{"meta":{"query_hash":"6bb64e2cbecb","filters":{"venue":"In Silico Biology"},"cohort_total":9,"direct_labels_cover":0,"predictions_cover":9,"exported":9,"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/6bb64e2cbecb","api":"https://metacan.xera.ac/api/v1/cohort?venue=In+Silico+Biology"},"results":[{"id":"W1517465908","doi":"10.3233/ci-2008-0016","title":"ChemModLab: A Web-Based Cheminformatics Modeling Laboratory","year":2012,"lang":"en","type":"article","venue":"In Silico Biology","topic":"Computational Drug Discovery Methods","field":"Computer Science","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 British Columbia","funders":"National Human Genome Research Institute; National Institute of Mental Health; National Institutes of Health; North Carolina State University","keywords":"Computer science; Cheminformatics; Toolbox; Quantitative structure–activity relationship; Data mining; Set (abstract data type); Visualization; Software; Machine learning; Applicability domain; Domain (mathematical analysis); Test set; Artificial intelligence; Bioinformatics","score_opus":0.029505267912682466,"score_gpt":0.31578619926535073,"score_spread":0.28628093135266824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1517465908","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003467969,0.0014726222,0.58551323,0.0013595365,0.00044960243,0.0005970269,0.02979898,0.34046188,0.036879152],"genre_scores_gemma":[0.044836275,0.0047470704,0.75315833,0.0026970126,0.00040340383,0.003932286,0.097755425,0.061264727,0.031205418],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997981,0.00039661457,0.000121238365,0.0004810914,0.00087487814,0.00014514028],"domain_scores_gemma":[0.99666435,0.0012856536,0.00025926184,0.0007035401,0.0006925495,0.0003946666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004414795,0.0029964794,0.002871026,0.0020655007,0.0009964259,0.0045879083,0.008839944,0.0021434654,0.085290454],"category_scores_gemma":[0.006259216,0.0018395467,0.002412368,0.0026739123,0.000933763,0.0042054798,0.0034892554,0.0049945135,0.051779535],"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":[0.0012499536,0.0007119203,0.002406469,0.003186452,0.000658749,0.00067641004,0.0003517851,0.059910715,0.023910005,0.06291753,0.6397741,0.20424591],"study_design_scores_gemma":[0.0013528293,0.00030142607,0.0009678992,0.000307815,0.00021785553,0.00041401488,0.0000665543,0.29259667,0.026155157,0.039888244,0.63752395,0.00020753985],"about_ca_topic_score_codex":0.0025096915,"about_ca_topic_score_gemma":0.002127629,"teacher_disagreement_score":0.085290454,"about_ca_system_score_codex":0.0016673013,"about_ca_system_score_gemma":0.0045671235,"threshold_uncertainty_score":0.285325},"labels":[],"label_agreement":null},{"id":"W1589936144","doi":"10.3233/isb-2010-0435","title":"A Computational Approach for Identification of Epitopes in Dengue Virus Envelope Protein: A Step Towards Designing a Universal Dengue Vaccine Targeting Endemic Regions","year":2010,"lang":"en","type":"article","venue":"In Silico Biology","topic":"vaccines and immunoinformatics approaches","field":"Biochemistry, Genetics and Molecular Biology","cited_by":73,"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":"Epitope; Dengue virus; Dengue fever; Virology; Immunogenicity; Dengue vaccine; Biology; Population; Peptide vaccine; Human leukocyte antigen; Flavivirus; Virus; Antigen; Genetics; Medicine","score_opus":0.01574742297355007,"score_gpt":0.25792449261851896,"score_spread":0.24217706964496888,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1589936144","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4786459,0.0010378184,0.50748473,0.0012867027,0.0000856942,0.0002701949,0.00094635674,0.001083515,0.009159197],"genre_scores_gemma":[0.78966534,0.0006586122,0.20603383,0.00020532029,0.000029428185,0.0004358058,0.0009343067,0.0000846704,0.0019526767],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999131,0.000033742766,0.000005634638,0.000012757597,0.00002121483,0.000013632815],"domain_scores_gemma":[0.9997818,0.00013686379,0.000016152884,0.000013119984,0.00003381016,0.000018223356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034478577,0.00044239152,0.0006149931,0.0005281833,0.00042655235,0.00059523544,0.0005755794,0.00068008166,0.002019305],"category_scores_gemma":[0.0010202597,0.00031123922,0.00067011063,0.0004621703,0.00019868085,0.00043805706,0.00037444796,0.00051383453,0.0002262244],"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":[0.00010989158,0.00014487965,0.0039049448,0.00017347051,0.00009141158,0.0001832048,0.00005906232,0.9692057,0.004349172,0.0039287168,0.00059176295,0.017257849],"study_design_scores_gemma":[0.000020520896,0.00003562175,0.00033381797,0.000009555744,0.000017326864,0.000026080947,0.000020118443,0.9965714,0.0005817174,0.0019042764,0.00047567746,0.0000039150555],"about_ca_topic_score_codex":0.003747492,"about_ca_topic_score_gemma":0.00432391,"teacher_disagreement_score":0.003747492,"about_ca_system_score_codex":0.00034213258,"about_ca_system_score_gemma":0.001269382,"threshold_uncertainty_score":0.0074513555},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99147534,0.00006009817,0.008059913,0.000021235883,0.0000016623936,0.0000030228925,0.000080257116,0.00007816049,0.00022035281],"genre_scores_gemma":[0.99667275,0.000028737171,0.0030344068,0.000007193988,0.0000013584274,0.00000520393,0.00011823381,0.000023578552,0.00010844241],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99946064,0.00007952057,0.000029441724,0.00015351483,0.00021356826,0.00006327948],"domain_scores_gemma":[0.9977264,0.001119635,0.0006060401,0.00028781235,0.00016152493,0.00009871599],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048066775,0.0002245979,0.00028958655,0.0004517669,0.00016248987,0.0005263421,0.00023175291,0.00029357764,0.00028440866],"category_scores_gemma":[0.0035267116,0.00028701877,0.00010736779,0.0003596547,0.0005190797,0.0003970596,0.0003353316,0.00034892678,0.000087302134],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035470352,0.000038331786,0.06631013,0.000063994456,0.00005236402,0.00010333626,0.00021843868,0.028215036,0.88294095,0.0011291299,0.00009680187,0.020476772],"study_design_scores_gemma":[0.000023909939,0.0002286607,0.52813774,0.000017982742,0.00005108006,0.000388239,0.00014022931,0.16062552,0.30669805,0.0028891144,0.0007010536,0.000098505596],"about_ca_topic_score_codex":0.000968225,"about_ca_topic_score_gemma":0.0016955013,"teacher_disagreement_score":0.000968225,"about_ca_system_score_codex":0.00043230478,"about_ca_system_score_gemma":0.0002068309,"threshold_uncertainty_score":0.0031365752},"labels":[],"label_agreement":null},{"id":"W1782187318","doi":"10.3233/isb-00190","title":"Evolutionary Analysis of Human Vascular Endothelial Growth Factor, Angiopoietin, and Tyrosine Endothelial Kinase Involved in Angiogenesis and Immunity","year":2005,"lang":"en","type":"article","venue":"In Silico Biology","topic":"Angiogenesis and VEGF in Cancer","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":"McMaster University","keywords":"Angiogenesis; Vascular endothelial growth factor B; Vascular endothelial growth factor; Angiopoietin; Vascular endothelial growth factor A; Vascular endothelial growth factor C; Biology; Cell biology; Receptor tyrosine kinase; Tyrosine kinase; Cancer research; Immunology; Signal transduction; VEGF receptors","score_opus":0.0137337628381714,"score_gpt":0.26753819980265625,"score_spread":0.25380443696448485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1782187318","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9949409,0.0011252285,0.0018772893,0.000045120556,0.000009602728,0.000014813823,0.00025717614,0.000009036737,0.0017208831],"genre_scores_gemma":[0.9929965,0.0008690055,0.0036526741,0.000046450255,0.000011012635,0.000013542414,0.0013510642,0.000011531703,0.0010482891],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998512,0.000036512476,0.000009928722,0.00003734236,0.000037965954,0.000027022546],"domain_scores_gemma":[0.99983597,0.000038947812,0.000046477795,0.000010470252,0.000029488756,0.000038715505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002244521,0.00017429338,0.00024223677,0.00089026825,0.00036679424,0.00029595147,0.00012544022,0.00020818102,0.00057895604],"category_scores_gemma":[0.00039066904,0.00008028942,0.00024544576,0.00086163764,0.00016403869,0.00017013452,0.00017382584,0.00020467817,0.00021107918],"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":[0.0014669746,0.00021538603,0.13401222,0.00038449492,0.00024745756,0.0024186047,0.0006503331,0.0030512842,0.79904866,0.002930395,0.00055361906,0.055020582],"study_design_scores_gemma":[0.000056420657,0.00057987106,0.8049037,0.00008122654,0.0003750163,0.00981727,0.00057920784,0.019364998,0.122113906,0.0013871226,0.040699456,0.000041791387],"about_ca_topic_score_codex":0.001084292,"about_ca_topic_score_gemma":0.00089762965,"teacher_disagreement_score":0.001084292,"about_ca_system_score_codex":0.0002883666,"about_ca_system_score_gemma":0.0002573009,"threshold_uncertainty_score":0.0021559},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017616425,0.835128,0.14431694,0.0029809396,0.0010678907,0.000034241948,0.00018794643,0.00019963698,0.014322736],"genre_scores_gemma":[0.018079938,0.9482824,0.02868929,0.00087024295,0.001180776,0.000094346615,0.0002103794,0.00005888378,0.0025336903],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99966574,0.000107706,0.000029885554,0.00007342096,0.00010669766,0.000016621321],"domain_scores_gemma":[0.99848324,0.0012277266,0.00006244338,0.000086762375,0.00011242596,0.000027358357],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014650584,0.00155472,0.0016263315,0.001719419,0.00034394895,0.0014604353,0.0019147889,0.001681037,0.0023540615],"category_scores_gemma":[0.003183367,0.00063790916,0.0009878215,0.0014036607,0.0018880437,0.0032208702,0.0010891743,0.0030551127,0.0017209935],"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":[0.000036393045,0.00010859943,0.0005348236,0.01313918,0.00023830685,0.00035751567,0.0002807269,0.05523568,0.0033684173,0.5529315,0.018101748,0.35566702],"study_design_scores_gemma":[0.000021039867,0.00012267163,0.0005363828,0.0032890378,0.00019522796,0.00090937916,0.00011859052,0.037246782,0.0022620342,0.40287322,0.55228674,0.00013892086],"about_ca_topic_score_codex":0.001095379,"about_ca_topic_score_gemma":0.0008648122,"teacher_disagreement_score":0.0023540615,"about_ca_system_score_codex":0.0012043759,"about_ca_system_score_gemma":0.0011547436,"threshold_uncertainty_score":0.008738339},"labels":[],"label_agreement":null},{"id":"W1913243285","doi":"10.3233/isb-00109","title":"Investigation of Interaction between Pax-5 Isoforms and Thioredoxin Using De Novo Modelling Methods","year":2003,"lang":"en","type":"article","venue":"In Silico Biology","topic":"Redox biology and oxidative stress","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 de Moncton","funders":"Canadian Institutes of Health Research","keywords":"Gene isoform; Computational biology; Thioredoxin; Biology; Biochemistry; Gene","score_opus":0.07025161075425523,"score_gpt":0.3792424259931232,"score_spread":0.30899081523886796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1913243285","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6548772,0.0015875322,0.31942594,0.00042398434,0.00014958496,0.00023477872,0.0018413606,0.0008434903,0.020616239],"genre_scores_gemma":[0.8654818,0.0016850559,0.12615077,0.00007206358,0.000035437413,0.0004966726,0.0017349495,0.000356275,0.0039870646],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997876,0.00004923095,0.000010887269,0.000035271325,0.00007300983,0.000043942866],"domain_scores_gemma":[0.9994999,0.00028061995,0.00006671743,0.000039709455,0.000073550334,0.000039532504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064586004,0.0009429142,0.0009782303,0.0005908605,0.0006880039,0.0010536917,0.0015828469,0.0014599409,0.004464074],"category_scores_gemma":[0.0009322389,0.0008220103,0.0013876277,0.0005118235,0.00034801668,0.000823301,0.00057317474,0.000984091,0.0007847452],"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":[0.00010534886,0.00010094325,0.0016946823,0.00032175137,0.00012862809,0.00048251526,0.00010296314,0.9630127,0.018789517,0.009884349,0.0002984863,0.0050780866],"study_design_scores_gemma":[0.000021438897,0.00003392749,0.00029700238,0.000012810359,0.000017962819,0.00005347524,0.00002429855,0.9943299,0.0026192127,0.0011290164,0.0014494688,0.000011535169],"about_ca_topic_score_codex":0.0051553124,"about_ca_topic_score_gemma":0.0042367885,"teacher_disagreement_score":0.0051553124,"about_ca_system_score_codex":0.0010457166,"about_ca_system_score_gemma":0.001085435,"threshold_uncertainty_score":0.014933765},"labels":[],"label_agreement":null},{"id":"W2282550052","doi":"10.3233/isb-140464","title":"Exploiting stoichiometric redundancies for computational efficiency and network reduction","year":2015,"lang":"en","type":"review","venue":"In Silico Biology","topic":"Microbial Metabolic Engineering and Bioproduction","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 Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Flux balance analysis; Reduction (mathematics); Computer science; Steady state (chemistry); Macro; Matrix (chemical analysis); Metabolic network; Mathematical optimization; Network analysis; Topology (electrical circuits); Network topology; Mathematics; Chemistry; Physics","score_opus":0.04090579175893761,"score_gpt":0.33704803787312143,"score_spread":0.2961422461141838,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2282550052","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0037187322,0.686696,0.28138256,0.001649446,0.0007670979,0.00009400873,0.00024738113,0.00052194676,0.024922825],"genre_scores_gemma":[0.05654145,0.76262176,0.17037167,0.00052401295,0.0008905782,0.00030533443,0.0006244602,0.00020355552,0.007917195],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995912,0.000100984034,0.00003311605,0.00008678031,0.00016209867,0.000025846624],"domain_scores_gemma":[0.999483,0.00031178264,0.00003673653,0.000054744578,0.000096002426,0.00001766554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010251245,0.001172431,0.0014362452,0.0019523407,0.0003012335,0.0013413982,0.0016859953,0.0009332373,0.003454464],"category_scores_gemma":[0.0016737968,0.00060252956,0.001055982,0.0023483136,0.0010434595,0.0020772377,0.0009515356,0.0017964347,0.0019668122],"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":[0.000059657836,0.00006573805,0.00032870096,0.007229883,0.0002691664,0.00021601537,0.000084072555,0.05413433,0.007509409,0.19928078,0.012031577,0.71879065],"study_design_scores_gemma":[0.000061035964,0.0001642273,0.0007483716,0.0015548691,0.00024338739,0.0010254221,0.000078926096,0.09177642,0.009300694,0.2437703,0.65115505,0.00012136542],"about_ca_topic_score_codex":0.001156853,"about_ca_topic_score_gemma":0.0013242624,"teacher_disagreement_score":0.003454464,"about_ca_system_score_codex":0.0009842335,"about_ca_system_score_gemma":0.0010644682,"threshold_uncertainty_score":0.011556387},"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":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.063222185,0.0012807202,0.914207,0.0012714912,0.00011560967,0.000121200996,0.0012019239,0.00044573963,0.018134044],"genre_scores_gemma":[0.8135157,0.0046757697,0.15680452,0.00058127777,0.00015141066,0.0009269395,0.0013890276,0.0002816242,0.021673746],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99974483,0.00007909566,0.000014557321,0.00007128545,0.00005506643,0.0000351364],"domain_scores_gemma":[0.9993649,0.00036436055,0.00011522358,0.000036876234,0.00008105847,0.00003764927],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057199865,0.000554375,0.00065866765,0.0007666178,0.00050051545,0.0012904941,0.0014880558,0.0015465034,0.0030984578],"category_scores_gemma":[0.0021003606,0.00034983642,0.0009189962,0.0007848473,0.00077181816,0.0013616489,0.00076289015,0.00086808525,0.00072391564],"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":[0.000009607696,0.000018297646,0.0015127234,0.000071758106,0.00002528781,0.000058785266,0.000102651,0.8994118,0.0029304235,0.089978576,0.0007749181,0.005105145],"study_design_scores_gemma":[0.000004404591,0.0000071568807,0.00020466711,0.000008876093,0.0000084922085,0.000025442889,0.000018339339,0.9803064,0.00038404227,0.016499758,0.0025253512,0.0000070038577],"about_ca_topic_score_codex":0.012757181,"about_ca_topic_score_gemma":0.0063587027,"teacher_disagreement_score":0.012757181,"about_ca_system_score_codex":0.0017371988,"about_ca_system_score_gemma":0.0011983269,"threshold_uncertainty_score":0.02536583},"labels":[],"label_agreement":null},{"id":"W4200068800","doi":"10.3233/isb-210233","title":"Lattice-based Monte Carlo simulation of the effects of nutrient concentration and magnetic field exposure on yeast colony growth and morphology","year":2021,"lang":"en","type":"article","venue":"In Silico Biology","topic":"Fungal and yeast genetics research","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 Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; University of Alberta","keywords":"Yeast; Monte Carlo method; Biology; Biological system; Ploidy; Mathematics; Genetics; Statistics","score_opus":0.006980149654771075,"score_gpt":0.25382522618885806,"score_spread":0.246845076534087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200068800","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.898662,0.0003258245,0.08758546,0.00050214614,0.00009474008,0.000084892956,0.00065966474,0.00037037185,0.011714926],"genre_scores_gemma":[0.9676119,0.00013769884,0.030608626,0.00007523804,0.000011921553,0.00011607376,0.00026874745,0.000053510234,0.0011163887],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998523,0.000051939507,0.000007814369,0.000018959885,0.000038139715,0.00003075809],"domain_scores_gemma":[0.99835783,0.001146965,0.000109673856,0.00006806701,0.00018897896,0.0001283497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004947822,0.00028669988,0.0006287645,0.00047260235,0.0005716804,0.0006023607,0.00092420285,0.0010590734,0.002015885],"category_scores_gemma":[0.0021195456,0.0003756278,0.000572775,0.00053843064,0.00060526177,0.00036063988,0.00038786582,0.0006251116,0.00015459256],"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":[0.000025981826,0.000025062227,0.000744786,0.000015402564,0.000012123429,0.00002330551,0.000014106286,0.9959304,0.0008212641,0.0018146839,0.00007417256,0.000498785],"study_design_scores_gemma":[0.0000093217395,0.000005901353,0.00010056022,0.0000013368314,0.0000023036976,0.0000031235918,0.000004486106,0.99931943,0.00020268865,0.00028312192,0.000065198576,0.0000025844786],"about_ca_topic_score_codex":0.025221484,"about_ca_topic_score_gemma":0.020008517,"teacher_disagreement_score":0.025221484,"about_ca_system_score_codex":0.001106399,"about_ca_system_score_gemma":0.0013520909,"threshold_uncertainty_score":0.05014938},"labels":[],"label_agreement":null}]}