{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":107,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":107,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"query_hash":"affdb47e25c4","filters":{"venue":"Computer-Aided Civil and Infrastructure Engineering"}},"results":[{"id":"W2598457882","doi":"10.1111/mice.12263","title":"Deep Learning‐Based Crack Damage Detection Using Convolutional Neural Networks","year":2017,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":3134,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Convolutional neural network; Sobel operator; Computer science; Artificial intelligence; Robustness (evolution); Pixel; Computer vision; Canny edge detector; Shadow (psychology); Deep learning; Pattern recognition (psychology); Adaptability; Image (mathematics); Edge detection; Image processing","retraction":null,"screen_n_in":null,"score":{"opus":0.004973053066563081,"gpt":0.1899400987236036,"spread":0.1849670456570405,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000107546,0.00042384,0.0003409473,0.0001599202,0.0005953733,0.0003645639,0.0003087662,0.0002278571,0.00002181026],"category_scores_gemma":[0.00004535647,0.0004364282,0.0001008895,0.00009565871,0.00008520947,0.0005085793,0.0001392591,0.0007884286,0.000001243315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001285697,"about_ca_system_score_gemma":0.00001174633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001313697,"about_ca_topic_score_gemma":0.000009972803,"domain_scores_codex":[0.9985781,0.0000180907,0.0003067469,0.0003404466,0.0001783688,0.0005782462],"domain_scores_gemma":[0.999202,0.0000512909,0.000107614,0.0003881938,0.00007605796,0.0001748496],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007514811,0.000002108695,0.002527372,0.00008331297,0.00004129613,0.00001672698,0.00005358192,0.9779424,0.003429384,0.00005725275,0.00002288992,0.01581613],"study_design_scores_gemma":[0.0004746333,0.00004138371,0.1170157,0.00008203555,0.00002555523,0.00005794732,0.000008471576,0.8803628,0.0007083169,0.00005473756,0.0007636041,0.0004048038],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3908195,0.0001950761,0.6061382,0.000005672883,0.002340446,0.00008866489,0.000001611592,0.0003272927,0.00008349634],"genre_scores_gemma":[0.9892836,0.00002549051,0.008575122,0.00003103523,0.001982531,0.000007867629,0.0000111154,0.00007792399,0.000005330974],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.598464,"threshold_uncertainty_score":0.9998087,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2768955070","doi":"10.1111/mice.12334","title":"Autonomous Structural Visual Inspection Using Region‐Based Deep Learning for Detecting Multiple Damage Types","year":2017,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":1520,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"","keywords":"Convolutional neural network; Computer science; Artificial intelligence; Visual inspection; Robustness (evolution); Pixel; Pattern recognition (psychology); Computer vision; Deep learning","retraction":null,"screen_n_in":null,"score":{"opus":0.008204456037696393,"gpt":0.2214790530364932,"spread":0.2132745969987968,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00010953,0.0004705011,0.0004142252,0.0002346177,0.0009911282,0.0004322034,0.000294028,0.0002261682,0.000004772716],"category_scores_gemma":[0.0001573729,0.0004799895,0.0001235536,0.0001006447,0.00006905491,0.0005620192,0.0001278592,0.0005700694,6.391797e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001928971,"about_ca_system_score_gemma":0.00002328854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002253065,"about_ca_topic_score_gemma":0.00002049193,"domain_scores_codex":[0.998444,0.00001477812,0.0003613593,0.0004164562,0.0001431052,0.0006203654],"domain_scores_gemma":[0.999131,0.0001099436,0.0001584581,0.0003510817,0.00009804041,0.0001514488],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001646604,0.000001790481,0.006176726,0.0002295799,0.00006110409,0.00001174196,0.0002520766,0.9375116,0.01402075,0.00006502331,0.00001676616,0.04163641],"study_design_scores_gemma":[0.000836733,0.0000845093,0.05235176,0.0001614758,0.00003810594,0.00006685619,0.00003451332,0.9402376,0.004809236,0.000133111,0.0007330714,0.0005129819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.492726,0.0001109318,0.5046669,0.000004856409,0.001746098,0.0001712539,0.000002309964,0.000528915,0.00004272565],"genre_scores_gemma":[0.968092,0.00001126743,0.02995123,0.00001644217,0.001780866,0.00001795814,0.00001387962,0.0001115089,0.000004852985],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.475366,"threshold_uncertainty_score":0.9997652,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2804948039","doi":"10.1111/mice.12375","title":"Autonomous UAVs for Structural Health Monitoring Using Deep Learning and an Ultrasonic Beacon System with Geo‐Tagging","year":2018,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":376,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"","keywords":"Global Positioning System; Beacon; Bridge (graph theory); Structural health monitoring; Computer science; Convolutional neural network; Real-time computing; Artificial intelligence; Deep learning; Ultrasonic sensor; GPS signals; Computer vision; Remote sensing; Assisted GPS; Engineering; Telecommunications; Geography; Acoustics","retraction":null,"screen_n_in":null,"score":{"opus":0.004909401045395913,"gpt":0.2188677157867856,"spread":0.2139583147413897,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002046339,0.0006166601,0.0006183981,0.0002643308,0.0005516434,0.0002829904,0.0001927762,0.0001856182,0.000003185302],"category_scores_gemma":[0.00001473979,0.0005697021,0.00005971829,0.0002239698,0.00009141778,0.0005800296,0.00008405917,0.0005435052,3.587216e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003439529,"about_ca_system_score_gemma":0.00004440059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003087419,"about_ca_topic_score_gemma":0.00001224959,"domain_scores_codex":[0.9977604,0.00002751697,0.0004683921,0.0005844022,0.0001928574,0.0009664528],"domain_scores_gemma":[0.9990704,0.00007759086,0.0001301424,0.0002537877,0.0001191844,0.000348916],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004000132,0.000003243275,0.005879785,0.001483299,0.0001945843,0.00001397778,0.003004409,0.8889898,0.01349833,0.0008164212,0.00001612301,0.08605999],"study_design_scores_gemma":[0.0008373996,0.0004854071,0.01714776,0.0007396956,0.00004281466,0.0004633659,0.0005227975,0.9757352,0.002339866,0.0000381843,0.000943447,0.0007039987],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5810475,0.0009037837,0.4156128,0.000005207404,0.001425143,0.0002802571,0.00000597163,0.0006899582,0.00002942688],"genre_scores_gemma":[0.9077339,0.00005713801,0.08879991,0.00001809695,0.003214727,0.00001963094,0.00001325379,0.0001407054,0.000002674123],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3268129,"threshold_uncertainty_score":0.9996755,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2122240896","doi":"10.1111/mice.12122","title":"Structural Damage Detection Using Modal Strain Energy and Hybrid Multiobjective Optimization","year":2015,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":222,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"Shell","keywords":"Modal; Structural health monitoring; Robustness (evolution); Computer science; Multi-objective optimization; Algorithm; Mathematical optimization; Structural engineering; Mathematics; Engineering; Materials science; Machine learning","retraction":null,"screen_n_in":null,"score":{"opus":0.01092976927454278,"gpt":0.2159024413505919,"spread":0.2049726720760491,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0000853188,0.0003707133,0.0002997764,0.0002428,0.0001067364,0.0001138784,0.0001153921,0.0001502746,0.000003739349],"category_scores_gemma":[0.00002503834,0.0003830546,0.00003301271,0.000191092,0.00004417415,0.0004718707,0.0001042666,0.0002764365,1.040888e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002398487,"about_ca_system_score_gemma":0.00002146052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005673909,"about_ca_topic_score_gemma":0.000007002436,"domain_scores_codex":[0.9987973,0.00002642653,0.0003017835,0.0003253796,0.0001736985,0.000375441],"domain_scores_gemma":[0.9993669,0.00004184709,0.00005540421,0.0001850624,0.00008283251,0.0002679072],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008064346,8.824299e-7,0.0001381123,0.000084277,0.00002504571,0.000006508925,0.0002233968,0.9651598,0.002248411,0.00008886349,0.00002190446,0.03199477],"study_design_scores_gemma":[0.0004173964,0.00007928914,0.01389336,0.00006528221,0.0000160433,0.0002090542,0.00002777642,0.9811511,0.003077997,0.000588576,0.00009884694,0.0003752862],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5656559,0.0002003793,0.4326431,0.000003203444,0.0008009697,0.00009670799,0.00001514999,0.0005665851,0.00001804916],"genre_scores_gemma":[0.8995736,0.00003688048,0.09964508,0.00001568368,0.0006402422,0.000008638441,0.00001689118,0.00006171537,0.000001225192],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3339178,"threshold_uncertainty_score":0.9998621,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2058350584","doi":"10.1111/j.1467-8667.2009.00632.x","title":"Fuzzy Monte Carlo Simulation and Risk Assessment in Construction","year":2009,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":207,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Canadian Natural Resources; University of Alberta","funders":"","keywords":"Monte Carlo method; Probabilistic logic; Fuzzy logic; Computer science; Range (aeronautics); Uncertainty analysis; Reliability engineering; Probability distribution; Construct (python library); Mathematical optimization; Data mining; Risk analysis (engineering); Operations research; Artificial intelligence; Simulation; Engineering; Mathematics; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.002812116848648407,"gpt":0.1979950191693164,"spread":0.195182902320668,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001068963,0.0003215881,0.0003150291,0.0002483336,0.0000751031,0.000108243,0.00008492257,0.0001564503,0.000003540125],"category_scores_gemma":[0.00001674062,0.0003219886,0.00003810643,0.000205549,0.00002845137,0.0003734844,0.00003894207,0.0005461851,3.660875e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001121091,"about_ca_system_score_gemma":0.00001169917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001166034,"about_ca_topic_score_gemma":0.000007847682,"domain_scores_codex":[0.998862,0.00001634428,0.0003318537,0.0002895894,0.0001333574,0.0003669111],"domain_scores_gemma":[0.9995698,0.00005550641,0.00005142872,0.0001725838,0.00003771366,0.000113],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003925935,0.000002323355,0.008524861,0.00004768486,0.00002131447,0.000007743715,0.0002596577,0.9130105,0.0006910752,0.0004211633,0.00003491882,0.07697476],"study_design_scores_gemma":[0.000401208,0.00004784222,0.3381745,0.0000882302,0.00001348485,0.0000319814,0.00002783757,0.6595842,0.00008780164,0.0008989513,0.0004026055,0.000241389],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8687446,0.0004307996,0.1290454,0.00001572368,0.0009393244,0.0001649266,0.000006285681,0.0002935149,0.0003594577],"genre_scores_gemma":[0.9718912,0.0003060576,0.02725229,0.00002532608,0.0004871156,0.000005275604,0.000003234297,0.0000275663,0.00000188643],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3296497,"threshold_uncertainty_score":0.9999232,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1509636799","doi":"10.1111/j.1467-8667.2012.00760.x","title":"Wavelet‐Based Detection of Beam Cracks Using Modal Shape and Frequency Measurements","year":2012,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":124,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; University of Ottawa; National Science Foundation","keywords":"Cantilever; Wavelet; Modal; Beam (structure); Acoustics; Natural frequency; Finite element method; Modal analysis; Structural engineering; Wavelet transform; Noise (video); Materials science; Computer science; Vibration; Engineering; Physics; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.01810893953962981,"gpt":0.2298481129179842,"spread":0.2117391733783544,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001424094,0.0003065919,0.0003125454,0.000220437,0.00007275804,0.00002990612,0.0001094869,0.0001788844,0.000008297628],"category_scores_gemma":[0.00002078641,0.0003124446,0.00004207237,0.0001890069,0.00003431856,0.000334012,0.00005867921,0.0002969176,2.314212e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001321965,"about_ca_system_score_gemma":0.00001225581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002154419,"about_ca_topic_score_gemma":0.000001305726,"domain_scores_codex":[0.9988092,0.00001457187,0.0003518489,0.0001963012,0.0001972766,0.0004307852],"domain_scores_gemma":[0.9994425,0.00004645822,0.00006458597,0.0001950893,0.00005688291,0.0001945546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000157818,0.00001576109,0.01618314,0.002000581,0.0001319364,0.000002910674,0.0005762422,0.12137,0.6799792,0.00008731104,0.00004269562,0.1795945],"study_design_scores_gemma":[0.0002997311,0.00006688704,0.2394527,0.0002075352,0.00002835647,0.00004971214,0.00000562566,0.6828864,0.07645592,0.0001390859,0.00006556883,0.000342508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.849935,0.0009835813,0.1475018,0.000002453074,0.0009950037,0.0001572986,0.000005960059,0.0003972306,0.00002170881],"genre_scores_gemma":[0.9329448,0.00002462361,0.06643341,0.00001313698,0.0005224054,0.000007801336,0.000003070086,0.00005041841,2.827422e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6035233,"threshold_uncertainty_score":0.9999328,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3011931516","doi":"10.1111/mice.12549","title":"Postdisaster image-based damage detection and repair cost estimation of reinforced concrete buildings using dual convolutional neural networks","year":2020,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":118,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Convolutional neural network; Computer science; Identification (biology); Artificial neural network; Reinforced concrete; Dual (grammatical number); Artificial intelligence; Reliability engineering; Risk analysis (engineering); Machine learning; Structural engineering; Engineering; Business","retraction":null,"screen_n_in":null,"score":{"opus":0.004896695296489259,"gpt":0.1828219904729464,"spread":0.1779252951764571,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008037774,0.0003366379,0.0003548627,0.0001234799,0.00009049077,0.00007543295,0.00008342459,0.000157588,0.000008955732],"category_scores_gemma":[0.00004069151,0.0003486489,0.00007770079,0.0002145819,0.00007888924,0.0004101816,0.00008444935,0.0003755947,2.100039e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006231093,"about_ca_system_score_gemma":0.0000143201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005997449,"about_ca_topic_score_gemma":4.8448e-7,"domain_scores_codex":[0.9987927,0.00001553801,0.0004086656,0.0002860495,0.0001547716,0.000342292],"domain_scores_gemma":[0.9994475,0.0000678807,0.00009018252,0.0001407452,0.00007849492,0.0001751848],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002709431,2.723374e-7,0.0001461141,0.0002867385,0.00004058863,0.000007432241,0.0002010841,0.9366904,0.0599209,0.00009223408,0.00004174479,0.002545355],"study_design_scores_gemma":[0.000720272,0.00009758185,0.006335673,0.0001237555,0.00004044687,0.00005877492,0.00002448973,0.9860856,0.006102028,0.000009217782,0.00008218028,0.0003199642],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4960615,0.00008455797,0.5030819,0.000008527445,0.0003868768,0.0001313742,0.000007753966,0.0002279601,0.000009581648],"genre_scores_gemma":[0.9561346,0.000009712181,0.04313498,0.00009046304,0.0005558983,0.000005984324,0.00001911855,0.00004863811,5.808693e-7],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4600731,"threshold_uncertainty_score":0.9998965,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2099862864","doi":"10.1111/1467-8667.00279","title":"Probabilistic Neural Network for Reliability Assessment of Oil and Gas Pipelines","year":2002,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":110,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Pipeline transport; Artificial neural network; Probabilistic logic; Reliability (semiconductor); Magnetic flux leakage; Fuzzy logic; Probabilistic neural network; Engineering; Reliability engineering; Computer science; Machine learning; Artificial intelligence; Time delay neural network","retraction":null,"screen_n_in":null,"score":{"opus":0.007548530011889236,"gpt":0.2033616333055661,"spread":0.1958131032936769,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001630819,0.0003161001,0.0005108697,0.00008890306,0.00008374849,0.00005780772,0.0001465629,0.0001700132,0.00004053417],"category_scores_gemma":[0.00007845132,0.0002699995,0.0001228517,0.000233192,0.0001003983,0.0001590463,0.00007347186,0.0003332651,1.98671e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004644186,"about_ca_system_score_gemma":0.000005691785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009184329,"about_ca_topic_score_gemma":0.000008973402,"domain_scores_codex":[0.9986861,0.00002081996,0.0004795936,0.0003334538,0.0001357854,0.0003442255],"domain_scores_gemma":[0.9991584,0.0002828952,0.00005792576,0.0002700013,0.0001005063,0.0001302594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003393078,0.000007335489,0.0007778906,0.001028844,0.00006655462,8.672899e-7,0.0001140687,0.9591154,0.0004177863,0.0005675869,0.0006574489,0.03724285],"study_design_scores_gemma":[0.0003141022,0.00008043357,0.01621138,0.000101897,0.00006984835,0.00002429548,0.000008999991,0.9796649,0.00006275192,0.001679091,0.00150977,0.0002725926],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9002333,0.001797722,0.09598546,0.0002023443,0.001020871,0.0001818289,0.00003803904,0.0003146659,0.0002257384],"genre_scores_gemma":[0.9566321,0.0004699052,0.0422882,0.00002869024,0.0004962202,0.00002175885,0.00001317449,0.00003083755,0.00001905667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05639884,"threshold_uncertainty_score":0.9999752,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2021428030","doi":"10.1111/j.1467-8667.2006.00458.x","title":"Comparison of Two Evolutionary Algorithms for Optimization of Bridge Deck Repairs","year":2006,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":106,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Bridge (graph theory); Computer science; Genetic algorithm; Prioritization; Selection (genetic algorithm); Deck; Operations research; Evolutionary algorithm; Optimization problem; Bridge maintenance; Mathematical optimization; Reliability engineering; Engineering; Artificial intelligence; Management science; Machine learning; Algorithm; Structural engineering; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.007563008613780916,"gpt":0.2336712894310342,"spread":0.2261082808172533,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007605508,0.000262836,0.0004524813,0.0001898793,0.00004856298,0.0000177506,0.0001398149,0.0001156804,0.00000684343],"category_scores_gemma":[0.00001449656,0.0002700946,0.0001010415,0.0002033004,0.00004433975,0.0001726082,0.00005007223,0.0001585486,1.305331e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005874036,"about_ca_system_score_gemma":0.00001626392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001607166,"about_ca_topic_score_gemma":0.000002383848,"domain_scores_codex":[0.9987727,0.00000742791,0.0005598568,0.000214239,0.0001477223,0.0002980868],"domain_scores_gemma":[0.9994283,0.00007639388,0.0001128883,0.0001981428,0.0001281133,0.00005621101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007398462,0.000008990666,0.004966203,0.0003572236,0.00004331073,7.885309e-7,0.0001193349,0.9843913,0.005521556,0.0008931542,0.001252318,0.002438413],"study_design_scores_gemma":[0.000578034,0.0000745535,0.09095311,0.0001458198,0.00002902568,0.00001576031,0.00001156789,0.9018222,0.005088089,0.0004234381,0.000623455,0.0002349419],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1862916,0.0006689237,0.8116548,0.00000375166,0.000891968,0.0001853955,0.00002899499,0.0001834383,0.00009106999],"genre_scores_gemma":[0.7896737,0.00001955385,0.2096514,0.000003449074,0.0005562703,0.00001134436,0.00004378277,0.00003821425,0.000002309978],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6033821,"threshold_uncertainty_score":0.9999751,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1506789237","doi":"10.1111/j.1467-8667.2010.00650.x","title":"Modeling Framework and Architecture of Hybrid System Dynamics and Discrete Event Simulation for Construction","year":2010,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"BIM and Construction Integration","field":"Engineering","cited_by":104,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; U.S. Department of Defense","keywords":"Computer science; System dynamics; Context (archaeology); Hybrid system; Architecture; Event (particle physics); Discrete event simulation; Systems engineering; Complex system; Distributed computing; Systems modeling; Industrial engineering; Simulation; Artificial intelligence; Engineering; Software engineering; Machine learning","retraction":null,"screen_n_in":null,"score":{"opus":0.002402853640755542,"gpt":0.1818860790829981,"spread":0.1794832254422426,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000664964,0.0002094664,0.0002342073,0.0001344273,0.00007205219,0.00005922371,0.00004911092,0.0001300188,0.000002240384],"category_scores_gemma":[0.00002108712,0.0002007103,0.00003464784,0.00007366517,0.00004841799,0.0001423155,0.00002983971,0.0003250256,4.783798e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000249509,"about_ca_system_score_gemma":0.000007371602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002786187,"about_ca_topic_score_gemma":0.00000677646,"domain_scores_codex":[0.9992638,0.000006370083,0.0002922689,0.000201592,0.00008012727,0.0001558553],"domain_scores_gemma":[0.9996064,0.00008648737,0.00004532791,0.0001232917,0.00005694953,0.00008159781],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008639777,8.12903e-7,0.0001249225,0.0004350146,0.00002864585,2.982964e-7,0.0001111661,0.8983681,0.002286941,0.01872374,0.000001759678,0.07990993],"study_design_scores_gemma":[0.0003178221,0.00003576385,0.0005223913,0.0001649534,0.00002832298,0.0001580703,0.00005361675,0.9954267,0.000673442,0.002353205,0.00007441452,0.000191372],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4052852,0.000117239,0.5936753,0.000006979311,0.0006368684,0.0001344443,0.00002060629,0.0001111797,0.0000122274],"genre_scores_gemma":[0.8919475,0.0000205079,0.1077238,0.000004077282,0.0002492067,0.00001189021,0.00001710608,0.00002529941,6.588602e-7],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4866623,"threshold_uncertainty_score":0.8184729,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1899685495","doi":"10.1111/j.1467-8667.2011.00732.x","title":"Hybrid Time‐Frequency Blind Source Separation Towards Ambient System Identification of Structures","year":2011,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":96,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Swedish Orphan Biovitrum","keywords":"Blind signal separation; Identification (biology); Computer science; Frequency domain; Energy (signal processing); Algorithm; Hilbert–Huang transform; Mathematics; Telecommunications","retraction":null,"screen_n_in":null,"score":{"opus":0.0100966014116902,"gpt":0.2220081456690892,"spread":0.211911544257399,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001487231,0.0003548557,0.0003905522,0.0002822481,0.00007273824,0.00004937584,0.000275475,0.0001544347,0.00002105341],"category_scores_gemma":[0.0000157426,0.0003512416,0.00007100399,0.0002018543,0.00004284609,0.000281283,0.00007760542,0.0002847326,0.000003255813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001553826,"about_ca_system_score_gemma":0.00002113688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003328366,"about_ca_topic_score_gemma":5.254832e-7,"domain_scores_codex":[0.998398,0.00002432272,0.0006840043,0.0003165804,0.0002356752,0.0003414395],"domain_scores_gemma":[0.9991947,0.00002818904,0.0001479943,0.0003813399,0.0001028248,0.000144989],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008848784,0.00002924677,0.001625881,0.006641437,0.0004373009,0.00003403755,0.005839979,0.5268954,0.2638124,0.008887031,0.001684149,0.1840247],"study_design_scores_gemma":[0.0004324933,0.0001355806,0.147762,0.0002771163,0.00005008464,0.0001777329,0.0000285512,0.6726869,0.1762261,0.001438129,0.0002199173,0.0005653266],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7355888,0.0002793731,0.261651,0.000002319075,0.001059048,0.0002611859,0.0000169038,0.0009713396,0.0001700756],"genre_scores_gemma":[0.972056,0.00003468553,0.02741012,0.000005800235,0.0003837975,0.00002155341,0.00002188861,0.00005994765,0.000006185978],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2364672,"threshold_uncertainty_score":0.999894,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2790882261","doi":"10.1111/mice.12344","title":"Modeling Relationship between Truck Fuel Consumption and Driving Behavior Using Data from Internet of Vehicles","year":2018,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":93,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"Ministry of Transport of the People's Republic of China; National Natural Science Foundation of China","keywords":"Truck; Fuel efficiency; Automotive engineering; Modal; Computer science; Energy consumption; The Internet; Index (typography); Consumption (sociology); Fuel cells; Regression analysis; Simulation; Transport engineering; Engineering; Machine learning","retraction":null,"screen_n_in":null,"score":{"opus":0.04064972787617242,"gpt":0.2522759280864324,"spread":0.21162620021026,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001058902,0.0002079847,0.0002545675,0.0001300827,0.00006493844,0.00006208002,0.0002063729,0.0001342192,0.0000203005],"category_scores_gemma":[0.00002004068,0.0002114837,0.00002050626,0.0001045809,0.00005181677,0.0004293131,0.0002417346,0.0002586007,0.000001177595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002476436,"about_ca_system_score_gemma":0.000009074917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002782694,"about_ca_topic_score_gemma":0.00001013493,"domain_scores_codex":[0.9990787,0.00001187424,0.0003385036,0.0002654071,0.0001048124,0.0002007087],"domain_scores_gemma":[0.9993929,0.0001032563,0.00004188369,0.0003200116,0.00003244609,0.0001094773],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004853503,0.000005170485,0.7108003,0.0002730365,0.00006477789,0.000002166683,0.0007533251,0.2630156,0.009017105,0.00008338432,0.00006930518,0.01591098],"study_design_scores_gemma":[0.0001658632,0.00001570349,0.3321159,0.0002082862,0.00003447977,0.000009538464,0.00000629554,0.6668561,0.0003094816,0.00007411464,0.00005606228,0.0001481737],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6748942,0.0004522535,0.3242632,0.000001830021,0.0002010939,0.00005870338,0.00002513703,0.00009514112,0.000008509365],"genre_scores_gemma":[0.9647777,0.00005895707,0.03458742,0.000004204286,0.0004751939,0.000001770009,0.00006029728,0.00003307397,0.000001385678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4038406,"threshold_uncertainty_score":0.8624056,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2118277919","doi":"10.1111/j.1467-8667.2006.00444.x","title":"GPS–GIS-Based Procedure for Tracking Vehicle Path on Horizontal Alignments","year":2006,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Traffic and Road Safety","field":"Engineering","cited_by":90,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"","keywords":"Global Positioning System; Differential GPS; Computer science; Horizontal position representation; Track (disk drive); Path (computing); Filter (signal processing); Position (finance); Horizontal and vertical; Geodesy; Geographic information system; Geology; Computer vision; Mathematics; Remote sensing; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.003230509362542492,"gpt":0.1683077178143788,"spread":0.1650772084518363,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00006796362,0.0003692461,0.000292899,0.0001176996,0.0001129566,0.00007938914,0.0001498541,0.0001707873,0.000009033607],"category_scores_gemma":[0.000007031815,0.0003495107,0.00009873709,0.0001393481,0.00002020667,0.0001439718,0.0000250491,0.0002485421,0.000002313829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008413276,"about_ca_system_score_gemma":0.00001710637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002737601,"about_ca_topic_score_gemma":0.000003919895,"domain_scores_codex":[0.9987506,0.000006485644,0.0002938749,0.0003239869,0.0001753509,0.0004497434],"domain_scores_gemma":[0.9995742,0.00006800424,0.00003619088,0.0001811437,0.00002852319,0.0001119687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000170861,0.00002092739,0.0006721478,0.0002967945,0.00003790145,0.000008133607,0.00007750891,0.9781724,0.004560873,0.0009246605,0.002547828,0.01266381],"study_design_scores_gemma":[0.001229587,0.0001826822,0.06948888,0.0001931917,0.00002327768,0.00001533847,0.000009193716,0.917385,0.003701648,0.0001645041,0.007125369,0.0004813332],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5305024,0.0003266991,0.4667058,0.00003135912,0.000916199,0.0003529006,0.00004577499,0.0008168351,0.00030211],"genre_scores_gemma":[0.9892088,0.000009275054,0.009700967,0.00006497499,0.0008360859,0.00003226695,0.00005703565,0.00008038351,0.00001023835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4587064,"threshold_uncertainty_score":0.9998957,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2141608439","doi":"10.1111/j.1467-8667.2006.00460.x","title":"Active Control of Structures Using Energy-Based LQR Method","year":2006,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Vibration Control and Rheological Fluids","field":"Engineering","cited_by":90,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Linear-quadratic regulator; Control theory (sociology); Energy (signal processing); Matrix (chemical analysis); Displacement (psychology); Selection (genetic algorithm); Control (management); Computer science; Engineering; Mathematics; Materials science; Statistics; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.003129855442097571,"gpt":0.1789080284455732,"spread":0.1757781730034756,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00006665001,0.0003147403,0.0004509682,0.000178239,0.00005730726,0.00004128068,0.0001420686,0.0001849503,0.00005180517],"category_scores_gemma":[0.00001197919,0.0002689977,0.0001019303,0.000202422,0.00004041772,0.0001485021,0.0000318058,0.0001999602,2.171158e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003957073,"about_ca_system_score_gemma":0.00001889782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002053334,"about_ca_topic_score_gemma":0.000003861127,"domain_scores_codex":[0.9989074,0.00003116803,0.0003721849,0.0002366995,0.0001527787,0.0002997147],"domain_scores_gemma":[0.9994698,0.0001534313,0.00005524346,0.000170234,0.00006116932,0.00009013559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001293935,0.000004851557,0.000116654,0.00007058455,0.00005604505,0.000003665896,0.00001682866,0.8981268,0.08560782,0.008456199,0.0001013144,0.007426348],"study_design_scores_gemma":[0.0009332485,0.00005119444,0.009795367,0.00003769645,0.00003580693,0.0000179808,0.000002697668,0.9641628,0.02192279,0.001968793,0.0007918781,0.0002797288],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05267464,0.0006031989,0.9457086,0.00001343869,0.0004424021,0.00008793185,0.00002998242,0.0002573168,0.0001824603],"genre_scores_gemma":[0.924598,0.000006971497,0.07483012,0.00007192124,0.0004362476,0.000005541528,0.00001512717,0.00003314251,0.000002895003],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8719234,"threshold_uncertainty_score":0.9999762,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2162582686","doi":"10.1111/j.1467-8667.2010.00710.x","title":"Durability Monitoring for Improved Service Life Predictions of Concrete Bridge Decks in Corrosive Environments","year":2011,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Concrete Corrosion and Durability","field":"Engineering","cited_by":89,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"National Research Council Canada","funders":"","keywords":"Durability; Service life; Bridge (graph theory); Probabilistic logic; Life-cycle assessment; Corrosion; Computer science; Reinforced concrete; Service (business); Life span; Forensic engineering; Environmental science; Reliability engineering; Engineering; Structural engineering; Database; Materials science; Business; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.01308610770133053,"gpt":0.1882508964387228,"spread":0.1751647887373922,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001344185,0.0002895872,0.0004021658,0.0001221144,0.00004457191,0.00001925846,0.0001839076,0.0001599508,0.00002705823],"category_scores_gemma":[0.00006828122,0.000308229,0.00008048063,0.0001750276,0.00004075663,0.000208792,0.0001028347,0.0002647513,8.173686e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008701683,"about_ca_system_score_gemma":0.00002105226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000289293,"about_ca_topic_score_gemma":0.00000749541,"domain_scores_codex":[0.9987397,0.00001622473,0.0005067114,0.0003191571,0.00009142527,0.0003267618],"domain_scores_gemma":[0.999257,0.0001209344,0.00006393254,0.000314706,0.00004624758,0.0001971523],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002878496,0.00004411243,0.07983916,0.003032531,0.000227771,0.000006897168,0.00939431,0.2557393,0.6359754,0.0003902014,0.0004424568,0.01462005],"study_design_scores_gemma":[0.0008108609,0.00006676969,0.4450075,0.00009895721,0.00002106696,0.000006427475,0.00003455351,0.545348,0.007929957,0.00009075426,0.0003233658,0.0002617825],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.751191,0.0002085978,0.2470271,0.000007677556,0.0009324246,0.0003817232,0.0000586425,0.0001495281,0.00004326459],"genre_scores_gemma":[0.9914685,0.00006777076,0.008183178,0.00002760334,0.0001452349,0.00005500994,0.00001272763,0.00003792887,0.000002007667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6280454,"threshold_uncertainty_score":0.999937,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4321783250","doi":"10.1111/mice.12981","title":"Large‐scale building damage assessment using a novel hierarchical transformer architecture on satellite images","year":2023,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":88,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"Texas A and M University","keywords":"Computer science; Transformer; Architecture; Deep learning; Satellite imagery; Encoder; Artificial intelligence; Data mining; Real-time computing; Remote sensing; Engineering; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.008401223590461457,"gpt":0.2299937896692188,"spread":0.2215925660787574,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002054752,0.0004734845,0.0003996387,0.0004909429,0.0001523575,0.0002020657,0.0002096741,0.0001943021,0.0000120836],"category_scores_gemma":[0.00001677296,0.000464131,0.0001118352,0.0006161067,0.00005145959,0.0002278576,0.0000662922,0.0008164558,0.000004880495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001384806,"about_ca_system_score_gemma":0.00002619015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000143401,"about_ca_topic_score_gemma":0.000002017384,"domain_scores_codex":[0.9981216,0.00002438916,0.0003948233,0.0004816356,0.0003010489,0.0006765241],"domain_scores_gemma":[0.9991953,0.0001469596,0.00004303874,0.0003695122,0.00003924351,0.0002059935],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004367552,0.000008662484,0.00006844717,0.000187158,0.00004288542,0.00001231689,0.000486714,0.6170051,0.3687808,0.0002516166,0.0001016093,0.01305029],"study_design_scores_gemma":[0.0005649793,0.00004695286,0.0526069,0.0002744804,0.00002605574,0.00007352934,0.00003380952,0.9345961,0.006737398,0.0003161654,0.004242151,0.0004814339],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3941445,0.00006394486,0.6040034,0.00006511798,0.0005222458,0.0001602433,0.00002567887,0.0007769031,0.0002379287],"genre_scores_gemma":[0.8354411,0.00009534133,0.1637128,0.00005974987,0.0005004578,0.000005645599,0.00004912035,0.0001233894,0.00001232393],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4412966,"threshold_uncertainty_score":0.999781,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2097548601","doi":"10.1111/j.1467-8667.2007.00485.x","title":"Reliability‐Based Optimal Design of Electrical Transmission Towers Using Multi‐Objective Genetic Algorithms","year":2007,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":82,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Truss; Reliability (semiconductor); Tower; Finite element method; Optimal design; Reliability engineering; Genetic algorithm; Mathematical optimization; Transmission tower; Multi-objective optimization; Computer science; Pareto principle; Engineering; Structural engineering; Algorithm; Mathematics; Power (physics); Machine learning","retraction":null,"screen_n_in":null,"score":{"opus":0.02931576540461784,"gpt":0.2749596291893149,"spread":0.2456438637846971,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001447739,0.0003595925,0.0005471719,0.0005011451,0.0001078529,0.00008017128,0.0004480035,0.0002344475,0.0000301822],"category_scores_gemma":[0.00047049,0.0002830889,0.0001349595,0.0009089113,0.0001066415,0.0001865365,0.00007955748,0.000369643,0.000001059067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001141759,"about_ca_system_score_gemma":0.0001185056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008134318,"about_ca_topic_score_gemma":1.417162e-7,"domain_scores_codex":[0.9972242,0.00008467604,0.0008698149,0.000644282,0.0006602856,0.0005167241],"domain_scores_gemma":[0.9975942,0.001294763,0.0001629727,0.0004057396,0.0002606457,0.0002816841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004647532,0.00002799404,0.0001303951,0.00002876419,0.00001873044,0.00001541636,0.0002271791,0.9188374,0.0147484,0.00004785969,0.00003608304,0.06583524],"study_design_scores_gemma":[0.0006483668,0.0002390674,0.01970493,0.0000748297,0.00002664273,0.00004773516,0.00001747392,0.974797,0.003553127,0.0003184694,0.0002589427,0.0003133753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07233505,0.0005460554,0.9263167,0.000006128204,0.0003869381,0.0002935867,0.000004109768,0.0001024649,0.000008960997],"genre_scores_gemma":[0.4627115,0.000008574934,0.5371392,0.00001482285,0.00009888295,0.000001986693,9.376012e-7,0.00001988194,0.000004198596],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3903764,"threshold_uncertainty_score":0.9999622,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2064277258","doi":"10.1111/j.1467-8667.2005.00384.x","title":"Progressive-Failure Analysis of Buildings Subjected to Abnormal Loading","year":2005,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Structural Response to Dynamic Loads","field":"Engineering","cited_by":82,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Progressive collapse; Structural engineering; Stiffness; Shearing (physics); Residual; Residual strength; Shear (geology); Demolition; Engineering; Computer science; Geotechnical engineering; Materials science; Reinforced concrete; Composite material","retraction":null,"screen_n_in":null,"score":{"opus":0.002160920146983566,"gpt":0.182781341739469,"spread":0.1806204215924854,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001021572,0.0004148969,0.0006223842,0.0009766264,0.00005308261,0.00008036234,0.0003099561,0.0001664613,0.0001208874],"category_scores_gemma":[0.00005096956,0.0004029168,0.0001553355,0.001535234,0.00003483934,0.0002899816,0.0001422809,0.0003220837,0.00000328425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001336604,"about_ca_system_score_gemma":0.00001702435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004818004,"about_ca_topic_score_gemma":0.00001210782,"domain_scores_codex":[0.9983785,0.0000155477,0.0004802743,0.0003581822,0.0002584969,0.0005089642],"domain_scores_gemma":[0.9991471,0.0001143781,0.00006801863,0.0003242672,0.00008446341,0.0002617509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001519513,0.000003303323,0.001286474,0.0000953354,0.0006334641,0.00001115524,0.0005619509,0.924423,0.05052705,0.0002998092,0.0002631811,0.0218801],"study_design_scores_gemma":[0.0003516714,0.0000601644,0.1265413,0.0001003725,0.0002410327,0.00007373272,0.00001362301,0.8558027,0.01339784,0.00001725282,0.002913661,0.0004866234],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8776374,0.0004269462,0.1209117,0.00003622755,0.0002544588,0.0001675319,0.0000215557,0.000460625,0.00008348296],"genre_scores_gemma":[0.9363306,0.00001141498,0.06323292,0.00003742354,0.000297104,0.00001158355,0.00001754124,0.00005253459,0.000008946592],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1252548,"threshold_uncertainty_score":0.9998423,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3137738592","doi":"10.1111/mice.12655","title":"A knowledge‐enhanced deep reinforcement learning‐based shape optimizer for aerodynamic mitigation of wind‐sensitive structures","year":2021,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Wind and Air Flow Studies","field":"Environmental Science","cited_by":78,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Reinforcement learning; Aerodynamics; Computer science; Artificial neural network; Artificial intelligence; Domain knowledge; Shape optimization; Process (computing); Domain (mathematical analysis); Deep learning; Machine learning; Engineering; Aerospace engineering; Mathematics; Structural engineering; Finite element method","retraction":null,"screen_n_in":null,"score":{"opus":0.003787149646000442,"gpt":0.19159702718897,"spread":0.1878098775429696,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006902919,0.000240639,0.0003034918,0.00005057749,0.0001307471,0.00003200015,0.00009292149,0.00008487469,0.0001440105],"category_scores_gemma":[0.00005318995,0.0002245212,0.00009391617,0.0001830181,0.00008016496,0.0001265377,0.0001668075,0.0001609952,0.000001836918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006736792,"about_ca_system_score_gemma":0.00001725112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000294688,"about_ca_topic_score_gemma":0.00001034367,"domain_scores_codex":[0.9989484,0.00002284801,0.0002704387,0.000343863,0.0001449445,0.0002695147],"domain_scores_gemma":[0.9995249,0.0001131096,0.00009403013,0.0001361257,0.00005147042,0.00008040144],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001271351,0.000008771624,0.000225715,0.00009675733,0.0000430775,0.000002105641,0.0006371738,0.9514874,0.03790998,0.00009956731,0.0001183716,0.009358411],"study_design_scores_gemma":[0.0007711669,0.0001213914,0.05556946,0.00009014057,0.00002932749,0.000006926886,0.00006994226,0.9228418,0.01957869,0.000128063,0.0005407307,0.0002523491],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5070121,0.000114808,0.4920579,0.00003154864,0.0002474199,0.0001648538,0.000003332145,0.00004947283,0.0003185789],"genre_scores_gemma":[0.9729631,0.00001772019,0.02669084,0.00006602212,0.0001446549,0.00001001246,0.00003945746,0.00002076346,0.00004745051],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.465951,"threshold_uncertainty_score":0.9155707,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2080802427","doi":"10.1111/0885-9507.00215","title":"A Hybrid AL‐Based System for Site Layout Planning in Construction","year":2001,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"BIM and Construction Integration","field":"Engineering","cited_by":78,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Vagueness; Closeness; Process (computing); Computer science; Knowledge base; Plan (archaeology); Fuzzy logic; Genetic algorithm; Artificial intelligence; Machine learning; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.004685697255764338,"gpt":0.1821016258944007,"spread":0.1774159286386364,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008259809,0.0002688112,0.0002764424,0.0003073833,0.00006622556,0.00009235474,0.00008510103,0.0001060142,0.00001017701],"category_scores_gemma":[0.000008905269,0.0002810443,0.00006150385,0.0001931768,0.00002604016,0.000230523,0.00001772747,0.0002442253,0.000001684656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001202806,"about_ca_system_score_gemma":0.00001626663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005011917,"about_ca_topic_score_gemma":0.000004426188,"domain_scores_codex":[0.9989811,0.00001044906,0.000341982,0.0002567374,0.0001029554,0.0003068332],"domain_scores_gemma":[0.9996112,0.00005982626,0.00004326027,0.0001502443,0.00004379373,0.00009170527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001732784,0.000002903611,0.004242179,0.000249829,0.00002603015,0.00001361643,0.0001258034,0.9685243,0.002654191,0.001538033,0.0004602162,0.02214557],"study_design_scores_gemma":[0.0008172471,0.00003757794,0.007805192,0.0003026449,0.00001300106,0.0003276255,0.00004985983,0.9806808,0.001019675,0.0001121393,0.008535879,0.0002984051],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4174255,0.0002423621,0.5804399,0.00001632606,0.001104277,0.0001545791,0.00001343497,0.000410781,0.0001928605],"genre_scores_gemma":[0.9772193,0.00001295802,0.02225009,0.00005226506,0.0003389127,0.00004507572,0.00003828028,0.00003989888,0.000003163753],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5597938,"threshold_uncertainty_score":0.9999642,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3217407015","doi":"10.1111/mice.12797","title":"Image‐based monitoring of bolt loosening through deep‐learning‐based integrated detection and tracking","year":2021,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Image and Object Detection Techniques","field":"Computer Science","cited_by":71,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Tracking (education); Artificial intelligence; Computer vision; Hough transform; Rotation (mathematics); Computer science; Clamping; Noise (video); Motion blur; Object detection; Preprocessor; Engineering; Image (mathematics); Pattern recognition (psychology)","retraction":null,"screen_n_in":null,"score":{"opus":0.005008102659073955,"gpt":0.2047428335388568,"spread":0.1997347308797828,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001519725,0.0002805167,0.0003249463,0.0002151551,0.0001646949,0.0002847414,0.0002033124,0.0001388937,0.000005885508],"category_scores_gemma":[0.00009774548,0.0002867597,0.00007957438,0.0006045017,0.00004383307,0.0007114592,0.0001504801,0.0004905773,3.319884e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005258486,"about_ca_system_score_gemma":0.00004699699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001539412,"about_ca_topic_score_gemma":0.000002709223,"domain_scores_codex":[0.9986444,0.00006469915,0.000342231,0.0004595921,0.0001951597,0.0002939339],"domain_scores_gemma":[0.9991328,0.0001423778,0.0001323597,0.0002780677,0.0002298933,0.00008452241],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001546391,0.00002723908,0.001179046,0.0004380232,0.00006189448,0.0000892134,0.0009849991,0.06675006,0.4062407,0.0001201695,0.00001221128,0.524081],"study_design_scores_gemma":[0.0002766443,0.00008777912,0.007490037,0.0001594491,0.000009662731,0.00005722841,0.00002957165,0.5062202,0.4850358,0.0001354059,0.0003091522,0.0001890294],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09205187,0.0005478162,0.9063336,0.00002169421,0.000423533,0.00007994648,8.407285e-7,0.0005005957,0.00004008646],"genre_scores_gemma":[0.6814352,0.0000327525,0.3183526,0.00003399545,0.0001167247,0.000005855863,0.000002046894,0.00001870477,0.000002173095],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5893833,"threshold_uncertainty_score":0.9999585,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2985669209","doi":"10.1111/mice.12509","title":"A machine learning approach based on multifractal features for crack assessment of reinforced concrete shells","year":2019,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":70,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"Texas Department of Transportation","keywords":"Structural engineering; Reinforced concrete; Parametric statistics; Cracking; Multifractal system; Computer science; Materials science; Fractal; Engineering; Composite material; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.003053797492701608,"gpt":0.1917627332210062,"spread":0.1887089357283046,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001643684,0.000455261,0.0005581733,0.0002431652,0.00006869391,0.00007241724,0.0002153364,0.0002080224,0.00002739078],"category_scores_gemma":[0.00003707974,0.0004139304,0.0001501183,0.0001718476,0.00002825244,0.0001808646,0.0000634356,0.0006380841,9.262512e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008644781,"about_ca_system_score_gemma":0.00002731912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004192879,"about_ca_topic_score_gemma":2.036013e-7,"domain_scores_codex":[0.9984949,0.00001536582,0.0004123088,0.0003643257,0.0002370564,0.000476059],"domain_scores_gemma":[0.999191,0.0001823232,0.0001024846,0.000300148,0.0001003507,0.0001236717],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002494345,0.000001515907,0.0005689414,0.0007228524,0.00006930099,0.00000178081,0.0001447119,0.966432,0.02596455,0.000727019,0.0001702863,0.005172058],"study_design_scores_gemma":[0.001340966,0.0002697303,0.007157901,0.0002359622,0.00002443685,0.00001505033,0.00002281277,0.9830905,0.005332861,0.00001706387,0.002065833,0.0004268803],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.299588,0.0001970902,0.6946432,0.00001364442,0.001695686,0.0007777463,0.00004307965,0.0004559389,0.002585595],"genre_scores_gemma":[0.909456,0.00002536624,0.08985473,0.0000603093,0.0003767183,0.00002822855,0.00007727888,0.00008263985,0.00003879581],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6098679,"threshold_uncertainty_score":0.9998313,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1998056562","doi":"10.1111/j.1467-8667.2008.00560.x","title":"Optimizing Design of Highway Horizontal Alignments: New Substantive Safety Approach","year":2008,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Traffic and Road Safety","field":"Engineering","cited_by":69,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Collision; Tangent; Geometric design; Computer science; Horizontal and vertical; Spiral (railway); Simulation; Engineering; Geometry; Mathematics; Mechanical engineering; Computer security","retraction":null,"screen_n_in":null,"score":{"opus":0.00774631198378084,"gpt":0.1608080931878187,"spread":0.1530617812040378,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008487258,0.0003917189,0.0004807886,0.0001544342,0.00009806972,0.00002037869,0.0002175613,0.0001730392,0.00001831225],"category_scores_gemma":[0.000006771905,0.00037132,0.0000883653,0.000266189,0.00005714422,0.000248667,0.00007909668,0.0003105347,0.00000168076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008009616,"about_ca_system_score_gemma":0.00003608181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004800436,"about_ca_topic_score_gemma":4.02904e-7,"domain_scores_codex":[0.9986212,0.00001900536,0.0004334946,0.0003096463,0.0002091915,0.0004074544],"domain_scores_gemma":[0.9994,0.0000709942,0.00005666607,0.0002353111,0.00003111294,0.0002059366],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002044627,0.00001110653,0.000114434,0.0001010192,0.0001353395,0.00001351922,0.001479082,0.9883252,0.003104477,0.0006057429,0.001151012,0.004938668],"study_design_scores_gemma":[0.001159477,0.0001231858,0.01712878,0.0001186375,0.00003439364,0.0002048038,0.00005897539,0.9761299,0.002676078,0.00003839695,0.001758283,0.0005690448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05230445,0.001165931,0.9446715,0.00000459701,0.0005997192,0.0002048247,0.00001308255,0.0004866785,0.0005491805],"genre_scores_gemma":[0.8038158,0.0004413149,0.1953335,0.000009886845,0.0003098192,0.000003939047,0.0000171447,0.00005560122,0.00001302958],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7515114,"threshold_uncertainty_score":0.9998739,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2019872178","doi":"10.1111/j.1467-8667.2004.00336.x","title":"Intelligent System for Condition Monitoring of Underground Pipelines","year":2003,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":69,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"Tokyo Metropolitan Government","keywords":"Pipeline (software); Pipeline transport; Process (computing); Data acquisition; Computer science; Identification (biology); Quality (philosophy); Focus (optics); Engineering; Risk analysis (engineering); Construction engineering; Systems engineering; Environmental engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.008859076996091892,"gpt":0.2239893807549617,"spread":0.2151303037588698,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007447263,0.0001719878,0.0002336831,0.0000568062,0.00004345546,0.00002929558,0.00007584268,0.00006974718,0.000002255027],"category_scores_gemma":[0.00001731229,0.0001684653,0.00005869245,0.0001344176,0.00001567784,0.00007812186,0.00001551078,0.0001036072,6.174548e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003700842,"about_ca_system_score_gemma":0.000006012642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001153566,"about_ca_topic_score_gemma":1.985325e-7,"domain_scores_codex":[0.9993308,0.000009351165,0.0002569903,0.0001530066,0.0000689541,0.0001808951],"domain_scores_gemma":[0.9995639,0.0001328001,0.00003660433,0.0001426152,0.0000504547,0.00007360949],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003455895,0.00001559032,0.0004283988,0.001849389,0.0001140143,9.053793e-7,0.0001902159,0.8152117,0.08088,0.07159515,0.0001809539,0.02953026],"study_design_scores_gemma":[0.0008583578,0.0001495675,0.02328425,0.0006435694,0.00009730813,0.00005007636,0.0003901907,0.8320385,0.1240087,0.00967771,0.008008208,0.0007935151],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2285682,0.0002687465,0.770108,0.000003761241,0.0006348234,0.0001472049,0.000009154443,0.0001599578,0.0001000782],"genre_scores_gemma":[0.8872572,0.00003362167,0.112354,0.000002388227,0.0002825233,0.00003535159,0.000005336773,0.00002609467,0.000003465201],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.658689,"threshold_uncertainty_score":0.6869814,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1604928349","doi":"10.1111/mice.12064","title":"Models for Seismic Vulnerability Analysis of Power Networks: Comparative Assessment","year":2014,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":68,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"European Commission","keywords":"Component (thermodynamics); Vulnerability (computing); Vulnerability assessment; Computer science; Electric power system; Prioritization; Identification (biology); Reliability engineering; Rank (graph theory); Power (physics); Engineering; Mathematics; Computer security","retraction":null,"screen_n_in":null,"score":{"opus":0.006813544686530976,"gpt":0.2281231679512383,"spread":0.2213096232647073,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000391818,0.0004062383,0.001031336,0.0004458212,0.0001044059,0.00006822124,0.0002590805,0.0001833073,0.00003604811],"category_scores_gemma":[0.00002022183,0.0003764404,0.000327089,0.0008911144,0.0000855524,0.0002983555,0.00007194961,0.0003502946,1.970887e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008944122,"about_ca_system_score_gemma":0.00001725314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007982168,"about_ca_topic_score_gemma":0.00001266893,"domain_scores_codex":[0.9982449,0.00005305203,0.0006195221,0.0004398997,0.0002110493,0.0004315723],"domain_scores_gemma":[0.9987622,0.0003754651,0.0001000039,0.0004623092,0.0001435428,0.0001564286],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006867926,0.00001093949,0.001004058,0.0001349648,0.0009546398,2.139986e-7,0.0002904337,0.9917184,0.000337401,0.00195056,0.0001559806,0.003435534],"study_design_scores_gemma":[0.0003046761,0.00009151424,0.04461837,0.00003018886,0.0004660411,0.000002228771,0.0000301821,0.9521223,0.0001559068,0.001466129,0.0003623685,0.0003501338],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2156007,0.0001441727,0.7833524,0.00000901338,0.0002660117,0.0001900614,0.00002782226,0.0001500467,0.0002597305],"genre_scores_gemma":[0.9716067,0.00002544918,0.02805003,0.00004458043,0.0001576903,0.00002914213,0.00005619743,0.00002793878,0.00000230153],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7560059,"threshold_uncertainty_score":0.9998688,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2043491709","doi":"10.1111/j.1467-8667.2006.00449.x","title":"Damage Detection in a Girder Bridge by Artificial Neural Network Technique","year":2006,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":68,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"","keywords":"Bridge (graph theory); Artificial neural network; Vibration; Modal; Structural engineering; Computer science; Girder; Finite element method; Stiffness; Identification (biology); Algorithm; Mode (computer interface); Engineering; Artificial intelligence; Acoustics","retraction":null,"screen_n_in":null,"score":{"opus":0.004505932567830929,"gpt":0.1993788969977656,"spread":0.1948729644299347,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001215695,0.0003687967,0.0003246512,0.0002054916,0.00007698036,0.00008432895,0.0001720006,0.0002459381,0.000007401342],"category_scores_gemma":[0.000008031262,0.0003971593,0.00004778998,0.0004293416,0.00002939639,0.0002315537,0.00007625202,0.0006065078,8.866435e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001581323,"about_ca_system_score_gemma":0.000007782879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001002269,"about_ca_topic_score_gemma":0.0000505671,"domain_scores_codex":[0.9984892,0.00002294318,0.00044912,0.0003186235,0.0001428081,0.0005773241],"domain_scores_gemma":[0.9995458,0.00005699315,0.00004449223,0.0002288995,0.0000247203,0.00009906593],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001063064,0.000006160089,0.001481725,0.0002375062,0.0000121673,0.00001934657,0.00006000019,0.8910055,0.02739155,0.0002100929,0.002888144,0.07667715],"study_design_scores_gemma":[0.0002286697,0.00006264666,0.2608809,0.0001238749,0.00000684858,0.00007333819,0.000001729026,0.7195867,0.01425009,0.001793553,0.002506365,0.000485232],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7711012,0.000371722,0.2257706,0.00001257556,0.001019845,0.0003235204,0.000007567939,0.001312326,0.00008059695],"genre_scores_gemma":[0.986014,0.00002557806,0.01238598,0.00002467595,0.001387849,0.00006791196,0.00001711986,0.00007411034,0.000002776028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2593992,"threshold_uncertainty_score":0.999848,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2079629977","doi":"10.1111/1467-8667.00302","title":"Computer Vision Techniques for Automatic Structural Assessment of Underground Pipes","year":2003,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":67,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"Tokyo Metropolitan Government","keywords":"Pipeline (software); Preprocessor; Automated X-ray inspection; Image processing; Pipeline transport; Computer science; Machine vision; Asset (computer security); Engineering; Artificial intelligence; Computer vision; Engineering drawing; Image (mathematics); Mechanical engineering; Computer security","retraction":null,"screen_n_in":null,"score":{"opus":0.003552501207301702,"gpt":0.2228507405451715,"spread":0.2192982393378698,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001575527,0.000434033,0.0005190428,0.0002317831,0.0001009678,0.0001017088,0.0001950844,0.000183625,0.00001481867],"category_scores_gemma":[0.00001544928,0.0003944848,0.000119382,0.0001924025,0.00005146653,0.0003069703,0.00006422387,0.0003046828,2.098121e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001175979,"about_ca_system_score_gemma":0.00002994225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002348216,"about_ca_topic_score_gemma":0.000001886398,"domain_scores_codex":[0.9984904,0.00002016622,0.0005082381,0.0003187207,0.0001935447,0.0004689375],"domain_scores_gemma":[0.999281,0.0001298564,0.00009164428,0.0002854526,0.00009219284,0.0001198645],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008991302,0.00001641293,0.001927726,0.002597001,0.0003361215,0.00001192711,0.0005001659,0.7686116,0.03263046,0.02641098,0.002149435,0.1647992],"study_design_scores_gemma":[0.0005577215,0.000259847,0.02897227,0.0003424792,0.00003987091,0.00009996731,0.00002862267,0.9559973,0.007447849,0.002415151,0.003310311,0.0005286077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2476892,0.0001823963,0.749576,0.000006615419,0.001510572,0.000316584,0.00001088862,0.000441338,0.0002663753],"genre_scores_gemma":[0.711361,0.00002687614,0.2880934,0.0000216675,0.0004081807,0.00002179756,0.00001054103,0.0000530312,0.000003529694],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4636718,"threshold_uncertainty_score":0.9998507,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1581132942","doi":"10.1111/j.1467-8667.2012.00773.x","title":"A Survival Analysis Model for Sewer Pipe Structural Deterioration","year":2012,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Water Systems and Optimization","field":"Engineering","cited_by":64,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Weibull distribution; Calibration; Convolution (computer science); Exponential function; Survival function; Sample (material); Statistics; Exponential distribution; Function (biology); Survival analysis; Engineering; Mathematics; Computer science; Artificial intelligence; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.006721659024082559,"gpt":0.1860306148772211,"spread":0.1793089558531385,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001013701,0.0002613894,0.0003240333,0.0002136506,0.00007048566,0.0001037475,0.00009260911,0.0001229334,0.000008130086],"category_scores_gemma":[0.000006917562,0.0002426524,0.00010045,0.0002691167,0.000009886137,0.0004737054,0.00003630331,0.0001111379,6.721586e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005020472,"about_ca_system_score_gemma":0.000005662565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002458542,"about_ca_topic_score_gemma":0.00002558214,"domain_scores_codex":[0.9990481,0.000008865939,0.000282324,0.0001806678,0.0001111101,0.0003689922],"domain_scores_gemma":[0.9995724,0.00002729858,0.00003809875,0.0001719066,0.00004933964,0.0001409308],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002686467,0.000001475124,0.001757975,0.00008821628,0.0001442398,1.916068e-7,0.0007016313,0.9947489,0.0009801239,0.0002581087,0.0002161183,0.001100362],"study_design_scores_gemma":[0.0002465081,0.00001515399,0.02724575,0.00001486422,0.0001124223,0.000006291606,0.0000073686,0.9713495,0.0002099168,0.00005849674,0.0004516223,0.0002821388],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2004653,0.0002518899,0.7978919,0.000004187333,0.0009348588,0.0001464386,0.00001932814,0.0002367432,0.00004932759],"genre_scores_gemma":[0.9629951,0.00001065682,0.03613956,0.00001401594,0.0006792256,0.00002179006,0.0000721677,0.00004210795,0.0000253732],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7625298,"threshold_uncertainty_score":0.9895077,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1501712065","doi":"10.1111/j.1467-8667.2012.00772.x","title":"Numerical Modeling of Dynamic Behavior of Annular Tuned Liquid Dampers for Applications in Wind Towers","year":2012,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Vibration Control and Rheological Fluids","field":"Engineering","cited_by":63,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Slosh dynamics; Structural engineering; Finite element method; Damping ratio; Mechanics; Damper; Vibration; Added mass; Parametric statistics; Thermoluminescent dosimeter; Materials science; Physics; Acoustics; Engineering; Radiation; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.004648606933293503,"gpt":0.1983123919775596,"spread":0.1936637850442661,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009167342,0.0001751559,0.0003206472,0.0001349327,0.00002443314,0.000008049423,0.0001109848,0.00012332,0.00001063834],"category_scores_gemma":[0.00001435958,0.0001594099,0.00007027308,0.0001749121,0.00002256214,0.0001676706,0.0000319383,0.0001349988,1.510008e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002831249,"about_ca_system_score_gemma":0.00000774107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002561852,"about_ca_topic_score_gemma":4.331671e-7,"domain_scores_codex":[0.9991376,0.000007514935,0.0003628686,0.0001344698,0.00008165015,0.0002758401],"domain_scores_gemma":[0.9996411,0.00006396277,0.0000302952,0.0001334294,0.00003717319,0.00009406437],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001122922,0.00001978335,0.0007180877,0.0001531706,0.00002448983,1.930861e-7,0.000239441,0.9643449,0.03083346,0.0007883731,0.000006900568,0.002859959],"study_design_scores_gemma":[0.0003795836,0.00008031513,0.007615052,0.00003713674,0.0000205056,0.000003701805,0.00002470784,0.9904883,0.001005028,0.00004733968,0.0001336144,0.0001647007],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3854026,0.0007700176,0.6133953,0.000005069141,0.0001410288,0.0002009881,0.0000117831,0.0000543907,0.00001887493],"genre_scores_gemma":[0.985444,0.0000435381,0.0143271,0.000008444829,0.00008959475,0.00004154549,0.00002256146,0.00002226053,9.220731e-7],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6000415,"threshold_uncertainty_score":0.6500546,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2755953131","doi":"10.1111/mice.12306","title":"Automated Model‐Based Finding of 3D Objects in Cluttered Construction Point Cloud Models","year":2017,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":60,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Point cloud; Computer science; Process (computing); Computer vision; Artificial intelligence; Identification (biology); Matching (statistics); Point (geometry); Object (grammar); Key (lock); Isolation (microbiology); Feature (linguistics); Measure (data warehouse); Task (project management); Data mining; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01322039835155316,"gpt":0.2018988000087383,"spread":0.1886784016571852,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001807794,0.000211219,0.0003051931,0.0001182178,0.0001720674,0.0001240692,0.0002303021,0.0001208693,0.00003744914],"category_scores_gemma":[0.00002846688,0.0001832771,0.00004459739,0.00009050655,0.00007045549,0.000461323,0.00003387623,0.0002153371,0.000001192489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001002754,"about_ca_system_score_gemma":0.00003247497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001880011,"about_ca_topic_score_gemma":0.0002376451,"domain_scores_codex":[0.9989712,0.00002891139,0.0002947432,0.0002700076,0.0001461973,0.0002888926],"domain_scores_gemma":[0.9994125,0.00005492074,0.0001422304,0.0002596889,0.00003354578,0.00009714373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001386222,0.000003063358,0.02269781,0.00008595925,0.00001102362,0.000007556678,0.0002935728,0.9640226,0.0003617783,0.00006378727,0.00004273478,0.01239628],"study_design_scores_gemma":[0.0004021044,0.00003873196,0.1957445,0.0001482695,0.000005138975,0.0000169437,0.00001912756,0.8028091,0.0001704025,0.0004685028,0.000005924804,0.0001712953],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9290721,0.000125737,0.06930827,0.00002204977,0.0005850542,0.0001083441,0.00003837255,0.0001647702,0.0005752787],"genre_scores_gemma":[0.9665169,0.00001521506,0.03329297,0.00003097302,0.00009838269,8.020441e-7,0.00003393085,0.000006785888,0.000004042254],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1730467,"threshold_uncertainty_score":0.7473825,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2102586410","doi":"10.1111/0885-9507.00200","title":"Traffic Volume Time‐Series Analysis According to the Type of Road Use","year":2000,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":58,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Regina; Saint Mary's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Transport engineering; Traffic volume; Computer science; Trip distribution; Time series; Volume (thermodynamics); Floating car data; Traffic congestion; Term (time); Advanced Traffic Management System; TRIPS architecture; Intelligent transportation system; Traffic analysis; Plan (archaeology); Operations research; Engineering; Geography; Machine learning; Computer network","retraction":null,"screen_n_in":null,"score":{"opus":0.003955246215684002,"gpt":0.1753286373948867,"spread":0.1713733911792027,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007739002,0.0002049082,0.0002765737,0.0002592054,0.00005150793,0.00008845117,0.0002010533,0.00006846577,0.0001046927],"category_scores_gemma":[0.000009106199,0.0001720074,0.0000811546,0.0007721329,0.0000201265,0.000325207,0.00005187823,0.0001527321,0.000009568068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002376735,"about_ca_system_score_gemma":0.00000422907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004982262,"about_ca_topic_score_gemma":0.000004504217,"domain_scores_codex":[0.9992243,0.00001095644,0.0002478301,0.0001828103,0.0001191807,0.0002148876],"domain_scores_gemma":[0.9995811,0.00002214422,0.00002087281,0.0002651867,0.00002779103,0.00008293287],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005465546,0.000003020487,0.0002099828,0.0000311379,0.0002230975,0.000001489693,0.000193206,0.9177517,0.0004387504,0.00005551241,0.006814744,0.07427194],"study_design_scores_gemma":[0.00008688062,0.00005490227,0.04868474,0.00003180101,0.0001110697,0.000007177565,0.00001325871,0.918096,0.0001124596,0.000004016907,0.0326081,0.0001896087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.693283,0.0001639621,0.3035927,0.0000484124,0.0003189212,0.0001813068,0.00001263304,0.002097746,0.0003013782],"genre_scores_gemma":[0.9907587,0.0001471686,0.008753827,0.00005057209,0.0001425779,0.000007628214,0.00001274676,0.00002659038,0.0001002383],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2974757,"threshold_uncertainty_score":0.7014259,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2039267090","doi":"10.1111/j.1467-8667.2005.00417.x","title":"Fuzzy Expert System to Assess Corrosion of Cast/Ductile Iron Pipes from Backfill Properties","year":2005,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Water Systems and Optimization","field":"Engineering","cited_by":57,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"National Research Council Canada","funders":"","keywords":"Knowledge base; Fuzzy logic; Expert system; Computer science; Context (archaeology); Mains electricity; Data mining; Inference; Inference engine; Process (computing); Artificial intelligence; Engineering; Geology; Programming language","retraction":null,"screen_n_in":null,"score":{"opus":0.008181363677682265,"gpt":0.1708736520550188,"spread":0.1626922883773365,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00005715649,0.0002984822,0.0003825745,0.0001484452,0.00004789605,0.00008146288,0.0001637991,0.0001288637,0.00001125745],"category_scores_gemma":[0.000006300611,0.0002600776,0.00004806526,0.0001503214,0.00001327632,0.0003016124,0.0000887651,0.0001395329,0.000005186098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009774369,"about_ca_system_score_gemma":0.000007330969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000440314,"about_ca_topic_score_gemma":0.00003993812,"domain_scores_codex":[0.9988888,0.00001533153,0.0003987287,0.0002658741,0.0001666225,0.0002646561],"domain_scores_gemma":[0.9994841,0.00002188345,0.00004746021,0.0002501011,0.00005950483,0.000136965],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005412125,0.000004661022,0.0000902399,0.0003158085,0.00001704613,0.000002040751,0.001240991,0.9486374,0.04420479,0.00007377075,0.002711036,0.002696831],"study_design_scores_gemma":[0.0003375242,0.00006141699,0.003474168,0.0007263041,0.00001468192,0.00002949833,0.0001240239,0.9611557,0.02797575,0.000003881057,0.005693062,0.0004040053],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5469093,0.001182203,0.4490366,0.00002430258,0.00164892,0.0002677198,0.00002551649,0.000480314,0.0004250859],"genre_scores_gemma":[0.9783546,0.00003259374,0.02052078,0.00001982862,0.0009497968,0.00001893571,0.0000183459,0.0000556977,0.00002943161],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4314452,"threshold_uncertainty_score":0.9999852,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1950380357","doi":"10.1111/mice.12023","title":"Activity‐Based Travel Scenario Analysis with Routing Problem Reoptimization","year":2013,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":55,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Heuristics; Mathematical optimization; Computer science; Genetic algorithm; Heuristic; Metaheuristic; Routing (electronic design automation); Schedule; Vehicle routing problem; Mathematics; Computer network","retraction":null,"screen_n_in":null,"score":{"opus":0.004225081752610376,"gpt":0.192273534673386,"spread":0.1880484529207757,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001243478,0.0001575446,0.0002035416,0.0002267681,0.0002651021,0.0002101033,0.00009210587,0.00009923003,0.00007419804],"category_scores_gemma":[0.00001344079,0.0001420928,0.00004400087,0.0007841145,0.00004339578,0.0004256333,0.000007815668,0.0001518586,0.000001112599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004334274,"about_ca_system_score_gemma":0.00006033096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004023475,"about_ca_topic_score_gemma":0.000196587,"domain_scores_codex":[0.9990916,0.00003315569,0.0001670414,0.0002503523,0.0002073563,0.0002504558],"domain_scores_gemma":[0.9995043,0.00006435525,0.00009300146,0.0001024992,0.0001122659,0.0001235815],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004227396,0.000007120567,0.01247343,0.00001940109,0.00006926241,0.000001108684,0.002211401,0.9809057,0.00008958573,0.000646416,0.00004833827,0.003524021],"study_design_scores_gemma":[0.0002367891,0.00003075175,0.2339665,0.00004227472,0.00007883117,6.908033e-7,0.00009419869,0.7651695,0.00004335641,0.00002686358,0.0001366513,0.0001735588],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.140161,0.00001361456,0.858658,0.0001542799,0.00006691415,0.0001780798,0.000002507338,0.0001664078,0.0005992419],"genre_scores_gemma":[0.8956475,0.000008027104,0.1040821,0.00005437712,0.0001062699,0.00001202864,0.00003715521,0.00001354682,0.00003891827],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7554865,"threshold_uncertainty_score":0.5794376,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2090853541","doi":"10.1111/0885-9507.00196","title":"A Multiobjective and Stochastic System for Building Maintenance Management","year":2000,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"BIM and Construction Integration","field":"Engineering","cited_by":55,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"National Research Council Canada","funders":"","keywords":"Maximization; Multi-objective optimization; Computer science; Stochastic programming; Minification; Prioritization; Stochastic optimization; Mathematical optimization; Reliability engineering; Preventive maintenance; Risk analysis (engineering); Decision support system; Operations research; Engineering; Management science; Business; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.00219760042188058,"gpt":0.1623528721163744,"spread":0.1601552716944939,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004722627,0.0002177443,0.0001935851,0.0001110552,0.00008411197,0.00007888256,0.00006613985,0.00007769175,0.00001223823],"category_scores_gemma":[0.000002746727,0.000211116,0.00003690117,0.0001071375,0.00002374004,0.0001537044,0.00002008633,0.0001313378,0.000001089576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000716927,"about_ca_system_score_gemma":0.000003248278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001851097,"about_ca_topic_score_gemma":0.000001222466,"domain_scores_codex":[0.9992621,0.000004917586,0.0001961444,0.0002313858,0.0000692074,0.0002362524],"domain_scores_gemma":[0.9997299,0.00003542339,0.0000191031,0.0001081203,0.00002737443,0.00008012799],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001222754,0.000002040264,0.00001596416,0.0005036763,0.00008881515,0.000002734153,0.000216684,0.7185652,0.0007224658,0.01209435,0.0002962029,0.2674797],"study_design_scores_gemma":[0.0006297918,0.00003415484,0.003534963,0.0002782124,0.00002852682,0.0001346173,0.00007095189,0.9916022,0.0001727875,0.0003548574,0.002905603,0.0002532781],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1220016,0.0002960566,0.8759352,0.000007037188,0.0005771463,0.0002688602,0.00001191291,0.0004096834,0.0004925122],"genre_scores_gemma":[0.9623078,0.00004351136,0.03726637,0.00001490527,0.0002390504,0.00006340452,0.000004497149,0.00003072359,0.0000297661],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8403062,"threshold_uncertainty_score":0.8609059,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2153199019","doi":"10.1111/j.1467-8667.2008.00564.x","title":"Using Evolutionary Optimization Techniques for Scheduling Water Pipe Renewal Considering a Short Planning Horizon","year":2008,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Water Systems and Optimization","field":"Engineering","cited_by":54,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Institut National de la Recherche Scientifique; Université Laval; National Research Council Canada","funders":"","keywords":"Sorting; Genetic algorithm; Mathematical optimization; Time horizon; Pareto principle; Computer science; Multi-objective optimization; Scheduling (production processes); Function (biology); Operations research; Engineering; Algorithm; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.01481917220449015,"gpt":0.2038371078022508,"spread":0.1890179355977607,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009295542,0.0003365391,0.0003331237,0.0002554338,0.0002275619,0.00007631377,0.0001058322,0.000194319,0.000006038663],"category_scores_gemma":[0.0000107207,0.0003134882,0.00006768134,0.0001310388,0.0000284017,0.0004145232,0.00007359058,0.0001903179,2.761324e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001075315,"about_ca_system_score_gemma":0.00001656382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005279652,"about_ca_topic_score_gemma":0.000001626645,"domain_scores_codex":[0.9987291,0.00001128645,0.0004033372,0.0003072008,0.0001330381,0.000416046],"domain_scores_gemma":[0.9995776,0.00003366846,0.00002997464,0.0001693798,0.00008069795,0.0001087241],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005864842,0.00000296797,0.0004146284,0.0001928821,0.00004375678,0.0000101148,0.0003814258,0.9892628,0.009132824,0.00003340282,0.0001733867,0.0003459905],"study_design_scores_gemma":[0.0002260363,0.00006164073,0.0002585968,0.0002428321,0.00002036203,0.0003096001,0.00001428955,0.9856153,0.01207224,0.00004796876,0.0007303658,0.0004008459],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1295732,0.0004399428,0.8682138,0.000005506595,0.0006765451,0.0002832967,0.000008044261,0.0007088444,0.00009080804],"genre_scores_gemma":[0.6304934,0.00003592345,0.368739,0.000008775412,0.0005840822,0.00002222289,0.0000521579,0.00006047594,0.000003949977],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5009203,"threshold_uncertainty_score":0.9999317,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2112752718","doi":"10.1111/j.1467-8667.2010.00673.x","title":"A Fuzzy Expert System for Prioritizing Rehabilitation of Sewer Networks","year":2010,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Water Systems and Optimization","field":"Engineering","cited_by":53,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Fuzzy logic; Ranking (information retrieval); Fuzzy inference system; Adaptive neuro fuzzy inference system; Sanitary sewer; Computer science; Index (typography); Expert system; Reliability engineering; Engineering; Fuzzy control system; Civil engineering; Data mining; Artificial intelligence; Environmental engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.002102090380668168,"gpt":0.1635908288130764,"spread":0.1614887384324083,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001215237,0.0001958189,0.00027263,0.0001168475,0.00004388073,0.00005045395,0.00009329992,0.0001573948,0.000001482851],"category_scores_gemma":[0.00001491644,0.0001892153,0.00006110675,0.0001215714,0.00001644428,0.0001783715,0.00002992126,0.000173404,1.933917e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002923788,"about_ca_system_score_gemma":0.000006068698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000471497,"about_ca_topic_score_gemma":0.00001775283,"domain_scores_codex":[0.9991771,0.000007084711,0.0003380167,0.0001803826,0.00008184141,0.0002155978],"domain_scores_gemma":[0.9995193,0.00009788987,0.00004652444,0.00018313,0.00007874354,0.00007434599],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003983006,0.000002639358,0.0001906669,0.0007176241,0.00003069322,6.499844e-7,0.0006393311,0.9833137,0.009593048,0.001734903,0.0007562583,0.003016522],"study_design_scores_gemma":[0.000363775,0.00005703064,0.004255707,0.0002067156,0.000009499536,0.00002110509,0.00004280401,0.9920904,0.0005907587,0.00004655077,0.002109745,0.0002058884],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1474072,0.0002637776,0.8489063,0.000006817855,0.002621485,0.0002847856,0.000006426651,0.0003235643,0.0001796335],"genre_scores_gemma":[0.9297658,0.000008253588,0.06935888,0.00000531759,0.0007693833,0.00003278697,0.00001289127,0.00004271085,0.000004008941],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7823586,"threshold_uncertainty_score":0.7715976,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2971587063","doi":"10.1111/mice.12493","title":"Automated building image extraction from 360° panoramas for postdisaster evaluation","year":2019,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":51,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"National Science Foundation","keywords":"Panorama; Viewpoints; Convolutional neural network; Image (mathematics); Projection (relational algebra); Feature extraction; Visualization","retraction":null,"screen_n_in":null,"score":{"opus":0.006937494437350255,"gpt":0.2176236485401114,"spread":0.2106861541027611,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002195867,0.000197533,0.0001991637,0.00006076377,0.00009144582,0.0001849723,0.0001071975,0.0001035714,0.0005354977],"category_scores_gemma":[0.0000278368,0.0001645338,0.00005319628,0.0001093854,0.00001317845,0.00047527,0.00001465557,0.0001449152,0.00002260494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001197347,"about_ca_system_score_gemma":0.00001611649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009703377,"about_ca_topic_score_gemma":0.00005268977,"domain_scores_codex":[0.9989986,0.00003712433,0.0002053589,0.000319283,0.0001835129,0.0002560763],"domain_scores_gemma":[0.9994721,0.0001614054,0.00006532398,0.0001401458,0.00006937534,0.00009163435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008531358,0.00001225618,0.09453326,0.0002302301,0.0001339124,0.000005764552,0.0009846733,0.5812415,0.06166231,0.00007729056,0.001692103,0.2593414],"study_design_scores_gemma":[0.0003031027,0.00005543028,0.3921394,0.00004248364,0.00001358202,0.000008610261,0.00002477029,0.6059893,0.0002306628,0.0001520549,0.0008918613,0.000148741],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9558438,0.0003781823,0.04164995,0.00002445341,0.001247719,0.0003047551,0.00007186239,0.0002894751,0.0001897758],"genre_scores_gemma":[0.9698967,0.000007843774,0.02933239,0.00005646522,0.0003316104,0.000002795925,0.0003442184,0.000009034516,0.0000188795],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2976061,"threshold_uncertainty_score":0.6709495,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2044130816","doi":"10.1111/j.1467-8667.2006.00456.x","title":"Mobile Model-Based Bridge Lifecycle Management System","year":2006,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"BIM and Construction Integration","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"Concordia University","keywords":"Bridge (graph theory); Computer science; Application lifecycle management; System lifecycle; Java; Systems engineering; Software engineering; Database; Embedded system; Operating system; Engineering; Software","retraction":null,"screen_n_in":null,"score":{"opus":0.002496510739770054,"gpt":0.1568324346184235,"spread":0.1543359238786535,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00004494577,0.0002705484,0.0002124936,0.0001749485,0.00007095026,0.00009856437,0.0001176052,0.0001103364,0.00001024509],"category_scores_gemma":[6.390516e-7,0.0002742138,0.00006377552,0.0001752243,0.00002123832,0.0001512043,0.00003297174,0.0001820691,0.000005461394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009887602,"about_ca_system_score_gemma":0.000007896564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005054619,"about_ca_topic_score_gemma":0.000002370079,"domain_scores_codex":[0.9990695,0.00000682379,0.0002818864,0.0002366065,0.0001363935,0.0002687841],"domain_scores_gemma":[0.9996358,0.00001267462,0.00002904057,0.0002106204,0.00002981229,0.00008210933],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001970908,0.000003825252,0.00009393301,0.0003385143,0.00002476663,0.000005330467,0.00002565006,0.9707993,0.0006028225,0.007703924,0.001446678,0.01895327],"study_design_scores_gemma":[0.0003590921,0.00002370066,0.00585668,0.0001158394,0.0000211487,0.00003476867,0.000009537349,0.9879662,0.0005757972,0.0002131834,0.004542718,0.0002812963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1007826,0.00046729,0.8942495,0.000003318261,0.0007957264,0.0001775145,0.00001150655,0.0009755556,0.002536987],"genre_scores_gemma":[0.9708355,0.00001686015,0.02859142,0.00002179009,0.0003854586,0.00005307833,0.0000248422,0.00004322797,0.00002778369],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8700529,"threshold_uncertainty_score":0.999971,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3133071534","doi":"10.1111/mice.12643","title":"Octree‐based point cloud simulation to assess the readiness of highway infrastructure for autonomous vehicles","year":2021,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":48,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Software deployment; Sight; Point cloud; Octree; Cloud computing; Automotive industry; Field (mathematics); Point (geometry); Software engineering; Artificial intelligence; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.009398191891529094,"gpt":0.2221023372911779,"spread":0.2127041453996488,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001233472,0.0001931749,0.0002204091,0.00004455456,0.0001327481,0.00006644105,0.0001817795,0.0000910554,0.00003839925],"category_scores_gemma":[0.00005855692,0.0001528968,0.00006736416,0.0003127073,0.00005323415,0.00008817663,0.000136003,0.0001471058,0.000002132979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006974252,"about_ca_system_score_gemma":0.00002602447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001435655,"about_ca_topic_score_gemma":0.00001092895,"domain_scores_codex":[0.9989992,0.00002541782,0.0002677955,0.0003286702,0.0001568944,0.0002219928],"domain_scores_gemma":[0.9991559,0.0002582182,0.00008160368,0.000357314,0.00004600986,0.0001009657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006516738,0.000007355203,0.0005012521,0.00003324641,0.00001362063,0.000001041225,0.0002362698,0.9492014,0.02599467,0.0003344222,0.001063913,0.02260626],"study_design_scores_gemma":[0.0002633835,0.00004299237,0.1118225,0.00004207597,0.0000212271,0.00001359586,0.00002338592,0.8559492,0.01175891,0.0006562831,0.01921648,0.0001899944],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3963958,0.00002364112,0.602643,0.0002821693,0.0002588581,0.0001965546,0.00001391392,0.00005949665,0.0001266389],"genre_scores_gemma":[0.9380455,0.00000208158,0.06137807,0.0002655401,0.0002367486,0.000006112074,0.00002369921,0.00002202889,0.00002023409],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5416497,"threshold_uncertainty_score":0.6234952,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2587245259","doi":"10.1111/mice.12255","title":"The Stretching Method for Vibration‐Based Structural Health Monitoring of Civil Structures","year":2017,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Seismic Waves and Analysis","field":"Earth and Planetary Sciences","cited_by":48,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Horizon 2020 Framework Programme; Horizon 2020; Fondazione Cassa di Risparmio di Perugia","keywords":"Structural health monitoring; Waveform; Time domain; Frequency domain; Vibration; Seismic noise; Acoustics; Context (archaeology); Noise (video); Spectral density; Computer science; Structural engineering; Geology; Physics; Engineering; Seismology; Telecommunications; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.01015211361496179,"gpt":0.2482096817353809,"spread":0.2380575681204191,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002930391,0.0002299793,0.0003399077,0.00008550831,0.001011778,0.0003727799,0.0004435884,0.00005944206,0.00002720044],"category_scores_gemma":[0.00007202353,0.0001574236,0.0001192486,0.0000767153,0.00006309438,0.0003186089,0.00004081619,0.0001885904,1.795036e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000854773,"about_ca_system_score_gemma":0.0000542404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003717227,"about_ca_topic_score_gemma":0.000227519,"domain_scores_codex":[0.9987786,0.00003609037,0.0003546012,0.0002856322,0.0001930201,0.0003520692],"domain_scores_gemma":[0.99877,0.0003440253,0.000307284,0.0003904307,0.00005294277,0.0001353236],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001590564,0.000001153059,0.0294088,0.0001429849,0.00009688819,0.000001168104,0.0001886076,0.8287267,0.0001381254,0.0008822801,0.0001462054,0.1402512],"study_design_scores_gemma":[0.0002187475,0.00006122048,0.3443286,0.00004437638,0.00001476462,0.000005075467,0.0000458318,0.6519081,0.0001576007,0.002604956,0.0004878106,0.0001229413],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4402266,0.001287998,0.555634,0.0006214948,0.001688753,0.0002740597,0.0001425364,0.0000654496,0.00005910681],"genre_scores_gemma":[0.9012101,0.00005017809,0.09801739,0.00007216301,0.0006023225,0.000001182966,0.00003314851,0.000008591984,0.000004959154],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4609834,"threshold_uncertainty_score":0.7781885,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4292114702","doi":"10.1111/mice.12906","title":"3D vision-based out-of-plane displacement quantification for steel plate structures using structure-from-motion, deep learning, and point-cloud processing","year":2022,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Point cloud; Plane (geometry); Artificial intelligence; Computer science; Point (geometry); Displacement (psychology); Convolutional neural network; Computer vision; Structural engineering; Engineering; Geometry; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.005675686095312223,"gpt":0.2159379204830485,"spread":0.2102622343877363,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016708,0.0004958023,0.0005061302,0.0002852071,0.0004148976,0.0001416563,0.0002161384,0.000145313,0.00005367025],"category_scores_gemma":[0.00003200304,0.000500755,0.00007474505,0.0002183776,0.000062313,0.0002539885,0.0001467704,0.0005569088,1.436689e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001577142,"about_ca_system_score_gemma":0.00003347097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001082783,"about_ca_topic_score_gemma":0.00000569555,"domain_scores_codex":[0.9980579,0.00003762984,0.0005809256,0.0005205141,0.0003108731,0.0004921411],"domain_scores_gemma":[0.9991868,0.0001279258,0.0002088805,0.0002368162,0.0001019454,0.0001375988],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004330599,0.000006227966,0.0007318709,0.0005341052,0.00007338083,0.000003159038,0.000944711,0.923591,0.04938354,0.0001633594,0.0001182047,0.02440714],"study_design_scores_gemma":[0.0009868935,0.0001585672,0.006525248,0.0001437739,0.00007859074,0.00002773697,0.0001752227,0.9803394,0.005147836,0.0005674489,0.005308778,0.0005404969],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3699819,0.0008558831,0.6261042,0.0000117057,0.002380571,0.0003454416,0.00009943621,0.0002091851,0.00001169206],"genre_scores_gemma":[0.9351094,0.00002149193,0.06363674,0.0000241828,0.0008822056,0.0000255727,0.0001995431,0.00009636658,0.000004543311],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5651275,"threshold_uncertainty_score":0.9997444,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2944163882","doi":"10.1111/mice.12452","title":"Integrative modeling of performance deterioration and maintenance effectiveness for infrastructure assets with missing condition data","year":2019,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Asset management; Markov chain; Maintenance actions; Asset (computer security); Computer science; Reliability engineering; Process (computing); Engineering; Risk analysis (engineering); Operations research; Business","retraction":null,"screen_n_in":null,"score":{"opus":0.004855282284652409,"gpt":0.1969422351506527,"spread":0.1920869528660003,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001800424,0.0004038681,0.0004927061,0.0001654949,0.00008111394,0.00008991006,0.0002255997,0.0001552415,0.000003955531],"category_scores_gemma":[0.00002459231,0.0003255364,0.00003249266,0.0001682077,0.00004940628,0.0008101102,0.0001216401,0.0003194144,2.396882e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007471585,"about_ca_system_score_gemma":0.00003105886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002782404,"about_ca_topic_score_gemma":0.000002521614,"domain_scores_codex":[0.9987035,0.00001720776,0.0003328226,0.0004374543,0.0001479441,0.0003610324],"domain_scores_gemma":[0.9991912,0.0001151176,0.00008969267,0.0003759036,0.0001401511,0.00008798039],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007443254,0.000002765812,0.003559767,0.001701965,0.00009997787,0.000001679413,0.0003654954,0.9387326,0.03207584,0.0003512028,0.00004263771,0.02299169],"study_design_scores_gemma":[0.0009393046,0.0002133177,0.03607855,0.001233354,0.00003787289,0.00007039028,0.00005918224,0.9568094,0.003598695,0.0003090646,0.0002736368,0.0003772261],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5184935,0.0001444515,0.4805185,0.000003248821,0.0003933333,0.0002929955,0.00003209381,0.0000847289,0.00003706781],"genre_scores_gemma":[0.9598086,0.00008029159,0.0397044,0.00001127781,0.000216149,0.00001931284,0.00009892399,0.00005913726,0.000001923033],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.441315,"threshold_uncertainty_score":0.9999197,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2085393389","doi":"10.1111/j.1467-8667.2005.00403.x","title":"Piezoelectric-Based Degradation Assessment of a Pipe Using Fourier and Wavelet Analyses","year":2005,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Dalhousie University","funders":"","keywords":"Fast Fourier transform; Wavelet; Transformation (genetics); Vibration; Pipeline (software); Energy (signal processing); SIGNAL (programming language); Acoustics; Structural engineering; Fourier transform; Computer science; Engineering; Mechanical engineering; Algorithm; Physics; Mathematics; Statistics; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.01801173866376587,"gpt":0.2887819443020757,"spread":0.2707702056383098,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001078792,0.0002588251,0.0003205829,0.0003183906,0.00007028475,0.00004246156,0.0001041799,0.0001271476,0.000007796055],"category_scores_gemma":[0.0000141377,0.0002615412,0.00004993681,0.0002900472,0.00003143182,0.0002110474,0.00004034415,0.0002588788,6.943569e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001504242,"about_ca_system_score_gemma":0.00003660144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001787323,"about_ca_topic_score_gemma":0.00000318356,"domain_scores_codex":[0.9989483,0.00001958521,0.000343176,0.0002087554,0.0001798779,0.000300356],"domain_scores_gemma":[0.9994677,0.00008689469,0.00006603961,0.0001926701,0.00005718855,0.0001294564],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005345215,0.000007414588,0.001586278,0.0006012615,0.00009584003,0.000003388514,0.0002055122,0.6868788,0.02155808,0.0003799624,0.000128167,0.28855],"study_design_scores_gemma":[0.0002482514,0.0000520282,0.03897463,0.0001284533,0.00003317035,0.00001989076,0.000004382333,0.9521751,0.007296609,0.00007473387,0.0007584887,0.0002342542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5151649,0.0003748797,0.4839043,0.00001491856,0.0001609516,0.0001008782,0.000003060158,0.0002487329,0.00002734228],"genre_scores_gemma":[0.6882029,0.00008787366,0.3113762,0.00001832104,0.0002760239,0.000004693164,0.000005147674,0.00002785398,9.627378e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2883157,"threshold_uncertainty_score":0.9999837,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2479713702","doi":"10.1111/mice.12222","title":"Location Optimization of Road Weather Information System (RWIS) Network Considering the Needs of Winter Road Maintenance and the Traveling Public","year":2016,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":42,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Minnesota Department of Transportation","keywords":"Simulated annealing; Computer science; Kriging; Variance (accounting); Transport engineering; Geographic information system; Network planning and design; Operations research; Business; Geography; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.002977846365495702,"gpt":0.1441511894821204,"spread":0.1411733431166247,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003488897,0.0001351222,0.000189101,0.00004384226,0.00007935954,0.00005240455,0.0001240803,0.00005875624,0.00002239258],"category_scores_gemma":[0.00003967062,0.00007200593,0.00002924159,0.0002011818,0.0002077068,0.0005183007,0.0001323396,0.00006217392,0.000001111518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000523573,"about_ca_system_score_gemma":0.000007494702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003319647,"about_ca_topic_score_gemma":0.000004046114,"domain_scores_codex":[0.9991983,0.00004261943,0.0003724559,0.0000969284,0.0001292232,0.0001605318],"domain_scores_gemma":[0.9994783,0.00006803746,0.0002076782,0.0001775957,0.00003518114,0.00003323122],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003320625,0.000001539364,0.006561123,0.0001063851,0.00003497924,1.029853e-7,0.001460594,0.9554633,0.001481998,0.002439558,0.00005611494,0.03236109],"study_design_scores_gemma":[0.001146454,0.00004351347,0.1223861,0.0005096365,0.00002978581,0.000116204,0.0003584299,0.8741476,0.0006312751,0.0001643734,0.0002907997,0.0001758689],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4898558,0.00004261494,0.5094466,0.0000947619,0.0003250691,0.0001447619,0.000001473071,0.0000290894,0.00005976305],"genre_scores_gemma":[0.9950186,0.00002394756,0.004802068,0.00002855964,0.0001052625,0.00000881213,0.000001475801,0.000009325886,0.000001933912],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5051628,"threshold_uncertainty_score":0.2936317,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4376955563","doi":"10.1111/mice.13023","title":"Autonomous 3D vision‐based bolt loosening assessment using micro aerial vehicles","year":2023,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Drone; Point cloud; Computer vision; Process (computing); Artificial intelligence; Computer science; Point (geometry); Machine vision; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.005511737534093021,"gpt":0.2193132721563569,"spread":0.2138015346222639,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001850928,0.0005497973,0.0004972444,0.0004652089,0.0002178772,0.0002566817,0.000273847,0.0002395082,0.00002799782],"category_scores_gemma":[0.0000163707,0.0005552793,0.0001181603,0.000562715,0.00005242317,0.0003350613,0.0001905602,0.0005718563,0.000006868249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002199188,"about_ca_system_score_gemma":0.00006320571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008578193,"about_ca_topic_score_gemma":0.000001745864,"domain_scores_codex":[0.9979241,0.00002186606,0.0004879099,0.0004651055,0.000268578,0.0008323754],"domain_scores_gemma":[0.9992026,0.00009672157,0.00006966038,0.0003531328,0.00006297664,0.0002149022],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005326483,0.000003598843,0.0005622901,0.0001988211,0.00006009149,0.00004627158,0.0001740253,0.8700966,0.1127552,0.00009844181,0.0008331541,0.01516617],"study_design_scores_gemma":[0.0007258763,0.00005761672,0.03476279,0.0002711016,0.0000329314,0.00005768358,0.00002628092,0.9521712,0.005348573,0.0001162466,0.005820919,0.0006087605],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6900427,0.0001856533,0.3039615,0.0000192998,0.003917748,0.000194161,0.00001748308,0.001482362,0.0001790425],"genre_scores_gemma":[0.9007475,0.00003525115,0.09713206,0.00005944699,0.001838416,0.00001440574,0.00003596575,0.0001275322,0.000009369383],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2107048,"threshold_uncertainty_score":0.9996899,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1979697910","doi":"10.1111/j.1467-8667.2005.00380.x","title":"Prediction of Onset of Corrosion in Concrete Bridge Decks Using Neural Networks and Case-Based Reasoning","year":2005,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Concrete Corrosion and Durability","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Acadia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bridge (graph theory); Artificial neural network; Probabilistic logic; Corrosion; Reliability (semiconductor); Computer science; Monte Carlo method; Field (mathematics); Artificial intelligence; Mathematics; Materials science; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.009220284858667702,"gpt":0.1924560578667446,"spread":0.1832357730080769,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001521939,0.0002212391,0.0003584494,0.0001715535,0.00003384028,0.00002201138,0.00006554708,0.0001385376,0.00001025565],"category_scores_gemma":[0.00003001634,0.0002314988,0.00004715896,0.00021314,0.00005229958,0.0001638298,0.00005975499,0.0002706072,4.328842e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005423653,"about_ca_system_score_gemma":0.00001245984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002639783,"about_ca_topic_score_gemma":0.00001643748,"domain_scores_codex":[0.9989896,0.00002538929,0.0004510027,0.0002117442,0.00009821507,0.0002240285],"domain_scores_gemma":[0.9994944,0.0001147856,0.00006881051,0.0001770407,0.00004135633,0.0001035521],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001703683,0.000001528579,0.01359881,0.0001881924,0.000005145697,0.00001788918,0.0001655023,0.967481,0.01240668,0.00001435091,0.00003417834,0.006069717],"study_design_scores_gemma":[0.0006354565,0.00004608789,0.06791686,0.0002338762,0.00001576293,0.0003775922,0.00001069944,0.9290913,0.001473845,0.000003097217,0.00004110858,0.0001543157],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7422571,0.0005790255,0.256687,0.000003229505,0.0002585635,0.000105416,0.00002053548,0.0000821151,0.000006966799],"genre_scores_gemma":[0.9919738,0.00003609987,0.00782614,0.00001688721,0.0001077305,0.000002488783,0.00001149258,0.0000251202,2.804464e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2497166,"threshold_uncertainty_score":0.9440246,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4220978993","doi":"10.1111/mice.12839","title":"Mountain railway alignment optimization integrating layouts of large-scale auxiliary construction projects","year":2022,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Geotechnical Engineering and Analysis","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Particle swarm optimization; Computer science; Dijkstra's algorithm; Process (computing); Scale (ratio); Function (biology); Mathematical optimization; Algorithm; Shortest path problem; Theoretical computer science; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.002512704043456887,"gpt":0.1673542674266326,"spread":0.1648415633831757,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001586501,0.0002827578,0.0003661035,0.0002771459,0.0001226743,0.00003664293,0.0001748109,0.00009028773,0.00007267505],"category_scores_gemma":[0.00001779714,0.0002973503,0.00009378994,0.0004935488,0.0000252626,0.000141081,0.0001758039,0.0004351907,3.900867e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001199456,"about_ca_system_score_gemma":0.00001645576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007052348,"about_ca_topic_score_gemma":0.000001296276,"domain_scores_codex":[0.9987108,0.00002497329,0.0004158857,0.0002748778,0.0002479635,0.0003255249],"domain_scores_gemma":[0.9995277,0.00004456451,0.00006831445,0.0002248596,0.00003777144,0.00009678156],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003038845,0.00001351691,0.0001364557,0.0001594993,0.00006773231,0.000003097571,0.0004949038,0.991965,0.003697317,0.0003959154,0.0001521749,0.002911367],"study_design_scores_gemma":[0.000407142,0.0000688699,0.0005296457,0.0000629069,0.00003513266,0.00005190825,0.000359966,0.9961596,0.0008822286,0.00004986848,0.001106178,0.0002865706],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1063869,0.0003773987,0.891901,0.00001902621,0.0005147723,0.0001533424,0.00003593978,0.000492955,0.0001186678],"genre_scores_gemma":[0.9302625,0.0000403262,0.06940029,0.00002177614,0.0001305104,0.00003472275,0.00005583686,0.00004589334,0.000008160076],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8238755,"threshold_uncertainty_score":0.9999478,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4319789103","doi":"10.1111/mice.12976","title":"Infrastructure deterioration modeling with an inhomogeneous continuous time Markov chain: A latent state approach with analytic transition probabilities","year":2023,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Markov chain; Balance equation; Markov chain mixing time; Variable-order Markov model; Markov property; Markov model; Examples of Markov chains; Continuous-time Markov chain; Computer science; Additive Markov chain; Markov process; Homogeneity (statistics); Markov renewal process; Mathematical optimization; Statistical physics; Mathematics; Statistics; Physics; Machine learning","retraction":null,"screen_n_in":null,"score":{"opus":0.00337814618201236,"gpt":0.1555790976150899,"spread":0.1522009514330775,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001570718,0.0006624191,0.0005937605,0.0004080344,0.0001667058,0.0002621529,0.0002123734,0.0001917071,0.000009868363],"category_scores_gemma":[0.000006029491,0.0005315075,0.00006490718,0.0005885421,0.00006854662,0.0006226127,0.00005689326,0.0004977455,0.000002243392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001479551,"about_ca_system_score_gemma":0.00004438515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001068599,"about_ca_topic_score_gemma":0.00001005915,"domain_scores_codex":[0.9978453,0.00003060607,0.0004396037,0.0005880403,0.000336441,0.0007600306],"domain_scores_gemma":[0.9991483,0.00002745653,0.00006920266,0.0003824956,0.0001367453,0.0002357715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007517431,0.000006088357,0.0001829924,0.000407779,0.0001337454,0.00004874414,0.002724859,0.9825737,0.003893255,0.00003416649,0.00003452906,0.009884946],"study_design_scores_gemma":[0.0007946056,0.0004138771,0.004964236,0.0002483161,0.00006001562,0.0003480857,0.0001558791,0.9916105,0.0003552301,0.0002599938,0.00007712107,0.0007121892],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6161496,0.00006354017,0.382306,0.000008523194,0.0001827755,0.000336348,0.00001910804,0.0008857154,0.00004836934],"genre_scores_gemma":[0.9667772,0.00004803205,0.03228946,0.00003283191,0.0004751008,0.00006215309,0.0001546648,0.0001468983,0.00001364201],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3506276,"threshold_uncertainty_score":0.9997137,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1997651055","doi":"10.1111/j.1467-8667.2006.00429.x","title":"A Computational Framework for Risk Assessment of RC Structures Using Indicators","year":2006,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Concrete Corrosion and Durability","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Probabilistic logic; Carbonation; Computer science; Reliability (semiconductor); Reliability engineering; Asset (computer security); Reinforced concrete; Basis (linear algebra); Corrosion; Asset management; Degradation (telecommunications); Risk analysis (engineering); Structural engineering; Engineering; Materials science; Mathematics; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.004645412777521086,"gpt":0.2234736059695905,"spread":0.2188281931920694,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00011582,0.0002723691,0.000358411,0.000226899,0.00008352327,0.00005561153,0.0001387637,0.0001622526,0.00002994858],"category_scores_gemma":[0.00003423412,0.0002677439,0.0001040776,0.0002558285,0.00004555043,0.0001177201,0.00006327951,0.0003012694,1.095526e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007289537,"about_ca_system_score_gemma":0.00003135405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008770615,"about_ca_topic_score_gemma":0.00000212896,"domain_scores_codex":[0.9988644,0.00001667418,0.0004230383,0.0002547725,0.0001778889,0.0002631881],"domain_scores_gemma":[0.9992738,0.0002782307,0.000100113,0.0001929533,0.00006185735,0.00009308493],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003699367,0.000004352294,0.007446779,0.0002270166,0.00003133124,6.714647e-7,0.00007325216,0.9759699,0.001368059,0.01053087,0.00012798,0.004216166],"study_design_scores_gemma":[0.0003181978,0.00003431103,0.1727335,0.00006007198,0.00002663057,0.00000957356,0.000008455881,0.8094752,0.0003909353,0.01640042,0.0003180561,0.0002245768],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4429445,0.0001424852,0.5562283,0.000003106799,0.0003524261,0.0001307109,0.0000460671,0.0001258737,0.00002649232],"genre_scores_gemma":[0.6952522,0.00000818292,0.3044501,0.00001120566,0.0002226965,0.000006364492,0.00002123484,0.00002756612,4.3814e-7],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2523077,"threshold_uncertainty_score":0.9999775,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2054881496","doi":"10.1111/j.1467-8667.2005.00386.x","title":"Ductility of Reinforced Concrete Flat Slab-Column Connections","year":2005,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Structural Load-Bearing Analysis","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Structural engineering; Ductility (Earth science); Slab; Punching; Finite element method; Reinforcement; Retrofitting; Materials science; Shear (geology); Reinforced concrete; Engineering; Composite material","retraction":null,"screen_n_in":null,"score":{"opus":0.003359278635432316,"gpt":0.1706638284692357,"spread":0.1673045498338034,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0000962129,0.0003466001,0.0004930272,0.0002365752,0.00008203043,0.00006130974,0.0002112853,0.0001690948,0.0001229268],"category_scores_gemma":[0.00004483762,0.0003589168,0.0001364762,0.0004003327,0.00006496432,0.0003056803,0.00009486249,0.0003796712,0.000005121034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009356565,"about_ca_system_score_gemma":0.00001429786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002491627,"about_ca_topic_score_gemma":0.000008259558,"domain_scores_codex":[0.9986254,0.00001407086,0.0004964665,0.000304424,0.0001862966,0.0003733377],"domain_scores_gemma":[0.999191,0.00009870087,0.00006828158,0.0003925912,0.00008109511,0.0001683661],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005833049,3.267363e-7,0.0003116297,0.0001817004,0.0002073119,0.000002470315,0.0003289498,0.7848976,0.2071538,0.0007449095,0.0006113598,0.00555419],"study_design_scores_gemma":[0.0004308717,0.00004277567,0.01042007,0.0000721416,0.00006608331,0.00006758369,0.00001971687,0.8894188,0.09528781,0.0000756146,0.003701842,0.0003966761],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9426363,0.0004609934,0.05486665,0.00003255509,0.0006915711,0.0001350774,0.00001855016,0.0006140172,0.0005442656],"genre_scores_gemma":[0.9818231,0.00006016016,0.01745691,0.00002645587,0.0005311563,0.000007359676,0.00001548295,0.00004487847,0.0000345363],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.111866,"threshold_uncertainty_score":0.9998863,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}