{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":7,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":7,"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","author_layer_release":"2026-06-26"},"query_hash":"e7d2ed982676","filters":{"venue":"Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2018"}},"results":[{"id":"W2794732825","doi":"10.1117/12.2295954","title":"Deep faster R-CNN-based automated detection and localization of multiple types of damage","year":2018,"lang":"en","type":"article","venue":"Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2018","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":true,"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; Robustness (evolution); Artificial intelligence; Consistency (knowledge bases); Visual inspection; Structural health monitoring; Bridge (graph theory); Computer vision; Pattern recognition (psychology); Engineering; Structural engineering","authors":[{"name":"Gahyun Suh","is_ca":true},{"name":"Young‐Jin Cha","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.006338425982700346,"gpt":0.2075250439961183,"spread":0.201186618013418,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004952769,0.001122194,0.0006087448,0.0008817973,0.0001737216,0.0004610355,0.001410202,0.0007071364,0.002578532],"category_scores_gemma":[0.001013799,0.0004736639,0.0006533499,0.00047047,0.0003074982,0.001141145,0.0007106771,0.0006193733,0.0009691557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009154777,"about_ca_system_score_gemma":0.0007492747,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01109718,"about_ca_topic_score_gemma":0.01701067,"domain_scores_codex":[0.9996356,0.00002526546,0.00001440056,0.0001279534,0.000111836,0.00008498639],"domain_scores_gemma":[0.9994901,0.00008659208,0.00009681311,0.0001282017,0.000168457,0.00002970002],"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":[0.0004865038,0.0002950979,0.005123404,0.0002426949,0.0002381983,0.0004211032,0.00008468044,0.2775129,0.1197224,0.002275126,0.01019337,0.5834045],"study_design_scores_gemma":[0.000009322275,0.00007811388,0.002413613,0.00001517244,0.00003571277,0.00011304,0.000009995288,0.9769948,0.01841485,0.0006350713,0.001266031,0.00001429904],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2567563,0.001775678,0.7168593,0.0003632001,0.0002666583,0.000166607,0.001332396,0.01296588,0.009513925],"genre_scores_gemma":[0.7776973,0.0005449684,0.2079981,0.0002933487,0.00005513652,0.00009035402,0.0023573,0.0002454452,0.010718],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01109718,"threshold_uncertainty_score":0.02206516,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2795331216","doi":"10.1117/12.2295966","title":"Automated damage-sensitive feature extraction using unsupervised convolutional neural networks","year":2018,"lang":"en","type":"article","venue":"Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2018","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Convolutional neural network; Artificial intelligence; Pattern recognition (psychology); Feature extraction; Support vector machine; Novelty detection; Feature (linguistics); Unsupervised learning; Test data; Feature learning; Machine learning; Deep learning; Novelty","authors":[{"name":"Young‐Jin Cha","is_ca":true},{"name":"Zilong Wang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01082749592005392,"gpt":0.2374454245919931,"spread":0.2266179286719392,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003474982,0.0010369,0.0006093807,0.001244504,0.0002000655,0.0003796935,0.0007302277,0.0005500564,0.0005870786],"category_scores_gemma":[0.0009496061,0.0003419296,0.0007375227,0.0008119622,0.0003473637,0.0008430628,0.0007610922,0.0006092951,0.0003126897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000458444,"about_ca_system_score_gemma":0.0004827039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003133248,"about_ca_topic_score_gemma":0.005574121,"domain_scores_codex":[0.9996272,0.00003064846,0.00002153441,0.0001181523,0.0001268177,0.00007553543],"domain_scores_gemma":[0.9995769,0.00008230853,0.0001141968,0.00008406914,0.0001236249,0.0000190405],"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":[0.0002612692,0.0003322288,0.01117001,0.0001990722,0.0001645322,0.0004111926,0.000128142,0.1326842,0.155849,0.001620242,0.00442302,0.692757],"study_design_scores_gemma":[0.00001050222,0.0001011835,0.01334194,0.00001626324,0.0000340259,0.0001809657,0.00003457709,0.9406203,0.04217017,0.001818186,0.00164805,0.00002382991],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2077122,0.0004833782,0.7861992,0.0001430247,0.00006585309,0.0001014604,0.000634944,0.002660407,0.001999592],"genre_scores_gemma":[0.8281983,0.0003441567,0.1656127,0.0001025982,0.00004936835,0.0001184235,0.00221447,0.00008312239,0.003276974],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003133248,"threshold_uncertainty_score":0.006229997,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2794552144","doi":"10.1117/12.2295962","title":"Vision-based concrete crack detection technique using cascade features","year":2018,"lang":"en","type":"article","venue":"Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2018","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"","keywords":"Cascade; Computer science; Structural health monitoring; Artificial intelligence; Face (sociological concept); Delamination (geology); Structural engineering; Bounding overwatch; Sensitivity (control systems); Computer vision; Pattern recognition (psychology); Engineering; Geology","authors":[{"name":"Young‐Jin Cha","is_ca":true},{"name":"Dharshan Lokekere Gopal","is_ca":true},{"name":"Rahmat Ali","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.008387589538341726,"gpt":0.2345909283736748,"spread":0.226203338835333,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004197023,0.0007108559,0.0008782977,0.001997608,0.0003433656,0.0004624301,0.0009202308,0.0007511102,0.001993118],"category_scores_gemma":[0.0008476991,0.0003291709,0.0009828162,0.000717896,0.0002883685,0.0009868264,0.000618208,0.0007759602,0.0008168782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003493247,"about_ca_system_score_gemma":0.0004299283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002946181,"about_ca_topic_score_gemma":0.003914498,"domain_scores_codex":[0.9993696,0.00003406759,0.00002481954,0.0001808751,0.0003053078,0.0000853746],"domain_scores_gemma":[0.9994616,0.0001125116,0.00005444362,0.0000830501,0.0002492526,0.00003920492],"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":[0.0002826133,0.000216253,0.003258686,0.0001225869,0.00008468243,0.0002337653,0.000091088,0.01827577,0.2539111,0.001208243,0.002502331,0.7198128],"study_design_scores_gemma":[0.00002132577,0.0004126552,0.009622411,0.00001759847,0.00007512759,0.0008471821,0.00003644697,0.8598404,0.1249021,0.0007643698,0.003415933,0.00004448422],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08175968,0.0004607987,0.9127832,0.00008004182,0.00009668827,0.0001964118,0.0001488554,0.001543802,0.00293055],"genre_scores_gemma":[0.5566093,0.0004316311,0.4371957,0.00009026021,0.00008822846,0.0001107234,0.0004730005,0.00009706205,0.004904092],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002946181,"threshold_uncertainty_score":0.006667674,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2795198781","doi":"10.1117/12.2295961","title":"Damage detection with an autonomous UAV using deep learning","year":2018,"lang":"en","type":"article","venue":"Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2018","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"","keywords":"Beacon; Global Positioning System; Computer science; Real-time computing; Drone; GPS signals; Convolutional neural network; Deep learning; Bridge (graph theory); Structural health monitoring; Artificial intelligence; Visual inspection; Assisted GPS; Engineering; Telecommunications","authors":[{"name":"Young‐Jin Cha","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.008482150627451607,"gpt":0.2151657905703628,"spread":0.2066836399429112,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001586203,0.0005703633,0.0003042705,0.0004069849,0.000180569,0.0002735696,0.0005453023,0.0006403811,0.0005758675],"category_scores_gemma":[0.0004500832,0.000251436,0.0002693957,0.0002438435,0.0002584691,0.0005061626,0.0004079422,0.0005093613,0.0001737397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005257387,"about_ca_system_score_gemma":0.000356146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006751241,"about_ca_topic_score_gemma":0.009020684,"domain_scores_codex":[0.9998908,0.000009821433,0.000004189615,0.00003862178,0.00003255843,0.00002398868],"domain_scores_gemma":[0.999841,0.00004136018,0.00003320165,0.00002531279,0.00004427526,0.0000148962],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002861604,0.0002268003,0.008346885,0.00008925493,0.0001087855,0.0004259093,0.00009707973,0.5499257,0.07436819,0.001440978,0.003165962,0.3615183],"study_design_scores_gemma":[0.000003313092,0.00004037019,0.0009391351,0.00000333157,0.000005113049,0.00002934082,0.00000691297,0.9939031,0.004418454,0.0003893733,0.0002582373,0.000003299656],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3644231,0.00077616,0.6268508,0.0004433566,0.0001269073,0.00007733548,0.0002484845,0.003541681,0.0035121],"genre_scores_gemma":[0.9249366,0.0001102042,0.07290465,0.00008498336,0.00001696805,0.00002668416,0.0001713302,0.00002110607,0.00172746],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006751241,"threshold_uncertainty_score":0.01342386,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2795205653","doi":"10.1117/12.2295947","title":"Automated air-coupled impact echo based non-destructive testing using machine learning","year":2018,"lang":"en","type":"article","venue":"Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2018","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"","keywords":"Automation; Computer science; Echo (communications protocol); Ground-penetrating radar; Artificial neural network; Non-regression testing; Integration testing; Nondestructive testing; Radar; Repeatability; Test strategy; Software performance testing; Reliability engineering; Artificial intelligence; Engineering; Software; Mechanical engineering","authors":[{"name":"Young‐Jin Cha","is_ca":true},{"name":"Tyler Epp","is_ca":true},{"name":"Dagmar Svecova","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01798014064458928,"gpt":0.2688178986548947,"spread":0.2508377580103055,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003721863,0.0004919404,0.0003753006,0.0004555736,0.0001705677,0.0004399203,0.0006705991,0.0004124648,0.001335751],"category_scores_gemma":[0.0009932129,0.0001922565,0.0002262574,0.0003404848,0.0003069297,0.0006006474,0.0004687776,0.0003566987,0.0004673016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002365484,"about_ca_system_score_gemma":0.0003435703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009692537,"about_ca_topic_score_gemma":0.001838793,"domain_scores_codex":[0.9996436,0.00006775663,0.00001824581,0.00008933995,0.0001507542,0.00003030061],"domain_scores_gemma":[0.9991954,0.0003691451,0.0001184174,0.0001153159,0.0001771546,0.00002460431],"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":[0.0002709109,0.0003875881,0.004548043,0.0001629487,0.00006283803,0.0001269223,0.0001208968,0.1349503,0.1261159,0.001175687,0.0009702972,0.7311076],"study_design_scores_gemma":[0.0000077281,0.000129847,0.003093226,0.000006052935,0.00000807813,0.0000640209,0.00001632064,0.9741062,0.0214134,0.0006894254,0.0004537864,0.00001188073],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1014401,0.0001197145,0.8948085,0.00005065711,0.00001988752,0.00008519532,0.00005754579,0.001693151,0.001725242],"genre_scores_gemma":[0.7650756,0.00008606068,0.2322634,0.00006365659,0.00001795275,0.0001404066,0.0001515672,0.00005352427,0.002147895],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001335751,"threshold_uncertainty_score":0.004468501,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2794782535","doi":"10.1117/12.2295952","title":"Identification of large-scale systems with noisy data using an iterated cubature unscented Kalman filter","year":2018,"lang":"en","type":"article","venue":"Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2018","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"","keywords":"Kalman filter; Extended Kalman filter; Robustness (evolution); Invariant extended Kalman filter; Control theory (sociology); Computer science; Fast Kalman filter; Covariance; Unscented transform; Nonlinear system; Linear system; Ensemble Kalman filter; Covariance intersection; System identification; Divergence (linguistics); State vector; Covariance matrix; Noise (video); Algorithm; Mathematics; Artificial intelligence; Data mining; Statistics; Measure (data warehouse)","authors":[{"name":"Young‐Jin Cha","is_ca":true},{"name":"Esmaeil Ghorbani","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02596909191448808,"gpt":0.2839933880670992,"spread":0.2580242961526111,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009581485,0.0008295446,0.001082132,0.0005262561,0.0003785354,0.0007333834,0.0008716452,0.0008431074,0.0008011563],"category_scores_gemma":[0.002802073,0.0004776739,0.0009640151,0.0005864422,0.0004784081,0.0009678197,0.0007851599,0.001065964,0.0003251763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004858961,"about_ca_system_score_gemma":0.0008859345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007360827,"about_ca_topic_score_gemma":0.004768852,"domain_scores_codex":[0.9993901,0.0001551696,0.00005811483,0.0001640174,0.0001900153,0.00004254432],"domain_scores_gemma":[0.999161,0.00040368,0.0001436431,0.00008698337,0.0001884589,0.0000162699],"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":[0.0001129577,0.00004286148,0.001491777,0.0002882419,0.0001795705,0.0001618069,0.0002543314,0.8209304,0.01245573,0.009897642,0.0007967948,0.1533878],"study_design_scores_gemma":[0.000002962347,0.00001593994,0.0001936166,0.00000746375,0.000008693646,0.00002007023,0.000006523409,0.9973787,0.001116598,0.0008442737,0.0003988376,0.000006371238],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003566928,0.0001523006,0.9957402,0.00002544752,0.00001232193,0.00001115809,0.00001316073,0.0001790781,0.0002993978],"genre_scores_gemma":[0.6124211,0.001084411,0.3826902,0.0001114407,0.00007583333,0.0002819205,0.0002932411,0.00009235163,0.002949538],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007360827,"threshold_uncertainty_score":0.01463592,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2796305543","doi":"10.1117/12.2295959","title":"Automated volumetric damage detection and quantification using region-based convolution neural networks and an inexpensive depth camera","year":2018,"lang":"en","type":"article","venue":"Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2018","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Convolutional neural network; Artificial intelligence; Pixel; Volume (thermodynamics); Computer vision; Fuse (electrical); Spall; Segmentation; Materials science; Engineering","authors":[{"name":"Young‐Jin Cha","is_ca":true},{"name":"Gustavo H. Beckman","is_ca":true},{"name":"Dimos Polyzois","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01699239035668196,"gpt":0.2465565993788125,"spread":0.2295642090221305,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003420507,0.0006997305,0.0003993651,0.0009713063,0.0001184317,0.000412159,0.0007806044,0.0005333031,0.001233108],"category_scores_gemma":[0.0007600558,0.0003406149,0.0003680377,0.0004606812,0.0002191516,0.0007560159,0.0006629735,0.0003326525,0.0004424968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005291326,"about_ca_system_score_gemma":0.000413399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002969097,"about_ca_topic_score_gemma":0.005712287,"domain_scores_codex":[0.9996295,0.00003323803,0.00001466912,0.0001032093,0.000173848,0.00004551704],"domain_scores_gemma":[0.9996253,0.00006598479,0.0000969516,0.00008192017,0.0001126979,0.00001701408],"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":[0.0003556844,0.0001545134,0.007487038,0.0002415066,0.0001097202,0.0001929565,0.0001008936,0.09482454,0.3898131,0.001428679,0.001807692,0.5034836],"study_design_scores_gemma":[0.00001158452,0.0002072328,0.01334566,0.00002856682,0.00005128379,0.0003949561,0.00003911483,0.8486112,0.1338729,0.000886964,0.002516513,0.00003400978],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1667842,0.0005308635,0.8269232,0.00007080079,0.0000431838,0.00009083168,0.00049399,0.002842258,0.00222064],"genre_scores_gemma":[0.6642026,0.0004113802,0.3315316,0.00007517376,0.00002346292,0.0001031285,0.0007618944,0.00009990021,0.002790909],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002969097,"threshold_uncertainty_score":0.005903602,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}