{"meta":{"query_hash":"bc92b95a269a","filters":{"venue":"Journal of Computational Design and Engineering"},"cohort_total":26,"direct_labels_cover":0,"predictions_cover":26,"exported":26,"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/bc92b95a269a","api":"https://metacan.xera.ac/api/v1/cohort?venue=Journal+of+Computational+Design+and+Engineering"},"results":[{"id":"W1539570097","doi":"10.7315/jcde.2014.021","title":"Survey on the virtual commissioning of manufacturing systems","year":2014,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Flexible and Reconfigurable Manufacturing Systems","field":"Engineering","cited_by":197,"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":"Agency for Defense Development; Ministry of Education, Science and Technology","keywords":"Project commissioning; Debugging; Engineering; Controller (irrigation); Systems engineering; Computer science; Control engineering; Manufacturing engineering; Operating system; Publishing","score_opus":0.018014839370516973,"score_gpt":0.19791926742201385,"score_spread":0.17990442805149687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1539570097","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":[0.015507211,0.6370091,0.264635,0.0027159306,0.00097973,0.000086086344,0.00020753627,0.00052616076,0.078333184],"genre_scores_gemma":[0.25494075,0.6501587,0.08485148,0.00069683645,0.00174229,0.00010284437,0.0005423367,0.00017288492,0.006791845],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983038,0.0006963366,0.00013157992,0.00021205959,0.0005533739,0.00010275109],"domain_scores_gemma":[0.9961224,0.0028182245,0.00023228377,0.0003756749,0.0003921679,0.00005913006],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013742063,0.0007143322,0.0010417893,0.0022102199,0.000477265,0.0026963737,0.0014640403,0.0010554016,0.0052785315],"category_scores_gemma":[0.0045572,0.000662323,0.0007270974,0.0045085256,0.0010026194,0.0035126114,0.0009817741,0.00080357346,0.0008484433],"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":[0.00007640251,0.000065971704,0.0015845082,0.0059266603,0.00008921792,0.00021773083,0.00030686878,0.051233012,0.0011227202,0.2273585,0.013545515,0.69847286],"study_design_scores_gemma":[0.000020385272,0.00020436711,0.0029404035,0.0032414985,0.000094316914,0.0013460871,0.00053906784,0.08505111,0.002968789,0.13457352,0.7689245,0.000096010284],"about_ca_topic_score_codex":0.0019622927,"about_ca_topic_score_gemma":0.00086972327,"teacher_disagreement_score":0.0052785315,"about_ca_system_score_codex":0.00089707086,"about_ca_system_score_gemma":0.0011984508,"threshold_uncertainty_score":0.017658412},"labels":[],"label_agreement":null},{"id":"W2224136207","doi":"10.1016/j.jcde.2015.12.001","title":"Cutter-workpiece engagement determination for general milling using triangle mesh modeling","year":2015,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Machining; Milling cutter; Process (computing); Intersection (aeronautics); Tool path; Mechanical engineering; Engineering; Polygon mesh; Engineering drawing; Path (computing); Series (stratigraphy); Cutter location; Geometry; Boundary (topology); Structural engineering; Computer science; Mathematics; Mathematical analysis","score_opus":0.06579461531457148,"score_gpt":0.2805356526886614,"score_spread":0.2147410373740899,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2224136207","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":[0.04835505,0.00007386277,0.94675785,0.000032846627,0.000013514868,0.000058519883,0.00008118601,0.00032024155,0.0043070097],"genre_scores_gemma":[0.6979287,0.00011230075,0.29955724,0.000017204544,0.000007800504,0.00009895406,0.00027358177,0.00016263982,0.0018414267],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995813,0.000087842665,0.00002858685,0.00006502326,0.00019886722,0.00003834562],"domain_scores_gemma":[0.99925166,0.000409148,0.00006751891,0.00009702087,0.00015185298,0.000022728307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005907045,0.0005628011,0.000641032,0.00073975587,0.00027680927,0.00078522286,0.0009503953,0.000770106,0.0026169815],"category_scores_gemma":[0.001739314,0.00024325606,0.00071004895,0.00055744767,0.00033760894,0.0006298468,0.0007520209,0.000506416,0.00034060157],"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":[0.000098465374,0.00007250909,0.0024851908,0.00018025417,0.000022400123,0.00021294154,0.0001261649,0.9056173,0.015436693,0.009543045,0.00052863563,0.065676436],"study_design_scores_gemma":[0.0000022380789,0.000009428021,0.00012316745,0.000003042832,0.0000017638293,0.000012771718,0.000008767549,0.9975224,0.0012715049,0.00070154504,0.0003409989,0.0000024589842],"about_ca_topic_score_codex":0.0040137307,"about_ca_topic_score_gemma":0.0032036921,"teacher_disagreement_score":0.0040137307,"about_ca_system_score_codex":0.00048725551,"about_ca_system_score_gemma":0.0005931539,"threshold_uncertainty_score":0.008754671},"labels":[],"label_agreement":null},{"id":"W2409698788","doi":"10.1016/j.jcde.2016.05.002","title":"Dynamic analysis and controller design for a slider–crank mechanism with piezoelectric actuators","year":2016,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Dynamics and Control of Mechanical Systems","field":"Engineering","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 Alberta","funders":"","keywords":"Control theory (sociology); Slider; Connecting rod; Feedback linearization; Vibration; Engineering; Controller (irrigation); Crank; Mechanism (biology); Actuator; Computer science; Mechanical engineering; Acoustics; Physics; Control (management)","score_opus":0.005200951169182097,"score_gpt":0.18130894052904872,"score_spread":0.17610798935986663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2409698788","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":[0.21717934,0.00059317576,0.7731855,0.00017487776,0.00008192409,0.00015049864,0.000046989222,0.0004355921,0.008152023],"genre_scores_gemma":[0.9848334,0.00011598528,0.013498226,0.000012632219,0.000008293289,0.00007467898,0.000014215605,0.00000648183,0.0014361107],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998795,0.000012784303,0.000006343227,0.0000302221,0.000054946362,0.00001626552],"domain_scores_gemma":[0.9998585,0.00004935761,0.000035715704,0.000012713736,0.00003627828,0.0000074679065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025473474,0.00039981672,0.00029429392,0.0002746384,0.00032216118,0.00037418675,0.0005850063,0.00048484493,0.0023379794],"category_scores_gemma":[0.00034888036,0.00027306273,0.0003628662,0.00012041368,0.0002919551,0.00019239858,0.00028917106,0.00024937038,0.00017080811],"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":[0.00021958891,0.000053120704,0.00080958166,0.00038034157,0.00008929193,0.00051025435,0.00015412422,0.59987354,0.34161448,0.004878844,0.00040790145,0.05100882],"study_design_scores_gemma":[0.000038184106,0.00027905643,0.000916201,0.000011084119,0.000028300457,0.00006376293,0.000021032138,0.9863505,0.010971385,0.00033958492,0.00097063056,0.000010340209],"about_ca_topic_score_codex":0.0026321146,"about_ca_topic_score_gemma":0.0017571696,"teacher_disagreement_score":0.0026321146,"about_ca_system_score_codex":0.00021056378,"about_ca_system_score_gemma":0.0003580185,"threshold_uncertainty_score":0.007821381},"labels":[],"label_agreement":null},{"id":"W2564475350","doi":"10.1016/j.jcde.2016.12.001","title":"Designing a generic human-machine framework for real-time supply chain planning","year":2016,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","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":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Scheme (mathematics); Convex hull; Mathematical optimization; Decision support system; Software; Regular polygon; Artificial intelligence; Mathematics","score_opus":0.025899957398394548,"score_gpt":0.23902345211502973,"score_spread":0.2131234947166352,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2564475350","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":[0.003947372,0.00003132952,0.9927642,0.000070035494,0.000011618929,0.00008653205,0.000029380602,0.0021800655,0.000879489],"genre_scores_gemma":[0.16854407,0.00005777677,0.829237,0.000058528894,0.000019325224,0.00030538838,0.00010991839,0.00023260913,0.0014353988],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988084,0.00044175604,0.00007453681,0.00024497177,0.0003201885,0.000110237714],"domain_scores_gemma":[0.9987936,0.0006544549,0.00007702694,0.00019557346,0.00017755106,0.00010183238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023672655,0.00089635834,0.00067537604,0.0006510206,0.00084084366,0.0018620676,0.0022766404,0.0015229905,0.008331806],"category_scores_gemma":[0.0034898957,0.00066230376,0.0010053397,0.00048328674,0.0011917652,0.0014319201,0.002094807,0.0012091058,0.0013674417],"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":[0.0003010855,0.00021333153,0.0011905124,0.00024471738,0.00010216195,0.0003571806,0.0005106463,0.843012,0.012297884,0.04098637,0.003048364,0.097735845],"study_design_scores_gemma":[0.000015581805,0.000022597376,0.000051973595,0.00000812118,0.0000061975534,0.000022965583,0.000017877956,0.99169767,0.0014611372,0.004252294,0.002436108,0.0000075183884],"about_ca_topic_score_codex":0.005490277,"about_ca_topic_score_gemma":0.005780392,"teacher_disagreement_score":0.008331806,"about_ca_system_score_codex":0.0011097065,"about_ca_system_score_gemma":0.0013920631,"threshold_uncertainty_score":0.027872682},"labels":[],"label_agreement":null},{"id":"W2649938423","doi":"10.1016/j.jcde.2017.06.003","title":"∊-constraint heat transfer search (∊-HTS) algorithm for solving multi-objective engineering design problems","year":2017,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","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":"Thompson Rivers University","funders":"Vedecká Grantová Agentúra MŠVVaŠ SR a SAV; Ministry of Economic Affairs","keywords":"Benchmark (surveying); Mathematical optimization; Multi-objective optimization; Reducer; Pareto principle; Engineering design process; Algorithm; Engineering optimization; Truss; Computer science; Optimization problem; Engineering; Mathematics; Structural engineering; Mechanical engineering","score_opus":0.03419872405366283,"score_gpt":0.26749690153505484,"score_spread":0.233298177481392,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2649938423","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":[0.009450511,0.000186168,0.98689216,0.00007364067,0.00002679453,0.000074566655,0.000026792794,0.00022454307,0.0030448232],"genre_scores_gemma":[0.27306753,0.00022604852,0.72119766,0.00012658087,0.00004073379,0.0006118608,0.00017515317,0.00012660574,0.0044278437],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996191,0.000114521,0.000022102886,0.0000481619,0.00015797629,0.000038161015],"domain_scores_gemma":[0.9995546,0.00025329652,0.00003875835,0.000023144421,0.0001093547,0.00002084362],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00078753836,0.0008431455,0.0007363773,0.0008349733,0.0005658244,0.0005602105,0.0009738314,0.00089634344,0.0035489628],"category_scores_gemma":[0.0012253368,0.00040599678,0.00076144375,0.00078391406,0.000398587,0.00051051524,0.00068059,0.0008094493,0.0003960729],"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":[0.00005261237,0.000044386015,0.0004035706,0.00009846472,0.00004454312,0.00004395802,0.00003740437,0.9083723,0.0024519383,0.0050208173,0.0012086111,0.08222137],"study_design_scores_gemma":[0.000010850307,0.0000186173,0.00005637836,0.0000048587813,0.0000038755356,0.000008852393,0.0000046087866,0.9980405,0.00051904615,0.0008084301,0.0005213609,0.0000025861013],"about_ca_topic_score_codex":0.005614355,"about_ca_topic_score_gemma":0.0049966886,"teacher_disagreement_score":0.005614355,"about_ca_system_score_codex":0.00061629515,"about_ca_system_score_gemma":0.0015103121,"threshold_uncertainty_score":0.011872411},"labels":[],"label_agreement":null},{"id":"W2770610194","doi":"10.1016/j.jcde.2017.11.004","title":"Interdisciplinary semantic model for managing the design of a steam-assisted gravity drainage tooling system","year":2017,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","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 Alberta","funders":"University of Alberta; Natural Sciences and Engineering Research Council of Canada; Canadian Association of Petroleum Producers","keywords":"Unified Modeling Language; Systems engineering; Computer science; Process (computing); Steam-assisted gravity drainage; Activity diagram; Engineering; Software engineering; Software; Programming language","score_opus":0.043852843244877586,"score_gpt":0.29631815850780685,"score_spread":0.25246531526292926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2770610194","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":[0.014176063,0.0000774668,0.9772217,0.00021655974,0.000024033916,0.00016335645,0.00014145224,0.00079138076,0.007187948],"genre_scores_gemma":[0.38242206,0.00027913696,0.6096375,0.00011224759,0.000018943878,0.00063429965,0.0006946198,0.00017560377,0.0060256077],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99888307,0.00036667642,0.000107376865,0.00016202015,0.00037451088,0.000106367945],"domain_scores_gemma":[0.9995221,0.00014440769,0.000058393183,0.000115680275,0.00011858765,0.000040904506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013512745,0.00069289125,0.00046576926,0.0013896073,0.00080996775,0.0024319098,0.0014859077,0.001391364,0.0033569804],"category_scores_gemma":[0.0015135492,0.00038359116,0.001454159,0.00074811565,0.001151109,0.0018701775,0.0016211901,0.0008276591,0.000586383],"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":[0.00013163834,0.00015350958,0.001981331,0.0002686167,0.00006307751,0.00079136743,0.0011251251,0.54236394,0.014702696,0.38503784,0.0017470766,0.0516338],"study_design_scores_gemma":[0.00003568541,0.00008580265,0.00029455128,0.000069769696,0.000051948908,0.000115604525,0.00021686249,0.91414714,0.005697017,0.047692332,0.031570993,0.000022317774],"about_ca_topic_score_codex":0.005718213,"about_ca_topic_score_gemma":0.00611556,"teacher_disagreement_score":0.005718213,"about_ca_system_score_codex":0.0013500558,"about_ca_system_score_gemma":0.0026745903,"threshold_uncertainty_score":0.011369824},"labels":[],"label_agreement":null},{"id":"W2889263021","doi":"10.1016/j.jcde.2018.08.004","title":"Finite element method for the static and dynamic analysis of FRP guyed tower","year":2018,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Structural Analysis and Optimization","field":"Engineering","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 Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Manitoba Hydro; University of Windsor","keywords":"Structural engineering; Finite element method; Fibre-reinforced plastic; Equilateral triangle; Serviceability (structure); Engineering; Tower; Vibration; Static analysis; Mathematics; Geometry","score_opus":0.010014018193696307,"score_gpt":0.2484417148035347,"score_spread":0.2384276966098384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889263021","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":[0.009185694,0.00018281143,0.98487246,0.00008475826,0.000048275015,0.00010761894,0.00015264798,0.00043896193,0.0049268017],"genre_scores_gemma":[0.2680352,0.00052962994,0.7092842,0.00009509281,0.000031635343,0.0009771625,0.0006965952,0.00031143712,0.020038992],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999627,0.00008768448,0.0000183089,0.000035717923,0.00020762427,0.00002366518],"domain_scores_gemma":[0.9995989,0.0001774233,0.00003398946,0.00003277475,0.00014219023,0.0000147447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000712754,0.0005944519,0.0006819665,0.0006433796,0.0004411373,0.00058889977,0.0011960309,0.0013515346,0.007000191],"category_scores_gemma":[0.00085623394,0.00058966863,0.0010940838,0.0003980161,0.00038845753,0.00048735048,0.00057927845,0.0010437474,0.0021089902],"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":[0.00006869824,0.00009465198,0.0009959516,0.00023990305,0.00005003645,0.00018200435,0.00021053723,0.9105025,0.023353158,0.0107221315,0.0017188292,0.051861558],"study_design_scores_gemma":[0.0000058705605,0.000023836094,0.0001462511,0.000020651056,0.000004143565,0.000024423187,0.000020787613,0.99513054,0.0010270383,0.0004521685,0.0031386234,0.0000056309354],"about_ca_topic_score_codex":0.0041507157,"about_ca_topic_score_gemma":0.0058783316,"teacher_disagreement_score":0.007000191,"about_ca_system_score_codex":0.00051009207,"about_ca_system_score_gemma":0.001048245,"threshold_uncertainty_score":0.02341795},"labels":[],"label_agreement":null},{"id":"W2898430231","doi":"10.1016/j.jcde.2018.10.006","title":"A hybridization of differential evolution and monarch butterfly optimization for solving systems of nonlinear equations","year":2018,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Thompson Rivers University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Metaheuristic; Nonlinear system; Mathematical optimization; Differential evolution; Maxima and minima; Heuristic; Optimization problem; Computer science; Mathematics; Algorithm","score_opus":0.02470235642766716,"score_gpt":0.2602231180731059,"score_spread":0.23552076164543873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2898430231","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":[0.037974007,0.0007084937,0.954174,0.00029754202,0.00008756625,0.00007136998,0.000022564667,0.00025107432,0.0064134593],"genre_scores_gemma":[0.55454475,0.0004050758,0.4392238,0.0003256804,0.00004479248,0.00024316546,0.00008769498,0.00006752815,0.0050575407],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996208,0.00011385615,0.000022692815,0.00005968825,0.00014558215,0.000037386555],"domain_scores_gemma":[0.999716,0.00016160906,0.00003241321,0.000025494417,0.00004738916,0.00001703935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088069186,0.00064212317,0.0007794968,0.00083981117,0.00047446133,0.00055841927,0.0011603346,0.0010019777,0.0011320356],"category_scores_gemma":[0.0010751483,0.00039719683,0.00070451177,0.00064989517,0.00053167285,0.0005654651,0.00096415024,0.00061679253,0.00015726342],"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":[0.000072368886,0.0000866504,0.0012026645,0.00011958587,0.00013028523,0.00008308916,0.000083088045,0.88366187,0.0067295614,0.016498769,0.00077522505,0.090556905],"study_design_scores_gemma":[0.000009032933,0.000027699121,0.00010394518,0.000005996522,0.0000076578435,0.000015560456,0.000005970581,0.9972356,0.00062208984,0.0009814868,0.0009808688,0.000004132306],"about_ca_topic_score_codex":0.004690276,"about_ca_topic_score_gemma":0.005408857,"teacher_disagreement_score":0.004690276,"about_ca_system_score_codex":0.0008218231,"about_ca_system_score_gemma":0.00086426263,"threshold_uncertainty_score":0.009325981},"labels":[],"label_agreement":null},{"id":"W2922260712","doi":"10.1016/j.jcde.2019.03.002","title":"Variational B-rep model analysis for direct modeling using geometric perturbation","year":2019,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Dynamics and Control of Mechanical Systems","field":"Engineering","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 British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Generalization; Boundary representation; Representation (politics); Constraint (computer-aided design); Perturbation (astronomy); Geometric modeling; Boundary (topology)","score_opus":0.016700969542642358,"score_gpt":0.20569897468770282,"score_spread":0.18899800514506046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2922260712","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":[0.008410821,0.000043895834,0.9879995,0.00006350656,0.000013445614,0.000029747504,0.00004078662,0.00012502327,0.0032732803],"genre_scores_gemma":[0.6266953,0.0003011024,0.35963127,0.00011172987,0.00004995539,0.00030563166,0.00029113653,0.00033162543,0.0122822225],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999681,0.00010259654,0.000011626504,0.000043062868,0.00013799054,0.000023721188],"domain_scores_gemma":[0.9996568,0.00015248627,0.000044021588,0.000058019734,0.000067212924,0.000021513455],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061654067,0.000694029,0.0006335274,0.00074481854,0.00034914142,0.00096613413,0.0009654197,0.0008826207,0.005318306],"category_scores_gemma":[0.0012841399,0.0003655341,0.00091397733,0.00039441144,0.0010336349,0.00091583794,0.0014759746,0.001017804,0.0007009669],"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":[0.00002855382,0.000043291453,0.00038696706,0.000064998574,0.000025335961,0.00015916416,0.00006601505,0.7845862,0.008063975,0.18633562,0.00095063343,0.019289361],"study_design_scores_gemma":[0.000001185087,0.000008756674,0.000025876077,0.0000023530201,0.0000012127972,0.0000134501415,0.0000068243694,0.9873166,0.00034130894,0.0118080815,0.00047168738,0.0000025960499],"about_ca_topic_score_codex":0.0025434762,"about_ca_topic_score_gemma":0.0019087311,"teacher_disagreement_score":0.005318306,"about_ca_system_score_codex":0.00051164645,"about_ca_system_score_gemma":0.000645712,"threshold_uncertainty_score":0.01779151},"labels":[],"label_agreement":null},{"id":"W3015497865","doi":"10.1093/jcde/qwaa039","title":"An efficient controlled elitism non-dominated sorting genetic algorithm for multi-objective supplier selection under fuzziness","year":2020,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","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":"York University","funders":"","keywords":"Sorting; Mathematical optimization; TOPSIS; Genetic algorithm; Particle swarm optimization; Taguchi methods; Selection (genetic algorithm); Ideal solution; Multi-objective optimization; Supply chain; Computer science; Fuzzy logic; Maximization; Algorithm; Mathematics; Operations research; Artificial intelligence; Machine learning","score_opus":0.07019889654136877,"score_gpt":0.3544353585863633,"score_spread":0.28423646204499453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3015497865","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":[0.042499136,0.00016759471,0.9548943,0.00013220978,0.000024922805,0.00010126711,0.000025449577,0.00019563858,0.0019594089],"genre_scores_gemma":[0.6789455,0.000152025,0.3176559,0.00014442607,0.000019460535,0.0003949385,0.00009197174,0.00003447908,0.0025612954],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99932253,0.00025949907,0.000031032643,0.00008454997,0.00022144415,0.0000809885],"domain_scores_gemma":[0.99905616,0.0006027455,0.00008743906,0.000035265693,0.00018781061,0.00003063878],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018294357,0.00086127355,0.0010263695,0.0011234853,0.0005359016,0.0009680815,0.0015102539,0.0013518294,0.0010439652],"category_scores_gemma":[0.0025189884,0.00044724403,0.00071723067,0.0009257063,0.00077916257,0.0005493409,0.0007338546,0.00075541384,0.0001380337],"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":[0.00003695637,0.00003867237,0.0003526005,0.000028693323,0.000025386305,0.000036227615,0.000052610325,0.9730435,0.0011977126,0.0030263865,0.0002028364,0.021958407],"study_design_scores_gemma":[0.0000143396255,0.000023898476,0.00004780892,0.0000043015884,0.0000043600044,0.000005120085,0.0000047187555,0.99883074,0.00026260273,0.0006947499,0.000105050865,0.0000023043458],"about_ca_topic_score_codex":0.008876271,"about_ca_topic_score_gemma":0.0059411083,"teacher_disagreement_score":0.008876271,"about_ca_system_score_codex":0.0013156101,"about_ca_system_score_gemma":0.001806018,"threshold_uncertainty_score":0.017649174},"labels":[],"label_agreement":null},{"id":"W3034731855","doi":"10.1093/jcde/qwaa059","title":"A fuzzy-based framework to support multicriteria design of mechatronic systems","year":2020,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Design Education and Practice","field":"Engineering","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":"Polytechnique Montréal","funders":"","keywords":"Mechatronics; Fuzzy logic; Conceptual design; Process (computing); Range (aeronautics); Fuzzy set; Identification (biology); Engineering design process; Measure (data warehouse)","score_opus":0.03483809038751014,"score_gpt":0.260161083025475,"score_spread":0.2253229926379649,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3034731855","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":[0.0031974912,0.00010864282,0.99497664,0.00005334,0.000017560435,0.000052294246,0.000014158124,0.000047519326,0.0015325054],"genre_scores_gemma":[0.26817253,0.00022296283,0.72932583,0.00004930757,0.00003292882,0.00030097872,0.00006607534,0.000032863318,0.0017965826],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99863654,0.0005999852,0.000106092004,0.00015821839,0.00040985967,0.00008923479],"domain_scores_gemma":[0.9989114,0.0005201953,0.000100578414,0.000077126664,0.00033698592,0.00005370565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033579313,0.0009893266,0.0009195743,0.0014531547,0.0007682132,0.0017723824,0.0016114033,0.0012447437,0.0030243592],"category_scores_gemma":[0.0029962827,0.00044461363,0.0014108011,0.0008726041,0.0011574593,0.0010370925,0.0014443424,0.0012288304,0.000379697],"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":[0.000045746754,0.00005771053,0.00026598922,0.00015373883,0.00005077694,0.00016341706,0.00020738033,0.8251035,0.004269197,0.13350363,0.00045186735,0.03572703],"study_design_scores_gemma":[0.000009161393,0.000027317215,0.00003683334,0.00002607022,0.000009454434,0.000015262676,0.000019376586,0.98060614,0.00051218114,0.016936598,0.0017948876,0.0000066750804],"about_ca_topic_score_codex":0.00539372,"about_ca_topic_score_gemma":0.0051741996,"teacher_disagreement_score":0.00539372,"about_ca_system_score_codex":0.0014855412,"about_ca_system_score_gemma":0.001610621,"threshold_uncertainty_score":0.017758667},"labels":[],"label_agreement":null},{"id":"W3117154257","doi":"10.1093/jcde/qwaa089","title":"A biobjective home health care logistics considering the working time and route balancing: a self-adaptive social engineering optimizer","year":2020,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Vehicle Routing Optimization Methods","field":"Engineering","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":"École de Technologie Supérieure","funders":"","keywords":"Metaheuristic; Vehicle routing problem; Scheduling (production processes); Computer science; Population; Operations research; Operations management; Routing (electronic design automation); Engineering; Artificial intelligence; Medicine; Computer network","score_opus":0.02356356349678254,"score_gpt":0.23335147664918524,"score_spread":0.2097879131524027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3117154257","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":[0.09556397,0.0008489063,0.88831997,0.0009921503,0.00016506563,0.00022356819,0.00015358072,0.00022517257,0.01350767],"genre_scores_gemma":[0.8534458,0.0005349874,0.13916355,0.0003478933,0.000089247085,0.00044561335,0.00019476707,0.00007795726,0.005700063],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99948514,0.00021285306,0.000020488149,0.00009089346,0.00010508641,0.00008545567],"domain_scores_gemma":[0.9991561,0.0004972095,0.000098613666,0.00003392371,0.00015151573,0.00006268141],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011610317,0.0012568483,0.001206919,0.00082913955,0.00052464136,0.0014487354,0.0010205616,0.0016748434,0.0021822096],"category_scores_gemma":[0.002044992,0.00049400626,0.0011657558,0.0006159349,0.0006405727,0.0007298312,0.0012006344,0.0011499133,0.00019662986],"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":[0.000024896905,0.000053346914,0.00043150116,0.000038006026,0.00003629678,0.000054859163,0.000021042457,0.9894806,0.00041044908,0.0031032225,0.00044242258,0.005903341],"study_design_scores_gemma":[0.0000045257216,0.000021047174,0.00005873368,0.000004828332,0.000006897776,0.0000054113602,0.000011135553,0.9989661,0.00006304138,0.0006500027,0.00020629016,0.0000020471543],"about_ca_topic_score_codex":0.006698887,"about_ca_topic_score_gemma":0.0029952829,"teacher_disagreement_score":0.006698887,"about_ca_system_score_codex":0.0009266006,"about_ca_system_score_gemma":0.0014036855,"threshold_uncertainty_score":0.01331979},"labels":[],"label_agreement":null},{"id":"W3132127288","doi":"10.1093/jcde/qwab009","title":"A novel particle swarm optimization-based grey model for the prediction of warehouse performance","year":2021,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Grey System Theory Applications","field":"Decision Sciences","cited_by":79,"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 Regina; École de Technologie Supérieure","funders":"","keywords":"Performance indicator; Particle swarm optimization; Warehouse; Supply chain; Data mining; Genetic algorithm; Taguchi methods; Computer science; Key (lock); Engineering; Operations research; Machine learning","score_opus":0.09769746644814277,"score_gpt":0.29296198254697847,"score_spread":0.19526451609883572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3132127288","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":[0.13831446,0.001165163,0.8514689,0.0006862789,0.00015855579,0.00008970141,0.00032941686,0.0003900943,0.00739746],"genre_scores_gemma":[0.97263294,0.00038388278,0.023981757,0.00006757493,0.000031162486,0.000088888024,0.00022023005,0.000018428436,0.0025752278],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99973077,0.00007814318,0.000018336576,0.00007271565,0.00006385303,0.00003608192],"domain_scores_gemma":[0.9996111,0.00022291564,0.00004547945,0.000012981992,0.00009203728,0.000015592004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063897157,0.00070813415,0.00094540016,0.0006406482,0.00034688532,0.0010106422,0.0010866796,0.001197466,0.0012923847],"category_scores_gemma":[0.0015207409,0.00039277182,0.0008844803,0.00072835264,0.00044895877,0.0006970662,0.0005449623,0.0009521101,0.00017984048],"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":[0.000017277787,0.00001393258,0.0007738521,0.000024598645,0.00002381342,0.00003164148,0.00001666985,0.9919252,0.00035624226,0.00094526605,0.00023062946,0.0056409948],"study_design_scores_gemma":[0.0000017678757,0.0000050883,0.00011649639,0.0000017847785,0.0000030139072,0.0000015348294,0.0000018734364,0.99957806,0.000039859096,0.00020191836,0.000047008107,0.0000015728881],"about_ca_topic_score_codex":0.021200659,"about_ca_topic_score_gemma":0.0091406545,"teacher_disagreement_score":0.021200659,"about_ca_system_score_codex":0.0006593855,"about_ca_system_score_gemma":0.00090179377,"threshold_uncertainty_score":0.04215449},"labels":[],"label_agreement":null},{"id":"W3135803911","doi":"10.1093/jcde/qwab011","title":"Airfoil profile reconstruction from unorganized noisy point cloud data","year":2021,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Advanced Measurement and Metrology Techniques","field":"Engineering","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":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Airfoil; Algorithm; Noise (video); Point cloud; Computer science; Mathematics; Computer vision; Engineering; Structural engineering","score_opus":0.02453848477246032,"score_gpt":0.22300566826383547,"score_spread":0.19846718349137515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3135803911","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":[0.13271363,0.00007824652,0.8657369,0.000046674584,0.000017536686,0.000036363796,0.00015539229,0.0008355362,0.00037964396],"genre_scores_gemma":[0.69845927,0.00011398689,0.29982626,0.000022485197,0.000012458833,0.000057894966,0.00074237044,0.00011105305,0.0006541925],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996623,0.000049684717,0.000019997513,0.00006454562,0.00016355752,0.000039981696],"domain_scores_gemma":[0.999019,0.00020337269,0.00013721413,0.00027061265,0.0003266781,0.000043066626],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048068838,0.0007164747,0.000614416,0.0011027597,0.00025782493,0.00064393994,0.0006459151,0.00066040125,0.0007089627],"category_scores_gemma":[0.0018189393,0.0003908469,0.00065944553,0.00080693787,0.00037984725,0.0006790918,0.0007080977,0.00070509105,0.00046818567],"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":[0.00046488966,0.00011628351,0.008693089,0.00024002306,0.000081423976,0.0006947225,0.00035711288,0.65521055,0.1123651,0.0014890763,0.0012934579,0.21899416],"study_design_scores_gemma":[0.0000065771674,0.00002459808,0.0015254213,0.0000065600225,0.000004490293,0.00006100329,0.000049790615,0.9846058,0.012971541,0.00039649667,0.00033755886,0.000010247122],"about_ca_topic_score_codex":0.0036237026,"about_ca_topic_score_gemma":0.0028840278,"teacher_disagreement_score":0.0036237026,"about_ca_system_score_codex":0.0002798268,"about_ca_system_score_gemma":0.0006344501,"threshold_uncertainty_score":0.0072051883},"labels":[],"label_agreement":null},{"id":"W3201884713","doi":"10.1093/jcde/qwab051","title":"A novel lattice structure topology optimization method with extreme anisotropic lattice properties","year":2021,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Topology Optimization in Engineering","field":"Engineering","cited_by":58,"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":"Natural Science Foundation of Shandong Province; Natural Science Foundation of Jiangsu Province; Shandong University","keywords":"Topology optimization; Lattice (music); Topology (electrical circuits); Homogenization (climate); Mathematics; Anisotropy; Mathematical optimization; Computer science; Structural engineering; Finite element method; Physics; Engineering; Combinatorics","score_opus":0.02031769075495351,"score_gpt":0.2181945457627767,"score_spread":0.19787685500782318,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3201884713","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":[0.009393171,0.0001877624,0.985069,0.00010827658,0.000042733343,0.000045843255,0.000045664183,0.00019982268,0.004907714],"genre_scores_gemma":[0.23715563,0.00022986034,0.75539327,0.00015948372,0.0000548023,0.0003255628,0.0002508993,0.00032497002,0.0061055375],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997528,0.00007373134,0.000009250905,0.000038897728,0.000101277394,0.000023961087],"domain_scores_gemma":[0.99975926,0.00010369016,0.000028769344,0.000027474869,0.000060348208,0.000020586323],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043167223,0.0006170139,0.000844162,0.00077175786,0.0003482877,0.00077248266,0.00089975586,0.00082047726,0.0032864583],"category_scores_gemma":[0.00079570565,0.0004108417,0.0007229831,0.0005071882,0.00045283267,0.00078264147,0.00077994965,0.00072559563,0.00073878857],"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":[0.00009106802,0.000089850095,0.0008403428,0.00021912476,0.000051671315,0.00015231779,0.00008094336,0.82445127,0.015913697,0.04041891,0.0034964082,0.11419434],"study_design_scores_gemma":[0.000011811261,0.000020158384,0.000038087535,0.000004790521,0.0000038172825,0.000025472307,0.000008490303,0.99490273,0.00065194553,0.0027681643,0.0015595736,0.0000048874285],"about_ca_topic_score_codex":0.0010994374,"about_ca_topic_score_gemma":0.0015971861,"teacher_disagreement_score":0.0032864583,"about_ca_system_score_codex":0.00037677021,"about_ca_system_score_gemma":0.000753565,"threshold_uncertainty_score":0.010994256},"labels":[],"label_agreement":null},{"id":"W4213255064","doi":"10.1093/jcde/qwab069","title":"A heterogeneous lattice structure modeling technique supported by multiquadric radial basis function networks","year":2021,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Topology Optimization in Engineering","field":"Engineering","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":"McGill University","funders":"Academic Excellence Foundation of BUAA for PHD Students","keywords":"Cable gland; Lattice (music); Basis (linear algebra); Function (biology); Architectural geometry; Computer science; Mathematical optimization; Engineering; Topology (electrical circuits); Mathematics; Mechanical engineering; Engineering drawing; Geometry","score_opus":0.006829751502120535,"score_gpt":0.19207739596933734,"score_spread":0.1852476444672168,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4213255064","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":[0.008248708,0.00006864343,0.9893416,0.000047268546,0.000012718832,0.000016274103,0.000027969467,0.0001277209,0.0021090105],"genre_scores_gemma":[0.42009625,0.00031275197,0.5749763,0.00007414211,0.000023746015,0.00016369772,0.0001546659,0.00013129669,0.004067159],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99979454,0.00008068955,0.000006524783,0.000025668223,0.00007413512,0.00001846515],"domain_scores_gemma":[0.9998338,0.00005348968,0.000026712405,0.000028916787,0.00004399698,0.0000131052475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004873916,0.0005481915,0.0005746202,0.00061745575,0.0003656667,0.0007387235,0.0010498975,0.0008349292,0.0016166623],"category_scores_gemma":[0.0005638416,0.0003383573,0.00064942765,0.0005621888,0.00045976037,0.00077477685,0.00057957857,0.00066887477,0.0005845822],"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":[0.000020928886,0.000030267383,0.0002219967,0.000026355307,0.000010573613,0.000058838756,0.000025518995,0.95879185,0.005247373,0.019571543,0.00036130782,0.015633458],"study_design_scores_gemma":[6.7805064e-7,0.0000025733996,0.000008924856,0.0000010803459,6.2118914e-7,0.0000042040274,0.0000014808207,0.9989711,0.00020116569,0.000594679,0.00021223152,0.0000012247901],"about_ca_topic_score_codex":0.0035284478,"about_ca_topic_score_gemma":0.0035550236,"teacher_disagreement_score":0.0035284478,"about_ca_system_score_codex":0.00043215745,"about_ca_system_score_gemma":0.00062012614,"threshold_uncertainty_score":0.0070158243},"labels":[],"label_agreement":null},{"id":"W4289885505","doi":"10.1093/jcde/qwac076","title":"A geometric modelling framework to support the design of heterogeneous lattice structures with non-linearly varying geometry","year":2022,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","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":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Geometric design; Geometric modeling; Lattice (music); Software; Computer Aided Design; Computer science; Geometric shape; Representation (politics); Geometric networks; Mathematics; Geometry","score_opus":0.02234133882158116,"score_gpt":0.21823323520863766,"score_spread":0.1958918963870565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4289885505","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":[0.0028396824,0.000059059035,0.99522287,0.00003458362,0.00001130256,0.000025938227,0.000025070374,0.00025355266,0.0015279909],"genre_scores_gemma":[0.16230474,0.0002699262,0.8345331,0.0000430662,0.000017703043,0.00023242699,0.00018935997,0.00028849655,0.0021213184],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993673,0.00019846245,0.000040033683,0.0000693186,0.00027173464,0.000053164335],"domain_scores_gemma":[0.999491,0.00021482387,0.00007462297,0.00008328312,0.00011109176,0.000025203022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011853317,0.0011917776,0.00089367037,0.0012162745,0.00043686753,0.0016400613,0.0018031836,0.001184847,0.0031120614],"category_scores_gemma":[0.0014284096,0.000546341,0.0014427869,0.00081817014,0.00104204,0.0010538679,0.001321688,0.0011139606,0.0009954054],"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":[0.000024923187,0.0000381739,0.0003048257,0.00012040607,0.000020595004,0.00012219552,0.00010253297,0.8962271,0.0097724125,0.05948496,0.00061694457,0.03316494],"study_design_scores_gemma":[0.0000059329404,0.000025601683,0.00003622826,0.000012917239,0.000005963675,0.000039042563,0.000012370854,0.9873998,0.001864735,0.0058438987,0.0047453344,0.000008111736],"about_ca_topic_score_codex":0.0018245444,"about_ca_topic_score_gemma":0.0021602313,"teacher_disagreement_score":0.0031120614,"about_ca_system_score_codex":0.00062771764,"about_ca_system_score_gemma":0.00095193874,"threshold_uncertainty_score":0.010410845},"labels":[],"label_agreement":null},{"id":"W4297688052","doi":"10.1093/jcde/qwac084","title":"TransNav: spatial sequential transformer network for visual navigation","year":2022,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Multimodal Machine Learning Applications","field":"Computer Science","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 Key Research and Development Program of China; Ministry of Natural Resources","keywords":"Computer science; Reinforcement learning; Artificial intelligence; Inference; Transformer; Machine learning; Engineering","score_opus":0.012894214952839501,"score_gpt":0.2588550867853863,"score_spread":0.24596087183254683,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297688052","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":[0.06758702,0.0016118545,0.9036824,0.0006712142,0.00033373025,0.00012871971,0.0021297461,0.014339802,0.009515453],"genre_scores_gemma":[0.83768475,0.0007028612,0.1441861,0.00037942524,0.00006721703,0.00019594439,0.004014095,0.00044706278,0.012322529],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998435,0.000022777605,0.000006709375,0.00006133805,0.00003465881,0.00003106262],"domain_scores_gemma":[0.9997619,0.000074943346,0.000022012468,0.00004147042,0.0000697358,0.000029905992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031952633,0.0010737742,0.00069834816,0.00052760914,0.000309045,0.0005803832,0.0020619535,0.0008567619,0.0048980047],"category_scores_gemma":[0.0012162745,0.00041254162,0.00067883387,0.0005375145,0.00049491116,0.0013308948,0.0009793605,0.0014111338,0.0010059376],"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":[0.00037918752,0.00019329142,0.0017968566,0.00017020044,0.00010082101,0.0001726438,0.0000688619,0.68733644,0.00675053,0.013812041,0.01700461,0.2722146],"study_design_scores_gemma":[0.0000105011195,0.000023395585,0.00007843586,0.0000053100484,0.0000074920763,0.000013450056,0.000004390294,0.9937831,0.0009698616,0.004350415,0.0007494688,0.0000041320477],"about_ca_topic_score_codex":0.024596673,"about_ca_topic_score_gemma":0.027236653,"teacher_disagreement_score":0.024596673,"about_ca_system_score_codex":0.0010893107,"about_ca_system_score_gemma":0.0014118709,"threshold_uncertainty_score":0.048906982},"labels":[],"label_agreement":null},{"id":"W4303685875","doi":"10.1093/jcde/qwac107","title":"Twisted-fin parametric study to enhance the solidification performance of phase-change material in a shell-and-tube latent heat thermal energy storage system","year":2022,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Phase Change Materials Research","field":"Engineering","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":"Natural Resources Canada","funders":"","keywords":"Fin; Annular fin; Materials science; Latent heat; Thermal energy storage; Heat transfer; Mechanics; Phase-change material; Thermal conduction; Thermodynamics; Thermal; Heat transfer coefficient; Composite material; Physics","score_opus":0.04084439053015943,"score_gpt":0.2734285288958825,"score_spread":0.23258413836572306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4303685875","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":[0.9961002,0.000070026195,0.002493079,0.000019663874,0.000007678476,0.000007735925,0.000046773257,0.0000264184,0.0012283857],"genre_scores_gemma":[0.9994717,0.000016064456,0.00035084816,0.000001392381,4.4761836e-7,0.000003100791,0.0000067174747,0.000002022663,0.00014763515],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999517,0.000006306443,0.0000020237906,0.000009424898,0.000015567493,0.000014914878],"domain_scores_gemma":[0.9998734,0.000055636785,0.00002171818,0.000016205562,0.000022697252,0.000010402624],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000154466,0.00020406689,0.00023579206,0.00015744557,0.00017773191,0.0002729188,0.00030412173,0.00021986091,0.0013033089],"category_scores_gemma":[0.00029057026,0.000101769096,0.00021622736,0.00016241227,0.00029896945,0.00026416153,0.0002681329,0.00020287416,0.0000917948],"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":[0.00097215356,0.00018748375,0.0048044384,0.00036851628,0.00004292285,0.0007025584,0.00023282919,0.38640434,0.58510906,0.0023875118,0.00038907712,0.018399011],"study_design_scores_gemma":[0.000053559463,0.001957754,0.0057335403,0.000025659197,0.000041514915,0.000127716,0.00017457326,0.66308147,0.32687905,0.0004966437,0.0013892892,0.000039243954],"about_ca_topic_score_codex":0.0005770502,"about_ca_topic_score_gemma":0.0005875741,"teacher_disagreement_score":0.0013033089,"about_ca_system_score_codex":0.00017913093,"about_ca_system_score_gemma":0.00014420884,"threshold_uncertainty_score":0.00436002},"labels":[],"label_agreement":null},{"id":"W4307096839","doi":"10.1093/jcde/qwac109","title":"A novel bio-inspired approach with multi-resolution mapping for the path planning of multi-robot system in complex environments","year":2022,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Robotic Path Planning Algorithms","field":"Computer Science","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 Guelph","funders":"Shenzhen Graduate School, Peking University","keywords":"Motion planning; Computer science; Path (computing); Robot; Stability (learning theory); Computation; Interference (communication); Artificial intelligence; Algorithm; Machine learning","score_opus":0.06823519760274802,"score_gpt":0.23910233431687178,"score_spread":0.17086713671412376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307096839","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":[0.0047097155,0.00019031439,0.9933943,0.00008488139,0.000022581768,0.000018494722,0.00001213779,0.00014238076,0.0014252239],"genre_scores_gemma":[0.44083905,0.00042967117,0.55420285,0.00015393228,0.000039852304,0.0002125908,0.00007775054,0.00007221972,0.0039721094],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99982136,0.00003923815,0.000010710563,0.000050982366,0.00005558292,0.000022131995],"domain_scores_gemma":[0.9998406,0.00005846909,0.000025609525,0.000020717342,0.00003946912,0.000015137341],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034910496,0.00074967934,0.0005592294,0.00063650904,0.00049743557,0.00060675223,0.0012076428,0.0009321492,0.001606726],"category_scores_gemma":[0.0005906012,0.00042424857,0.00074542384,0.0005280562,0.0004621791,0.0010786374,0.0010434744,0.00074042444,0.00020577635],"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":[0.000025425174,0.0000310985,0.00038729887,0.00008186803,0.000039634993,0.0001037594,0.0000913094,0.9099439,0.0075818193,0.012912758,0.0007222372,0.068078816],"study_design_scores_gemma":[0.0000019101547,0.000010477404,0.000032694665,0.000002684095,0.000003505962,0.00001613047,0.0000048092043,0.9977586,0.00037228814,0.0013900336,0.0004029452,0.0000038796957],"about_ca_topic_score_codex":0.0039015182,"about_ca_topic_score_gemma":0.0032281133,"teacher_disagreement_score":0.0039015182,"about_ca_system_score_codex":0.00059209083,"about_ca_system_score_gemma":0.00085120415,"threshold_uncertainty_score":0.007757604},"labels":[],"label_agreement":null},{"id":"W4365457819","doi":"10.1093/jcde/qwad033","title":"Laser–tissue interaction simulation considering skin-specific data to predict photothermal damage lesions during laser irradiation","year":2023,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Optical Coherence Tomography Applications","field":"Engineering","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 Laval","funders":"National Research Foundation of Korea; Ministry of Trade, Industry and Energy; Ministry of Science and ICT, South Korea; Ministry of Food and Drug Safety; Korea Medical Device Development Fund; Ministry of Education; Ministry of Health and Welfare","keywords":"Photothermal therapy; Laser; Monte Carlo method; Optical coherence tomography; Materials science; Irradiation; Attenuation coefficient; Absorption (acoustics); Optics; Biomedical engineering; Radiation; Biological system; Mathematics; Composite material; Physics; Nanotechnology; Engineering; Statistics","score_opus":0.04653069397089487,"score_gpt":0.27719574750907555,"score_spread":0.23066505353818068,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4365457819","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":[0.7165091,0.00046579752,0.2760397,0.00021364911,0.000047649828,0.00009548456,0.00022748036,0.0003596694,0.006041424],"genre_scores_gemma":[0.98553616,0.00013154266,0.012618168,0.00003635112,0.000005266505,0.00007803253,0.000070346476,0.00004499303,0.0014791755],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999043,0.000026928972,0.000004474029,0.000015633837,0.000031692005,0.000016946855],"domain_scores_gemma":[0.999645,0.00022149384,0.00004019705,0.000024497629,0.000050326453,0.000018522704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022021127,0.0003618994,0.0004028117,0.0002894088,0.00028484256,0.00045981625,0.00042297578,0.00093400764,0.0010682121],"category_scores_gemma":[0.00087506033,0.00031147167,0.00054931553,0.0002474864,0.00033736587,0.00037551252,0.00029574838,0.00031613448,0.00017223111],"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":[0.000014510659,0.0000137882935,0.00042990487,0.000009130696,0.0000054873562,0.000034033073,0.000013061667,0.9949563,0.0034994194,0.00019028889,0.000029899878,0.0008041598],"study_design_scores_gemma":[0.0000016310978,0.0000072804905,0.000112437556,8.544919e-7,0.0000016399431,0.0000081537,0.0000030664567,0.9991159,0.0006547904,0.000045416273,0.000047148907,0.0000016090722],"about_ca_topic_score_codex":0.0075786468,"about_ca_topic_score_gemma":0.004908034,"teacher_disagreement_score":0.0075786468,"about_ca_system_score_codex":0.00071702665,"about_ca_system_score_gemma":0.0008012006,"threshold_uncertainty_score":0.0150690675},"labels":[],"label_agreement":null},{"id":"W4367693552","doi":"10.1093/jcde/qwad039","title":"Hybrid neural network-based metaheuristics for prediction of financial markets: a case study on global gold market","year":2023,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":59,"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":"Metaheuristic; Firefly algorithm; Artificial neural network; Computer science; Hyperparameter; Novelty; Artificial intelligence; Machine learning; Convolutional neural network; Particle swarm optimization","score_opus":0.09818076663270471,"score_gpt":0.35188170961076126,"score_spread":0.25370094297805657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4367693552","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":[0.9111178,0.0009891121,0.082811266,0.0007832838,0.000059380352,0.000108798755,0.0002395798,0.0002235066,0.003667218],"genre_scores_gemma":[0.9806306,0.00013308265,0.018212257,0.000043878303,0.0000117928585,0.000048237,0.00008146133,0.000012820403,0.0008259229],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996915,0.0001471194,0.000015692945,0.00004635082,0.000039801736,0.000059487375],"domain_scores_gemma":[0.99785477,0.0016814806,0.00014677041,0.00005513031,0.00018593053,0.00007593522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018382462,0.001135277,0.0010108072,0.0012775024,0.00046180285,0.000969309,0.00090414827,0.0019070756,0.0010004191],"category_scores_gemma":[0.0031092095,0.00032614803,0.0008557575,0.0008357606,0.0006233699,0.00076883455,0.0005756351,0.0010306382,0.000073902105],"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":[0.000055932906,0.0000816494,0.0020802633,0.0000293521,0.000034991404,0.000112675305,0.000015404083,0.99185693,0.00019807542,0.000838904,0.00019369432,0.004502107],"study_design_scores_gemma":[0.000004972126,0.000014603441,0.00017528853,0.0000018161411,0.0000036891956,0.000003899188,0.000008940297,0.99944633,0.000097887736,0.00020774124,0.00003294557,0.0000018179918],"about_ca_topic_score_codex":0.017348778,"about_ca_topic_score_gemma":0.011621344,"teacher_disagreement_score":0.017348778,"about_ca_system_score_codex":0.0011534458,"about_ca_system_score_gemma":0.0008029898,"threshold_uncertainty_score":0.034495592},"labels":[],"label_agreement":null},{"id":"W4392180792","doi":"10.1093/jcde/qwae020","title":"Revolutionizing the latent heat storage: Boosting discharge performance with innovative undulated phase change material containers in a vertical shell-and-tube system","year":2024,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Phase Change Materials Research","field":"Engineering","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Natural Resources Canada","funders":"Engineering and Physical Sciences Research Council","keywords":"Latent heat; Phase-change material; Boosting (machine learning); Phase change; Tube (container); Shell (structure); Materials science; Thermal energy storage; Engineering; Structural engineering; Composite material; Computer science; Engineering physics; Physics; Artificial intelligence; Meteorology; Thermodynamics","score_opus":0.03697011949127055,"score_gpt":0.2572042458758056,"score_spread":0.22023412638453504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392180792","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":[0.9911841,0.00024118328,0.007675099,0.00003256254,0.000024704774,0.000019179002,0.00006500653,0.0002617116,0.00049645104],"genre_scores_gemma":[0.995978,0.00008431539,0.003391743,0.00001300586,0.000004295287,0.00000863915,0.00005793917,0.000017827868,0.0004441209],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998747,0.000018389901,0.000010450506,0.000026697504,0.000042188705,0.00002747301],"domain_scores_gemma":[0.99990106,0.000016601878,0.00002315317,0.00001725845,0.000029043797,0.000012857121],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019233144,0.00024968205,0.00033379742,0.00022139086,0.00020439034,0.00042110396,0.0005183091,0.00022051236,0.0012031095],"category_scores_gemma":[0.0002786623,0.00012309584,0.00026510766,0.00022768047,0.00024846094,0.0005542495,0.0004754168,0.00027954922,0.00038068646],"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":[0.00069494674,0.00012417856,0.0024966826,0.0001847443,0.000019596722,0.00026390035,0.000090173555,0.00824507,0.9596227,0.0004318178,0.00032944913,0.027496831],"study_design_scores_gemma":[0.000055665616,0.0012204847,0.0044654207,0.000016219497,0.00003742834,0.00016169157,0.000107721724,0.053977296,0.9361706,0.00010795168,0.0036421276,0.000037437763],"about_ca_topic_score_codex":0.000595137,"about_ca_topic_score_gemma":0.0007407142,"teacher_disagreement_score":0.0012031095,"about_ca_system_score_codex":0.00028176315,"about_ca_system_score_gemma":0.00018965013,"threshold_uncertainty_score":0.0040248632},"labels":[],"label_agreement":null},{"id":"W4411020509","doi":"10.1093/jcde/qwaf053","title":"Optimizing image format piping and instrumentation diagram recognition: Integrating symbol and text recognition with a single backbone architecture","year":2025,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","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":"ASTER","funders":"Ministry of Science and ICT, South Korea; Ministry of Education, India; National Research Foundation; National Research Foundation of Korea; Ministry of Education","keywords":"Symbol (formal); Instrumentation (computer programming); Architecture; Piping; Diagram; Computer science; Engineering drawing; Artificial intelligence; Pattern recognition (psychology); Computer vision; Speech recognition; Natural language processing; Engineering; Mechanical engineering; Programming language; Database","score_opus":0.011713344175164665,"score_gpt":0.2171274700654885,"score_spread":0.20541412589032382,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411020509","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":[0.106794536,0.00045552736,0.8728054,0.0002766784,0.000097540586,0.00010240988,0.00024104257,0.015032512,0.004194316],"genre_scores_gemma":[0.7522815,0.0002456588,0.23865862,0.00020632679,0.000038743998,0.000116318544,0.0006716069,0.00027092695,0.0075103045],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997664,0.000019456318,0.000010685205,0.000095097144,0.00006505069,0.000043253625],"domain_scores_gemma":[0.9997321,0.000058980415,0.000028294873,0.000046212826,0.00011096131,0.000023530652],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032589503,0.0010102296,0.0006228443,0.0005433824,0.00021811038,0.00083074847,0.0010763371,0.00077392417,0.0027779671],"category_scores_gemma":[0.0007531827,0.0002577635,0.0006486158,0.00049322424,0.00030380095,0.0012604521,0.00042512934,0.000737313,0.0019572377],"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":[0.00026746237,0.00021511794,0.0017750658,0.00012489171,0.00009469653,0.00013608267,0.000040557967,0.25935122,0.086421594,0.0014271239,0.004704228,0.64544195],"study_design_scores_gemma":[0.0000073197684,0.000055380307,0.00041534618,0.0000048036177,0.000023987233,0.000032337568,0.000008079961,0.9730688,0.025119493,0.000564211,0.00069407345,0.000006160531],"about_ca_topic_score_codex":0.0068189926,"about_ca_topic_score_gemma":0.0072498415,"teacher_disagreement_score":0.0068189926,"about_ca_system_score_codex":0.000636469,"about_ca_system_score_gemma":0.0009645526,"threshold_uncertainty_score":0.013558567},"labels":[],"label_agreement":null},{"id":"W4414861064","doi":"10.1093/jcde/qwaf100","title":"Optimizing Markov decision process state design for deep reinforcement learning manufacturing scheduling using Bayesian optimization","year":2025,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Manufacturing Process and Optimization","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":"Canada Research Chairs; University of Toronto","funders":"Incheon National University","keywords":"Reinforcement learning; Markov decision process; Scheduling (production processes); Job shop scheduling; Dynamic priority scheduling; Bayesian optimization; Feature selection; Partially observable Markov decision process","score_opus":0.011097002070480085,"score_gpt":0.23587606496968183,"score_spread":0.22477906289920174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414861064","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":[0.02380617,0.00017991186,0.97379977,0.0002538527,0.000024820132,0.00005378694,0.000038285183,0.0002677327,0.001575736],"genre_scores_gemma":[0.90592223,0.00012850686,0.09140905,0.00017417829,0.000025179157,0.0002221183,0.00011646055,0.00006981475,0.0019324825],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99932003,0.000272192,0.000026888942,0.00013490452,0.00013611541,0.00010982134],"domain_scores_gemma":[0.9972759,0.001984588,0.0002012724,0.00007439037,0.0003593455,0.00010446138],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019781112,0.0009528892,0.0013646004,0.0005081122,0.00034012893,0.00093546964,0.0010055308,0.0010447227,0.002396285],"category_scores_gemma":[0.004938869,0.0006939853,0.0007062279,0.00039343338,0.0009863738,0.0008519637,0.0010155037,0.0016768785,0.0003138665],"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":[0.00003609817,0.000024571897,0.00020907972,0.000022372602,0.000013644727,0.000012134228,0.000013041388,0.9881467,0.00035682973,0.0027961407,0.00015535885,0.008213997],"study_design_scores_gemma":[0.0000029120574,0.000007006773,0.000015496566,0.0000014529762,0.0000014090601,6.410175e-7,8.816067e-7,0.99922407,0.000056510715,0.00066237646,0.000026249389,8.7445324e-7],"about_ca_topic_score_codex":0.007205281,"about_ca_topic_score_gemma":0.0065548187,"teacher_disagreement_score":0.007205281,"about_ca_system_score_codex":0.001371735,"about_ca_system_score_gemma":0.0020192878,"threshold_uncertainty_score":0.014326692},"labels":[],"label_agreement":null},{"id":"W4415502605","doi":"10.1093/jcde/qwaf112","title":"AR-RBMO: An enhanced red-billed blue magpie optimizer with attraction-repulsion and dynamic balancing strategies for global optimization","year":2025,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","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":"Lakehead University","funders":"National Natural Science Foundation of China","keywords":"Benchmark (surveying); Global optimization; Metaheuristic; Flexibility (engineering); Convergence (economics); Population; Robustness (evolution); Swarm intelligence; Optimization problem; Wilcoxon signed-rank test","score_opus":0.010517179620667231,"score_gpt":0.2738454120282298,"score_spread":0.2633282324075626,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415502605","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":[0.086135186,0.0017512017,0.8915888,0.00047753143,0.00021908984,0.0001704494,0.000092693845,0.0022116182,0.01735347],"genre_scores_gemma":[0.72772086,0.00046001218,0.26300046,0.0004136134,0.0000930091,0.00037032666,0.00023363985,0.00021902012,0.0074890666],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99966407,0.00011011876,0.000016651597,0.000047414953,0.00012551456,0.00003624391],"domain_scores_gemma":[0.9997806,0.000077035154,0.000037575956,0.000024973851,0.00006006144,0.000019771342],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000675838,0.0010288076,0.00084659515,0.0007441123,0.00039905193,0.00077949197,0.001153305,0.0009846654,0.0021039704],"category_scores_gemma":[0.00080631184,0.00034588622,0.00073518424,0.00042646108,0.0003829609,0.000494307,0.000978358,0.00069416454,0.00059283676],"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":[0.000118733,0.000117368516,0.00062482955,0.000110876164,0.00010083804,0.00009547646,0.000038990373,0.9066486,0.010304214,0.0062202746,0.0025030284,0.07311684],"study_design_scores_gemma":[0.000015052021,0.000056041696,0.00011223994,0.0000057188267,0.0000076147207,0.00001275345,0.000003915105,0.99748355,0.0006840448,0.00047488505,0.0011386883,0.000005535344],"about_ca_topic_score_codex":0.0023442786,"about_ca_topic_score_gemma":0.002190979,"teacher_disagreement_score":0.0023442786,"about_ca_system_score_codex":0.00038315717,"about_ca_system_score_gemma":0.00058334187,"threshold_uncertainty_score":0.0070385337},"labels":[],"label_agreement":null}]}