":"","type":"article","venue":"International Journal of Electrical Electronics and Computer Systems","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","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":"Epigenetics; Gene regulatory network; Chromatin; Regulation of gene expression; Histone; Systems biology; DNA methylation; Epigenesis; Gene","score_opus":0.013841424528690898,"score_gpt":0.3113750826606927,"score_spread":0.2975336581320018,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7162191107","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0095593035,0.56015676,0.42926306,0.00021131973,0.00035430578,0.00042211424,0.0000035422988,0.000001538593,0.000028016679],"genre_scores_gemma":[0.67303824,0.3031581,0.02286161,0.000071460316,0.0007285537,0.00003135529,0.0000064240203,0.000030433574,0.00007382176],"study_design_codex":"systematic_review","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9940346,0.0018764439,0.0023699412,0.00043902572,0.0008725619,0.00040744196],"domain_scores_gemma":[0.99639094,0.00040325164,0.0011406387,0.00040893347,0.0015137257,0.00014253677],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0043670144,0.00029603436,0.0014554046,0.0008651306,0.00007157448,0.000059443548,0.00064467784,0.00030908445,0.0000031283453],"category_scores_gemma":[0.00015420254,0.00024773012,0.0003555878,0.0007432698,0.00013017881,0.000009788633,0.0002638718,0.000630625,1.08713415e-7],"study_design_candidate":"simulation_or_modeling","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":[0.0018437371,0.0034296701,0.00021962188,0.43987587,0.021938926,0.00015795628,0.0009373267,0.06529047,0.26075658,0.14777961,0.0009945494,0.056775652],"study_design_scores_gemma":[0.002633391,0.002924925,0.00006462504,0.22351341,0.0020574292,0.0020185055,0.00015167847,0.6067042,0.13417393,0.02290424,0.0019844535,0.00086926017],"about_ca_topic_score_codex":0.00000835414,"about_ca_topic_score_gemma":0.0000022268691,"teacher_disagreement_score":0.663479,"about_ca_system_score_codex":0.00016020706,"about_ca_system_score_gemma":0.00060846604,"threshold_uncertainty_score":0.9999975},"labels":[],"label_agreement":null},{"id":"W77265774","doi":"10.1007/978-1-62703-526-2_3","title":"Single-Molecule Resolution Fluorescent In Situ Hybridization (smFISH) in the Yeast S. cerevisiae","year":2013,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Canadian Institutes of Health Research","keywords":"In situ hybridization; Gene expression; Biology; RNA; Yeast; Cell biology; In situ; Context (archaeology); Molecular biology; DNA; Saccharomyces cerevisiae; Fluorescence in situ hybridization; Fluorescence; Computational biology; Cell; Gene; Single-cell analysis; Chemistry; Biochemistry; Chromosome","score_opus":0.015454702991797813,"score_gpt":0.3159296412762041,"score_spread":0.3004749382844063,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W77265774","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":[0.7123233,0.0022379402,0.28352672,0.00047751324,0.00010171823,0.00053800474,0.0000021731373,0.0000092710325,0.0007833818],"genre_scores_gemma":[0.9120056,0.00013011138,0.086768486,0.00065794436,0.0000845101,0.00013389048,0.00016333534,0.000030450854,0.000025673775],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9953555,0.0028855512,0.00052724325,0.0006207437,0.00011715467,0.00049384916],"domain_scores_gemma":[0.9990515,0.000041009454,0.00013084985,0.00065915385,0.00006699256,0.00005046881],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015253474,0.00024327206,0.00031466025,0.0002729946,0.000035057554,0.000031130712,0.0004390152,0.00031247872,0.000021777005],"category_scores_gemma":[0.0003525102,0.000209441,0.00013155035,0.00071979844,0.00013267931,0.000006040912,0.00017258785,0.00023275695,0.000011294737],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018411682,0.00012163175,0.007938835,0.000009319718,0.000018919385,0.000012024793,0.00006112102,0.0013473843,0.97852206,0.00023680994,0.00015548732,0.011557995],"study_design_scores_gemma":[0.0011845676,0.00032401521,0.029724574,0.000046803045,0.000035837824,0.000037063477,0.0002023666,0.0034054613,0.9543759,0.003053755,0.007036224,0.00057338644],"about_ca_topic_score_codex":0.00016638485,"about_ca_topic_score_gemma":0.00036894745,"teacher_disagreement_score":0.19968231,"about_ca_system_score_codex":0.00008078286,"about_ca_system_score_gemma":0.000046910547,"threshold_uncertainty_score":0.8540756},"labels":[],"label_agreement":null},{"id":"W916572488","doi":"","title":"Evolution by Computational Selection","year":2015,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; McGill University","funders":"","keywords":"Knapsack problem; Solver; Degree (music); Biological network; Degree distribution; Computer science; Network topology; Reduction (mathematics); Computational complexity theory; Representation (politics); Evolutionary algorithm; Mathematics; Random graph; Mathematical optimization; Algorithm; Theoretical computer science; Graph; Complex network; Combinatorics","score_opus":0.02745180192094429,"score_gpt":0.17825863891012833,"score_spread":0.15080683698918404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W916572488","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":[0.81011724,0.00038622163,0.18844093,0.00001762538,0.00015017313,0.0001156114,0.000034550536,0.00003244512,0.0007052199],"genre_scores_gemma":[0.9954705,0.000043372598,0.00022668038,0.000027561324,0.00021168154,7.447322e-7,0.0010230078,0.0000206175,0.0029757875],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99884,0.000115173585,0.0001225515,0.00066476624,0.00007037251,0.00018716433],"domain_scores_gemma":[0.9991229,0.0000049777627,0.00015540849,0.00031386255,0.00028264953,0.00012017895],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00014939775,0.00019934257,0.00016805378,0.00008564905,0.00008278779,0.00001956828,0.00024609294,0.00037345328,0.000023175173],"category_scores_gemma":[0.000014815681,0.00025761526,0.00016518033,0.00021880334,0.000069090784,0.000003873443,0.00034145723,0.00017915713,0.000031633568],"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":[0.000041652685,0.000042512398,0.006929394,0.00001167685,0.00017430643,0.0000027223791,0.0000050323138,0.96437454,0.002154332,0.00074088376,0.025483247,0.000039725794],"study_design_scores_gemma":[0.0009615716,0.00017499091,0.0032329261,0.000027274466,0.00046522403,0.000010856253,0.00006877567,0.95140123,0.0019230774,0.02952024,0.011310135,0.00090372015],"about_ca_topic_score_codex":0.000060039747,"about_ca_topic_score_gemma":0.00005447805,"teacher_disagreement_score":0.18821426,"about_ca_system_score_codex":0.00020184428,"about_ca_system_score_gemma":0.00026093028,"threshold_uncertainty_score":0.9999876},"labels":[],"label_agreement":null},{"id":"W97890272","doi":"10.1007/0-387-28111-8_13","title":"Genetic Programming Inside a Cell","year":2006,"lang":"en","type":"book-chapter","venue":"Kluwer Academic Publishers eBooks","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"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 Calgary","funders":"","keywords":"lac operon; Operon; Genetic programming; In silico; Gene; Computational biology; Biology; Computer science; Genetics; Escherichia coli; Artificial intelligence","score_opus":0.009537106723398962,"score_gpt":0.21078359023500287,"score_spread":0.2012464835116039,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W97890272","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006294503,0.008553036,0.00053821417,0.00008039549,0.0004770932,0.00075331196,0.000027631213,0.00012861661,0.9831472],"genre_scores_gemma":[0.05659096,0.00008480703,0.001432659,0.0005876031,0.0024786673,0.00008454967,0.00054028985,0.00034077573,0.9378597],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99623376,0.00005765734,0.0008847728,0.0013647134,0.00060919207,0.0008499057],"domain_scores_gemma":[0.9976287,0.000016451375,0.0006084114,0.0011844744,0.0002212687,0.0003407182],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0003326962,0.0008637969,0.00066382776,0.0003318925,0.00015170232,0.00023517397,0.001013713,0.0025459065,0.00009763616],"category_scores_gemma":[0.000026120912,0.0009279683,0.0006577292,0.00004992315,0.0003149224,0.000013349282,0.00052161596,0.0013292705,0.000068628],"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":[0.000060885854,0.000030024325,0.0007328653,0.00016733256,0.0007889845,0.000072270006,0.00006610562,0.0005410672,0.017698744,0.00046002967,0.92814857,0.05123313],"study_design_scores_gemma":[0.00044270162,0.00009044889,0.00007685847,0.00006165157,0.0003909954,0.000040364557,0.00001074951,0.000031053576,0.0025859873,0.0013620786,0.9939138,0.0009932993],"about_ca_topic_score_codex":0.000028868826,"about_ca_topic_score_gemma":0.000036317164,"teacher_disagreement_score":0.06576525,"about_ca_system_score_codex":0.00011692625,"about_ca_system_score_gemma":0.0004170948,"threshold_uncertainty_score":0.9993171},"labels":[],"label_agreement":null}]}