{"meta":{"query_hash":"f642fb22983b","filters":{"venue":"Sustainable Computing Informatics and Systems"},"cohort_total":13,"direct_labels_cover":0,"predictions_cover":13,"exported":13,"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/f642fb22983b","api":"https://metacan.xera.ac/api/v1/cohort?venue=Sustainable+Computing+Informatics+and+Systems"},"results":[{"id":"W2028641944","doi":"10.1016/j.suscom.2011.11.001","title":"Optimizing Cloud providers revenues via energy efficient server allocation","year":2011,"lang":"en","type":"article","venue":"Sustainable Computing Informatics and Systems","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":55,"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":"European Regional Development Fund","keywords":"Cloud computing; Server; Data center; Lease; Revenue; Computer science; Service provider; Renting; Environmental economics; Operations research; Order (exchange); Database; Service (business); Computer network; Business; Finance; Economics; Operating system; Engineering; Marketing","score_opus":0.012324258606661906,"score_gpt":0.200490233173688,"score_spread":0.1881659745670261,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028641944","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":[0.48538417,0.0009400882,0.45248905,0.0027024997,0.000291519,0.00026867405,0.00049788126,0.0011356695,0.056290455],"genre_scores_gemma":[0.983411,0.00014121358,0.012680186,0.00004330089,0.00003531043,0.00001915015,0.000048276437,0.00007040289,0.003551179],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99948573,0.00017008421,0.00001362057,0.000046979338,0.00010902927,0.00017459672],"domain_scores_gemma":[0.9993799,0.0003041094,0.00006557636,0.00004991914,0.00013082102,0.00006976688],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080214697,0.0005451649,0.00057941617,0.00063430594,0.00045474272,0.0015523368,0.00069507543,0.0005386,0.0048511056],"category_scores_gemma":[0.0025784469,0.00029635523,0.00020412683,0.0014027007,0.00029157597,0.0015310263,0.00060295063,0.00063607906,0.00059295405],"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":[0.000494987,0.00030363514,0.0028985396,0.00008313686,0.000050275816,0.00014575508,0.00003638519,0.8298321,0.015726246,0.045092363,0.0062953173,0.099041246],"study_design_scores_gemma":[0.000029618206,0.000035587636,0.0010162537,0.000005379318,0.000020682954,0.00003755697,0.000041117593,0.9782138,0.0044387165,0.014722496,0.0014307086,0.000008012684],"about_ca_topic_score_codex":0.0020434172,"about_ca_topic_score_gemma":0.004463112,"teacher_disagreement_score":0.0048511056,"about_ca_system_score_codex":0.001032931,"about_ca_system_score_gemma":0.0017054911,"threshold_uncertainty_score":0.016228557},"labels":[],"label_agreement":null},{"id":"W2274590954","doi":"10.1016/j.suscom.2016.01.004","title":"A simple and robust approach to energy disaggregation in the presence of outliers","year":2016,"lang":"en","type":"article","venue":"Sustainable Computing Informatics and Systems","topic":"Smart Grid Energy Management","field":"Engineering","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 Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; Natural Science Foundation of Ningbo","keywords":"Computer science; Outlier; Overhead (engineering); Cluster analysis; Data mining; TRACE (psycholinguistics); Energy consumption; Energy (signal processing); Event (particle physics); Data cleansing; Anomaly detection; Hidden Markov model; Markov chain; Artificial intelligence; Machine learning; Engineering; Data quality; Mathematics","score_opus":0.008811287612282077,"score_gpt":0.18599460527200934,"score_spread":0.17718331765972725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2274590954","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0059516225,0.000113725335,0.9924298,0.00009975356,0.00007135411,0.000036769412,0.00011514426,0.00058578845,0.0005960049],"genre_scores_gemma":[0.46578637,0.0002538696,0.5280394,0.0001512426,0.00036350463,0.00012669517,0.00077670545,0.00034809718,0.0041540703],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99808735,0.00040977882,0.0001397321,0.0004792694,0.0007381515,0.00014574833],"domain_scores_gemma":[0.9976928,0.0008148885,0.00029575347,0.00057112833,0.0005421725,0.00008312313],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017704472,0.0014399964,0.002222874,0.0011549267,0.0008063475,0.0017664656,0.0015581792,0.0013231579,0.001760687],"category_scores_gemma":[0.007941299,0.000628707,0.0012102633,0.001419049,0.00068294496,0.0016958913,0.0022215038,0.0021103444,0.0009373445],"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":[0.00053682434,0.0001730432,0.0027160463,0.00020170615,0.00034902256,0.00040417208,0.00020105758,0.6275404,0.029691514,0.01773556,0.004912447,0.31553823],"study_design_scores_gemma":[0.000011484269,0.000041090367,0.000507103,0.0000059405193,0.000016411093,0.000065278036,0.000017827399,0.9877828,0.003120288,0.0068817423,0.0015291235,0.00002084902],"about_ca_topic_score_codex":0.0038883016,"about_ca_topic_score_gemma":0.0051343623,"teacher_disagreement_score":0.0038883016,"about_ca_system_score_codex":0.0004948815,"about_ca_system_score_gemma":0.0011567472,"threshold_uncertainty_score":0.009363174},"labels":[],"label_agreement":null},{"id":"W3217655315","doi":"10.1016/j.suscom.2021.100617","title":"Modeling and evaluation of dispatching policies in IaaS cloud data centers using SANs","year":2021,"lang":"en","type":"article","venue":"Sustainable Computing Informatics and Systems","topic":"Cloud Computing and Resource Management","field":"Computer Science","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":"","keywords":"CloudSim; Cloud computing; Computer science; Data center; Distributed computing; Service-level agreement; Scheduling (production processes); Quality of service; Operating system; Computer network; Operations management; Engineering","score_opus":0.051090300136524915,"score_gpt":0.3003796007054221,"score_spread":0.24928930056889717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3217655315","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":[0.92702895,0.00031678283,0.04475152,0.0011732312,0.00013278998,0.00012358019,0.00048819988,0.00030809417,0.02567684],"genre_scores_gemma":[0.9945457,0.000085565196,0.0034291279,0.000030324,0.0000102101385,0.00002250108,0.00008501,0.000028372291,0.0017632524],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99941707,0.00026501276,0.000023834207,0.00006723558,0.00007581687,0.00015116007],"domain_scores_gemma":[0.99787045,0.0012193831,0.00018102245,0.000093021496,0.00044533797,0.00019065886],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016063702,0.00078610325,0.0008918713,0.00060852146,0.0009394156,0.0017144996,0.0011084666,0.0009956335,0.002515448],"category_scores_gemma":[0.0033070305,0.0005822218,0.0006831344,0.000691023,0.00082491076,0.0011629957,0.0006676837,0.0013428817,0.00019936876],"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":[0.000020544856,0.000017386346,0.00053610234,0.0000057173606,0.0000038821195,0.000013365631,0.000007889078,0.9978815,0.00008495165,0.001029683,0.00009059638,0.00030844557],"study_design_scores_gemma":[0.000003122793,0.000007842035,0.0001095774,0.0000010569245,0.0000020581806,0.0000014993589,0.000013102164,0.99956137,0.000054339755,0.00018596083,0.000058574242,0.00000139103],"about_ca_topic_score_codex":0.08895644,"about_ca_topic_score_gemma":0.04468827,"teacher_disagreement_score":0.08895644,"about_ca_system_score_codex":0.0033388122,"about_ca_system_score_gemma":0.003202147,"threshold_uncertainty_score":0.17687732},"labels":[],"label_agreement":null},{"id":"W4224267687","doi":"10.1016/j.suscom.2022.100743","title":"Improving sugarcane production in saline soils with Machine Learning and the Internet of Things","year":2022,"lang":"en","type":"article","venue":"Sustainable Computing Informatics and Systems","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brandon University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Sugar; Agriculture; Leaching (pedology); Hectare; Agricultural engineering; Sustainability; Soil salinity; Environmental science; Business; Soil water; Geography; Engineering; Biology","score_opus":0.0046415002942509385,"score_gpt":0.17352669600674653,"score_spread":0.16888519571249558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224267687","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":[0.8611965,0.0018491817,0.115292974,0.0022882915,0.00015613507,0.00008452201,0.0005460361,0.0006126779,0.017973648],"genre_scores_gemma":[0.9754952,0.0008076968,0.022005837,0.00010721056,0.000014838386,0.000016774535,0.00019209561,0.000022193673,0.001338097],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998497,0.00003300016,0.0000076111883,0.000026656486,0.00005102433,0.000031948854],"domain_scores_gemma":[0.999824,0.000054002176,0.00002543735,0.000013253038,0.000069615075,0.000013750494],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030099752,0.0003069057,0.00028062993,0.00037588537,0.00029637612,0.00092600274,0.0003374873,0.00038576763,0.0010417089],"category_scores_gemma":[0.0005010771,0.000089474415,0.00028948992,0.0011742427,0.00025808884,0.0013570982,0.00038813232,0.00030746008,0.00016870085],"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":[0.00041585037,0.0005341005,0.047085818,0.0008168266,0.0003030013,0.00049544073,0.00020301866,0.2304279,0.17519586,0.0070833885,0.004035343,0.53340346],"study_design_scores_gemma":[0.00007209097,0.0005714911,0.05086072,0.00010097792,0.00032811338,0.00014726892,0.0020280313,0.78125316,0.12595072,0.017840156,0.020751778,0.00009554036],"about_ca_topic_score_codex":0.011388413,"about_ca_topic_score_gemma":0.023695437,"teacher_disagreement_score":0.011388413,"about_ca_system_score_codex":0.0005537046,"about_ca_system_score_gemma":0.00081893377,"threshold_uncertainty_score":0.022644281},"labels":[],"label_agreement":null},{"id":"W4362580023","doi":"10.1016/j.suscom.2023.100867","title":"An efficient edge computing management mechanism for sustainable smart cities","year":2023,"lang":"en","type":"article","venue":"Sustainable Computing Informatics and Systems","topic":"IoT and Edge/Fog Computing","field":"Computer Science","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":"Royal Military College of Canada","funders":"","keywords":"Computer science; Server; Edge computing; Enhanced Data Rates for GSM Evolution; Smart city; Service (business); Mechanism (biology); Computer security; Internet of Things; Computer network; Telecommunications; Business","score_opus":0.013717480090452169,"score_gpt":0.24421826744848463,"score_spread":0.23050078735803245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362580023","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":[0.12347796,0.0005088206,0.8409898,0.0013690661,0.000679114,0.0004924217,0.00028132135,0.0055834535,0.026618063],"genre_scores_gemma":[0.8908847,0.00018893275,0.096680515,0.00030195614,0.000100377314,0.0001282333,0.0002147606,0.00008172183,0.011418813],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99967873,0.000049052247,0.000021644237,0.000063631356,0.00010025417,0.00008671867],"domain_scores_gemma":[0.9995956,0.00006520863,0.000032326887,0.000109041255,0.00015289923,0.00004502613],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057108625,0.0004228171,0.00045950778,0.0007586259,0.0011288804,0.001841509,0.0016106656,0.0009752849,0.0047606733],"category_scores_gemma":[0.00086577644,0.00024771114,0.0002836147,0.0006933017,0.00033432353,0.002436744,0.0014571886,0.0006900481,0.000895546],"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":[0.001266937,0.0012926584,0.0029418229,0.00027408762,0.00015177319,0.0008036861,0.00038891158,0.17408068,0.11044667,0.27627295,0.042946566,0.3891333],"study_design_scores_gemma":[0.000069175614,0.0001978705,0.00080773013,0.000021928276,0.0000680255,0.00019217774,0.00015668196,0.9087035,0.027702803,0.033932157,0.028086495,0.000061478204],"about_ca_topic_score_codex":0.0013863504,"about_ca_topic_score_gemma":0.0020878708,"teacher_disagreement_score":0.0047606733,"about_ca_system_score_codex":0.0006496125,"about_ca_system_score_gemma":0.0009614982,"threshold_uncertainty_score":0.015926063},"labels":[],"label_agreement":null},{"id":"W4362672441","doi":"10.1016/j.suscom.2023.100868","title":"Multivariate time-series sensor vital sign forecasting of cardiovascular and chronic respiratory diseases","year":2023,"lang":"en","type":"article","venue":"Sustainable Computing Informatics and Systems","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","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":"Brandon University","funders":"Høgskulen på Vestlandet","keywords":"Computer science; Machine learning; Artificial intelligence; Feature (linguistics); Random forest; Vital signs; Support vector machine; Naive Bayes classifier; Feature engineering; Medicine; Deep learning","score_opus":0.07856979135498487,"score_gpt":0.36249202610573084,"score_spread":0.28392223475074596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362672441","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":[0.9606038,0.00043028363,0.035388764,0.00031024666,0.00011963984,0.000018707768,0.001954233,0.00022912813,0.0009451681],"genre_scores_gemma":[0.99672663,0.0001184804,0.0020201332,0.000012553691,0.000027317858,0.0000048222882,0.00076264626,0.000005233696,0.0003222576],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99985147,0.000028983171,0.000014218227,0.000043100164,0.000036068246,0.000026187336],"domain_scores_gemma":[0.99952316,0.00021391531,0.000078482786,0.000044247183,0.000105958694,0.000034278713],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005074208,0.00041349384,0.00036841698,0.0007703196,0.00010913861,0.00038855936,0.00024613217,0.00032748125,0.00088461774],"category_scores_gemma":[0.001982699,0.000099420104,0.0004119877,0.00077147153,0.000072690425,0.00043901853,0.00020177051,0.00044351598,0.0002763383],"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":[0.0011853159,0.00065019453,0.49242282,0.00013345413,0.00040441033,0.00034549442,0.00013451661,0.23063587,0.017829489,0.001173286,0.0044783102,0.2506068],"study_design_scores_gemma":[0.000007417152,0.000106747866,0.16741726,0.000010122461,0.000051876617,0.000090686684,0.000042814358,0.8298025,0.0015147362,0.0005220592,0.00041847306,0.000015432395],"about_ca_topic_score_codex":0.006950352,"about_ca_topic_score_gemma":0.0068947393,"teacher_disagreement_score":0.006950352,"about_ca_system_score_codex":0.00021312416,"about_ca_system_score_gemma":0.00032822046,"threshold_uncertainty_score":0.013819814},"labels":[],"label_agreement":null},{"id":"W4381384545","doi":"10.1016/j.suscom.2023.100888","title":"Energy and carbon-aware initial VM placement in geographically distributed cloud data centers","year":2023,"lang":"en","type":"article","venue":"Sustainable Computing Informatics and Systems","topic":"Cloud Computing and Resource Management","field":"Computer Science","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":"Polytechnique Montréal","funders":"","keywords":"CloudSim; Cloud computing; Data center; Computer science; Energy consumption; Efficient energy use; Greenhouse gas; Environmental economics; Carbon fibers; Virtual machine; Environmental science; Algorithm; Operating system; Engineering","score_opus":0.0156882160483962,"score_gpt":0.24205759500177326,"score_spread":0.22636937895337705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4381384545","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":[0.9474827,0.00031888427,0.04491511,0.0003946662,0.00007406709,0.000060413528,0.00013017937,0.00031986166,0.006304096],"genre_scores_gemma":[0.99629647,0.000013652727,0.003296789,0.000009291902,0.000002742001,0.0000035363628,0.000018986235,0.000007892465,0.00035074243],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997178,0.000059833565,0.000008814264,0.000059859703,0.000053835596,0.000099859215],"domain_scores_gemma":[0.99941266,0.00022130346,0.00006258363,0.000048457096,0.00017241557,0.00008263121],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046572843,0.0003067524,0.000376658,0.00040092436,0.00070596987,0.00087956054,0.0006277798,0.00046205643,0.0017469741],"category_scores_gemma":[0.0015644841,0.00017403366,0.00017200284,0.00043786858,0.00028850356,0.0006117279,0.00043490526,0.00025034137,0.00014099409],"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":[0.0008944209,0.00026461697,0.00891901,0.0000618073,0.000031166102,0.00018421096,0.000065935055,0.9378048,0.011882784,0.0022944652,0.0011958224,0.036400944],"study_design_scores_gemma":[0.000012939493,0.00006371891,0.0027278035,0.0000037167001,0.000011008931,0.000024392726,0.0001129177,0.99253005,0.0033121866,0.0010268918,0.00016918447,0.000005161781],"about_ca_topic_score_codex":0.007800887,"about_ca_topic_score_gemma":0.017679526,"teacher_disagreement_score":0.007800887,"about_ca_system_score_codex":0.0008931434,"about_ca_system_score_gemma":0.0011901944,"threshold_uncertainty_score":0.015510917},"labels":[],"label_agreement":null},{"id":"W4403583265","doi":"10.1016/j.suscom.2024.101044","title":"Energy-efficient and fault-tolerant routing mechanism for WSN using optimizer based deep learning model","year":2024,"lang":"en","type":"article","venue":"Sustainable Computing Informatics and Systems","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","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":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Mechanism (biology); Fault tolerance; Routing (electronic design automation); Distributed computing; Energy (signal processing); Parallel computing; Embedded system","score_opus":0.012923741848462691,"score_gpt":0.23003708456954486,"score_spread":0.21711334272108218,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403583265","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":[0.06809388,0.0005192803,0.92642796,0.0004109987,0.00007099504,0.00002939113,0.00007827529,0.00060383376,0.0037653875],"genre_scores_gemma":[0.9500329,0.00020042516,0.04592444,0.000099891455,0.00002320667,0.000041899522,0.00010468015,0.000036114856,0.0035363804],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998758,0.00001881452,0.000006935992,0.000038740276,0.00003205941,0.000027663495],"domain_scores_gemma":[0.99982435,0.000055982342,0.000024694244,0.00001905223,0.0000659515,0.000010013227],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034174323,0.00040763235,0.0005497503,0.00023009631,0.00024367504,0.0005197196,0.000926794,0.00051732693,0.0013069815],"category_scores_gemma":[0.000670594,0.00020204601,0.00032971174,0.00028651298,0.000289299,0.0007425199,0.00046277713,0.00068913586,0.00015174814],"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":[0.000054660584,0.000051551564,0.00063801394,0.000036829384,0.000030455478,0.000026845997,0.000018430936,0.94645035,0.0036917124,0.005435348,0.000944612,0.042621203],"study_design_scores_gemma":[0.0000012099155,0.000009121549,0.000048453676,0.0000010052892,0.0000026151076,0.0000030980598,0.0000013536434,0.9988438,0.0002669172,0.00076023134,0.000061110746,0.0000011098246],"about_ca_topic_score_codex":0.005617865,"about_ca_topic_score_gemma":0.0065878024,"teacher_disagreement_score":0.005617865,"about_ca_system_score_codex":0.0006621192,"about_ca_system_score_gemma":0.0006762123,"threshold_uncertainty_score":0.011170328},"labels":[],"label_agreement":null},{"id":"W4408107987","doi":"10.1016/j.suscom.2025.101107","title":"Secured user authentication and data sharing for mobile cloud computing using 2C-Cubehash and PWCC","year":2025,"lang":"en","type":"article","venue":"Sustainable Computing Informatics and Systems","topic":"Cryptography and Data Security","field":"Computer Science","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":"PotashCorp (Canada)","funders":"","keywords":"Computer science; Cloud computing; Authentication (law); Data sharing; Mobile cloud computing; Computer network; Computer security; Operating system","score_opus":0.02831750202727509,"score_gpt":0.31018741919642046,"score_spread":0.2818699171691454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408107987","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":[0.08394993,0.000777134,0.8954156,0.00075558823,0.00037238488,0.00033790644,0.00030561266,0.001528201,0.01655755],"genre_scores_gemma":[0.8408033,0.00027431318,0.15259182,0.00021380612,0.00013555175,0.00016623487,0.0003034541,0.000052495532,0.0054591163],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984377,0.0003240823,0.00008593569,0.0002804423,0.0005723156,0.00029959224],"domain_scores_gemma":[0.99883944,0.00024664425,0.00009083561,0.00036888197,0.00036221909,0.00009195089],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070659147,0.000364642,0.00078565243,0.0009809457,0.0015540465,0.0014274496,0.0008838725,0.000748795,0.003983057],"category_scores_gemma":[0.0019921863,0.00018105417,0.00062996784,0.0013889868,0.0010599388,0.001965187,0.0018309357,0.0009336121,0.0011628667],"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":[0.0020040402,0.0004282016,0.002306747,0.00035821318,0.00010619281,0.000986322,0.0006033504,0.08894308,0.087512255,0.33957446,0.015735654,0.46144146],"study_design_scores_gemma":[0.000074976444,0.00044506817,0.00097433745,0.000041478484,0.000036952468,0.0009035613,0.0002663637,0.875622,0.03074026,0.07593771,0.014831596,0.00012574297],"about_ca_topic_score_codex":0.003145387,"about_ca_topic_score_gemma":0.003611748,"teacher_disagreement_score":0.003983057,"about_ca_system_score_codex":0.0010811265,"about_ca_system_score_gemma":0.0027215327,"threshold_uncertainty_score":0.013324618},"labels":[],"label_agreement":null},{"id":"W4412507335","doi":"10.1016/j.suscom.2025.101166","title":"Does faster mean greener? Runtime and energy trade-offs in iOS applications with compiler optimizations","year":2025,"lang":"en","type":"article","venue":"Sustainable Computing Informatics and Systems","topic":"Green IT and Sustainability","field":"Engineering","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; Queen's University","funders":"","keywords":"Computer science; Compiler; Parallel computing; Optimizing compiler; Embedded system; Operating system","score_opus":0.0030346550180378384,"score_gpt":0.1843689082150246,"score_spread":0.18133425319698676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412507335","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":[0.9894791,0.0012592992,0.004237397,0.00023209609,0.000071680515,0.000031865635,0.00025310952,0.0013606382,0.0030747503],"genre_scores_gemma":[0.9833625,0.0003852579,0.013535335,0.00015536536,0.00002212028,0.000045388482,0.00057688414,0.0009799794,0.0009370856],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.998531,0.0003098277,0.00012360633,0.00029049386,0.00041404253,0.00033106856],"domain_scores_gemma":[0.9951382,0.0029030778,0.0004409874,0.0007162141,0.00065449264,0.00014713303],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012759495,0.0009995007,0.00037583284,0.0008785404,0.00042353375,0.0011072995,0.00066732336,0.00038508404,0.00087672274],"category_scores_gemma":[0.008415671,0.00036918907,0.00057099585,0.0011463965,0.00062064646,0.0015919913,0.0005783414,0.0009744439,0.00030575384],"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":[0.004538612,0.001333127,0.13758394,0.002264338,0.00056966994,0.0008182246,0.0019556456,0.17613201,0.33541164,0.007070196,0.010352992,0.3219697],"study_design_scores_gemma":[0.00027221828,0.0034552764,0.20263633,0.0003078651,0.000908982,0.0007124961,0.0022227932,0.38430205,0.3719941,0.007941828,0.024991594,0.0002545065],"about_ca_topic_score_codex":0.0034703626,"about_ca_topic_score_gemma":0.007862437,"teacher_disagreement_score":0.0034703626,"about_ca_system_score_codex":0.000665247,"about_ca_system_score_gemma":0.0009900989,"threshold_uncertainty_score":0.0069003105},"labels":[],"label_agreement":null},{"id":"W4414583580","doi":"10.1016/j.suscom.2025.101214","title":"A two-stage spatio-temporal flexibility-based energy optimization of internet data centers in active distribution networks based on robust control and transformer machine learning strategy","year":2025,"lang":"en","type":"article","venue":"Sustainable Computing Informatics and Systems","topic":"Smart Grid Energy Management","field":"Engineering","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 Windsor","funders":"","keywords":"Mean squared error; Robustness (evolution); Mean absolute percentage error; Approximation error; Feature selection; Efficient energy use; Extreme learning machine; Renewable energy; Gradient boosting","score_opus":0.010361380630286141,"score_gpt":0.2174166966273537,"score_spread":0.20705531599706756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414583580","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":[0.03949167,0.0003314954,0.95364225,0.00022514282,0.00005377169,0.000066601744,0.00003892351,0.0001675123,0.0059827096],"genre_scores_gemma":[0.9772117,0.00013310395,0.019943558,0.000043033342,0.000017820154,0.00007362379,0.000037764934,0.000028915643,0.0025105008],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996574,0.000087723114,0.000019553447,0.00008609509,0.00008129667,0.00006798618],"domain_scores_gemma":[0.99971837,0.00013090251,0.000037664056,0.000016957283,0.00007518605,0.000020869014],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087320583,0.00081818964,0.0013253246,0.000415036,0.0005990954,0.0013555824,0.0013349799,0.0011399155,0.0023165883],"category_scores_gemma":[0.0009407673,0.0005416173,0.0008336723,0.000487334,0.00078920013,0.0011807588,0.001241111,0.00064613373,0.00016677359],"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":[0.00007633131,0.000026556694,0.0002974956,0.000052654865,0.000029933934,0.00005915704,0.00003869397,0.9837151,0.0016265915,0.0046147583,0.00031409485,0.009148674],"study_design_scores_gemma":[0.000003550398,0.000015652817,0.00004599899,0.000001780848,0.0000048878865,0.000005565355,0.0000048046504,0.9992009,0.00018252632,0.0004679773,0.00006366825,0.0000027420074],"about_ca_topic_score_codex":0.007335316,"about_ca_topic_score_gemma":0.0052456274,"teacher_disagreement_score":0.007335316,"about_ca_system_score_codex":0.00067915325,"about_ca_system_score_gemma":0.000934297,"threshold_uncertainty_score":0.014585197},"labels":[],"label_agreement":null},{"id":"W4417085887","doi":"10.1016/j.suscom.2025.101279","title":"Challenges of IoT sensors in smart buildings ecosystems and integration of blockchain for enhanced security and efficiency","year":2025,"lang":"en","type":"article","venue":"Sustainable Computing Informatics and Systems","topic":"Blockchain Technology Applications and Security","field":"Computer Science","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":"Université de Moncton","funders":"","keywords":"Internet of Things; Blockchain; Building automation; Context (archaeology); Confidentiality; Building management system; Big data; Data management; Smart objects","score_opus":0.008416564498445127,"score_gpt":0.2441935399049309,"score_spread":0.23577697540648576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417085887","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":[0.32347348,0.013705475,0.4601794,0.051800217,0.00095956674,0.00028194804,0.00037097582,0.0005496614,0.14867938],"genre_scores_gemma":[0.9722074,0.003081354,0.015699439,0.00035347292,0.000108756576,0.00007713254,0.00009446457,0.000024700908,0.008353385],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986883,0.0004892737,0.000049538463,0.0001576207,0.0004179252,0.00019741993],"domain_scores_gemma":[0.9975083,0.0010966972,0.00017728217,0.00041091428,0.00058978866,0.00021695436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026443454,0.00029015864,0.0005119511,0.0003680091,0.00079361675,0.0037216186,0.0012252079,0.0020389762,0.006683161],"category_scores_gemma":[0.003502305,0.00026817227,0.00026877865,0.00076670223,0.0016309315,0.008364167,0.0023641863,0.0015864196,0.0010276213],"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":[0.00021578852,0.0001577954,0.0030229974,0.00044669418,0.000041744042,0.00041997604,0.0005765199,0.079374194,0.011666993,0.7810889,0.007434737,0.11555367],"study_design_scores_gemma":[0.000030080686,0.0001392212,0.00097183685,0.00027402848,0.000020337407,0.0002925939,0.0012921655,0.27006266,0.007929016,0.653345,0.06559864,0.000044431068],"about_ca_topic_score_codex":0.0010705619,"about_ca_topic_score_gemma":0.0015068909,"teacher_disagreement_score":0.006683161,"about_ca_system_score_codex":0.0011541547,"about_ca_system_score_gemma":0.001863706,"threshold_uncertainty_score":0.022357404},"labels":[],"label_agreement":null},{"id":"W7115564490","doi":"10.1016/j.suscom.2025.101284","title":"Explainable and counterfactual lasso regression for resilient micro gas turbine power prediction in smart grids","year":2025,"lang":"en","type":"article","venue":"Sustainable Computing Informatics and Systems","topic":"Energy Load and Power Forecasting","field":"Engineering","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 Moncton","funders":"","keywords":"Lasso (programming language); Microgrid; Smart grid; Counterfactual thinking; Turbine; Power (physics); Electric power system; Grid; Energy (signal processing)","score_opus":0.005467601936135394,"score_gpt":0.20940605431126838,"score_spread":0.20393845237513297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7115564490","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1652812,0.0014557171,0.8259357,0.0028010525,0.00045076752,0.00006160938,0.0010506773,0.0012625622,0.001700645],"genre_scores_gemma":[0.958948,0.0003041311,0.035900027,0.00032276858,0.00035605082,0.000092617025,0.001452853,0.00016016574,0.0024633796],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9962864,0.0026502456,0.000109620654,0.00050237984,0.00025413366,0.00019715427],"domain_scores_gemma":[0.97826093,0.017716387,0.0012945445,0.0016427889,0.0007771239,0.00030820863],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011727749,0.0012014015,0.0017955021,0.0004887974,0.0005402209,0.0015716299,0.0020572257,0.0017422107,0.0017941368],"category_scores_gemma":[0.027589543,0.0007264629,0.0010083565,0.00060064316,0.0015028608,0.0014419483,0.0014046411,0.0027476875,0.000360072],"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":[0.00025723153,0.000081600985,0.0036408945,0.00007836631,0.00016535007,0.00011186427,0.000058539143,0.96769863,0.00032512535,0.011146053,0.0022858197,0.014150508],"study_design_scores_gemma":[0.0000065439417,0.0000086322225,0.00027322664,0.0000037479697,0.0000054298594,0.000004295725,0.00000447409,0.99679786,0.00004956943,0.0027513977,0.00009092597,0.0000039537213],"about_ca_topic_score_codex":0.006769065,"about_ca_topic_score_gemma":0.0058791256,"teacher_disagreement_score":0.011727749,"about_ca_system_score_codex":0.0007049086,"about_ca_system_score_gemma":0.0012768977,"threshold_uncertainty_score":0.062022984},"labels":[],"label_agreement":null}]}