{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":9,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":9,"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":"e90da4c9436d","filters":{"venue":"Transportation Engineering"}},"results":[{"id":"W3041666796","doi":"10.1016/j.treng.2020.100013","title":"Smart transportation planning: Data, models, and algorithms","year":2020,"lang":"en","type":"article","venue":"Transportation Engineering","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":122,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"Ryerson University","keywords":"Exponential smoothing; Cluster analysis; Computer science; Autoregressive integrated moving average; Intelligent transportation system; Machine learning; Field (mathematics); Population; Artificial intelligence; Transportation planning; Time series; Kalman filter; Engineering; Transport engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.03778781692137233,"gpt":0.2241208272100097,"spread":0.1863330102886374,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005409687,0.0001463463,0.0001320194,0.00006754389,0.00002358193,0.0000194103,0.0001266398,0.00005627614,0.000007160863],"category_scores_gemma":[0.00000217658,0.0001751605,0.00002111996,0.0001470282,0.0000088292,0.0005223532,0.000001826208,0.0001268837,0.00000253252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008700368,"about_ca_system_score_gemma":0.000003792987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006714462,"about_ca_topic_score_gemma":0.000006910686,"domain_scores_codex":[0.999286,0.000002575003,0.0002265554,0.0002123322,0.0001286478,0.0001439083],"domain_scores_gemma":[0.9997128,0.00001051393,0.00001625408,0.0001356504,0.00001186371,0.0001129489],"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":[0.000006091053,0.000006289316,0.0002859281,0.000244246,0.0000476267,0.00001517135,0.001638861,0.9875162,0.001121783,0.001695627,0.002822189,0.004599969],"study_design_scores_gemma":[0.0002489655,0.0000161737,0.01190802,0.00002568894,0.00003660523,4.514134e-7,0.00007483709,0.9757728,0.0003819346,0.0000152005,0.01133583,0.0001835229],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02872913,0.0003475775,0.9641621,0.0001396105,0.0001256745,0.0001652099,0.0001342831,0.005980368,0.0002160342],"genre_scores_gemma":[0.9888898,0.0002025188,0.009935753,0.0000756599,0.00005230069,0.00001824416,0.0007823572,0.00003996432,0.000003446835],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9601606,"threshold_uncertainty_score":0.7142839,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4224273618","doi":"10.1016/j.treng.2022.100115","title":"3D object detection for autonomous driving: Methods, models, sensors, data, and challenges","year":2022,"lang":"en","type":"article","venue":"Transportation Engineering","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":42,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Object detection; Categorization; Artificial intelligence; Object (grammar); Focus (optics); Computer vision; Data mining; Pattern recognition (psychology)","retraction":null,"screen_n_in":null,"score":{"opus":0.05284242472348057,"gpt":0.2838832401896235,"spread":0.2310408154661429,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002464074,0.000104961,0.0001072616,0.00008173753,0.0001804555,0.00001942487,0.0003425837,0.00002174574,0.000001506453],"category_scores_gemma":[0.000008063073,0.0001293568,0.00002178,0.0001902161,0.000006427952,0.000479491,0.00003345939,0.0001151587,2.557984e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000324763,"about_ca_system_score_gemma":0.00001305197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003606176,"about_ca_topic_score_gemma":0.00001673808,"domain_scores_codex":[0.9991389,0.00002101753,0.0001755586,0.0003974222,0.0001032472,0.0001638641],"domain_scores_gemma":[0.9993036,0.0001641815,0.00005479986,0.0004081584,0.00002114271,0.00004807773],"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":[0.000002001444,0.000009064768,0.000002573604,0.00002604854,0.000008611065,8.523425e-7,0.0005356214,0.8840604,0.002311404,0.01263578,0.000003512072,0.1004041],"study_design_scores_gemma":[0.0001392755,0.00002856559,0.000565812,0.000002675463,0.00001062862,0.000006652631,0.0000387058,0.9810506,0.0008013868,0.001208379,0.01600956,0.0001378263],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003478526,0.0009806125,0.9943726,0.0003069711,0.0001534127,0.0002934418,0.00002758403,0.0003754676,0.0000113789],"genre_scores_gemma":[0.4985251,0.0002092999,0.5009311,0.00001420673,0.00002901434,0.0002129663,0.00005053248,0.00001645015,0.00001134247],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4950466,"threshold_uncertainty_score":0.5275016,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3185095324","doi":"10.1016/j.treng.2021.100087","title":"A data-driven model for safety risk identification from flight data analysis","year":2021,"lang":"en","type":"article","venue":"Transportation Engineering","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":16,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Group for Research in Decision Analysis; Polytechnique Montréal","funders":"Mitacs","keywords":"Runway; Aviation; Fault tree analysis; Aviation accident; Computer science; Aviation safety; Identification (biology); Risk analysis (engineering); Aeronautics; Data mining; Engineering; Reliability engineering; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.1711923024703331,"gpt":0.4046555615509826,"spread":0.2334632590806495,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003223741,0.0001222986,0.000276489,0.00005948653,0.00006083972,0.00002406839,0.0003200315,0.00005435334,0.00003198938],"category_scores_gemma":[0.0005487665,0.0001308137,0.00006230847,0.0002659953,0.00000773255,0.0003487289,0.0000165502,0.00009343652,0.000001359778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001837212,"about_ca_system_score_gemma":0.00002975397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000142343,"about_ca_topic_score_gemma":0.0004011027,"domain_scores_codex":[0.9986768,0.00002101502,0.0004741194,0.0005188294,0.0001636655,0.0001455703],"domain_scores_gemma":[0.9978198,0.0006709737,0.0001212267,0.001221198,0.0001026367,0.00006420393],"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":[0.00001683974,0.00003997743,0.00006444904,0.00007319005,0.0004618468,0.000003206424,0.0003866892,0.954334,0.001727653,0.04002454,0.00006873249,0.002798938],"study_design_scores_gemma":[0.0002447245,0.000002080843,0.001573177,0.00001267085,0.001616105,8.624581e-8,0.00002819361,0.9566551,0.0002908699,0.03906805,0.0003649167,0.0001440295],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003752426,0.00006220383,0.9604376,0.00003984929,0.00006483728,0.0001580114,0.03538548,0.00009297274,0.000006654739],"genre_scores_gemma":[0.1373712,0.00006397605,0.8391118,0.000007423778,0.00003734963,0.00001943071,0.0232872,0.00002548594,0.00007611263],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1336188,"threshold_uncertainty_score":0.533443,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4407986324","doi":"10.1016/j.treng.2025.100312","title":"Effect of aging kinetics on the fatigue behavior of asphalt mixtures incorporating various RAP contents","year":2025,"lang":"en","type":"article","venue":"Transportation Engineering","topic":"Asphalt Pavement Performance Evaluation","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Asphalt; Kinetics; Materials science; Composite material; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.01326546339592378,"gpt":0.2562566467723457,"spread":0.2429911833764219,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000306704,0.0001694611,0.000216542,0.0001697131,0.00002680903,0.000007079647,0.0001244184,0.00006068604,0.00001547901],"category_scores_gemma":[0.00003255249,0.0001437013,0.00006452968,0.000314241,0.00002007093,0.000094461,0.000002424259,0.0001501892,9.588829e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000394075,"about_ca_system_score_gemma":0.000008297918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000104629,"about_ca_topic_score_gemma":0.00000754234,"domain_scores_codex":[0.9990211,0.00002220369,0.0004702657,0.0001059147,0.0002421708,0.0001383371],"domain_scores_gemma":[0.9994399,0.0002082486,0.00009681375,0.0001710904,0.00006276702,0.00002121104],"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":[0.00001042251,0.00001982748,0.01153728,0.0006619308,0.00005769851,0.000001130016,0.0003358542,0.8007135,0.183442,0.0006233546,0.00001299545,0.002584084],"study_design_scores_gemma":[0.0005490056,0.000136797,0.05263749,0.0003704797,0.0001232242,1.520633e-7,0.00002659527,0.1547629,0.7912617,0.000008217099,0.000008936613,0.0001145472],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9388487,0.0001579714,0.05988809,0.00001638467,0.0003174387,0.000468984,0.00001414221,0.0001194124,0.0001688698],"genre_scores_gemma":[0.9992427,0.00001325147,0.0005463615,0.00001149822,0.00001509003,0.00008814692,0.00004884194,0.0000246337,0.000009519614],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6459506,"threshold_uncertainty_score":0.585997,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4284969520","doi":"10.1016/j.treng.2022.100124","title":"Ultra-low NOx diesel aftertreatment: An assessment by simulation","year":2022,"lang":"en","type":"article","venue":"Transportation Engineering","topic":"Catalytic Processes in Materials Science","field":"Materials Science","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"General Motors of Canada","keywords":"Robustness (evolution); NOx; Context (archaeology); Computer science; Diesel fuel; Automotive engineering; Procurement; Process (computing); Environmental science; Systems engineering; Simulation; Combustion; Engineering; Business","retraction":null,"screen_n_in":null,"score":{"opus":0.007020296165010977,"gpt":0.2678479680439302,"spread":0.2608276718789192,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003295855,0.0001523294,0.0001439105,0.00006795926,0.0002017462,0.00007404381,0.0002590607,0.00002374316,0.002930989],"category_scores_gemma":[0.00001255534,0.0001672484,0.00003128377,0.0002219036,0.00002390207,0.0005631396,0.00000738782,0.00006905664,0.00002605588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001631625,"about_ca_system_score_gemma":0.0000438966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003302216,"about_ca_topic_score_gemma":0.000004204011,"domain_scores_codex":[0.998613,0.0000219612,0.0002935414,0.0003457311,0.0004713562,0.0002543906],"domain_scores_gemma":[0.9995067,0.00005531123,0.00008451045,0.0002271949,0.00004117552,0.00008515036],"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":[0.000007276576,0.00005023994,0.0000849735,0.00002659117,0.000001927575,0.000003763824,0.0003453512,0.5040226,0.4952907,0.00008323367,0.00001656719,0.00006675199],"study_design_scores_gemma":[0.001168228,0.0003636164,0.01399556,0.00003201523,0.00006455179,0.000007558588,0.0003880343,0.3280167,0.6505037,0.0001538534,0.00447869,0.0008274685],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9228228,0.0000374884,0.07578184,0.00003045779,0.0004449367,0.0001920772,0.0003377947,0.0002655844,0.00008701105],"genre_scores_gemma":[0.996309,0.000002569836,0.002802775,0.00003723039,0.00003270612,0.0001779696,0.0004750427,0.00002517734,0.0001375049],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1760059,"threshold_uncertainty_score":0.9979805,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3086620783","doi":"10.1016/j.treng.2020.100021","title":"Impacts of road and rail temporal traffic variations on grade crossings exposure, design, and regulation in Manitoba","year":2020,"lang":"en","type":"article","venue":"Transportation Engineering","topic":"Traffic and Road Safety","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Level crossing; Train; Product (mathematics); Transport engineering; Computer science; Environmental science; Warning system; Engineering; Geography; Mathematics; Telecommunications; Cartography","retraction":null,"screen_n_in":null,"score":{"opus":0.01483814174372709,"gpt":0.1941730200541121,"spread":0.179334878310385,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000766423,0.00012969,0.0001573206,0.00009804207,0.0000241857,0.0000148447,0.0000306347,0.00006996841,0.000003819132],"category_scores_gemma":[0.000007932086,0.0001415183,0.00002115275,0.0002012402,0.00001533347,0.0001653137,8.631741e-7,0.0001069454,6.112722e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001636684,"about_ca_system_score_gemma":0.00001015037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002602533,"about_ca_topic_score_gemma":0.00006287503,"domain_scores_codex":[0.9993641,0.000007863415,0.0002768587,0.0001296516,0.00009619391,0.0001252703],"domain_scores_gemma":[0.9997938,0.00003469242,0.00002889526,0.00005187023,0.00001240359,0.00007835288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00002094542,0.00001097844,0.003152001,0.0001693968,0.00001347234,0.000002784072,0.003092849,0.9842196,0.00671143,0.0002325342,0.000008430794,0.002365541],"study_design_scores_gemma":[0.0005628418,0.0000446684,0.6158599,0.0000520676,0.00001146889,8.341551e-7,0.00005654813,0.3823147,0.0009398136,0.000005231747,0.00004074855,0.0001111698],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9030349,0.0002006947,0.09628236,0.00006114236,0.00004852661,0.0001685775,0.00001058944,0.0001847606,0.00000845294],"genre_scores_gemma":[0.9948777,0.00005139611,0.004968068,0.00001036074,0.00002447894,0.000007773431,0.00003254559,0.00002636827,0.000001325249],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6127079,"threshold_uncertainty_score":0.5770947,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4403634878","doi":"10.1016/j.treng.2024.100284","title":"Ensemble-based model to investigate factors influencing road crash fatality for imbalanced data","year":2024,"lang":"en","type":"article","venue":"Transportation Engineering","topic":"Traffic and Road Safety","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Crash; Road accident; Computer science; Transport engineering; Statistics; Engineering; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.03787001009734391,"gpt":0.254573342776216,"spread":0.2167033326788721,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001284332,0.0002378711,0.000199072,0.0001445092,0.0000405261,0.00004627837,0.0002355688,0.00009007318,0.000005367258],"category_scores_gemma":[0.00001604451,0.0002462839,0.00006765213,0.0002771805,0.000008835966,0.0003362063,0.000004267303,0.0001543367,0.000007694754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006510878,"about_ca_system_score_gemma":0.00005250653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001610496,"about_ca_topic_score_gemma":0.00009354579,"domain_scores_codex":[0.9988696,0.000002894427,0.000332824,0.0003299596,0.0001558116,0.0003088832],"domain_scores_gemma":[0.9993982,0.00005267439,0.0000119572,0.0003462795,0.00002665382,0.0001642355],"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":[0.000004659559,0.000004053781,0.000356207,0.0005775773,0.00003788566,0.000002817247,0.0008434678,0.9790223,0.01764578,0.0003755628,0.000161736,0.000967963],"study_design_scores_gemma":[0.0001997507,0.000009860455,0.02160898,0.000141122,0.00004218472,2.153722e-7,0.00003146417,0.9703422,0.00629759,0.0000227492,0.001006677,0.0002972095],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4522355,0.00007883452,0.5455511,0.00003108675,0.0002657947,0.0002156988,0.0004675113,0.001135757,0.0000187029],"genre_scores_gemma":[0.9827821,0.000007033544,0.01587437,0.00003255026,0.00005917969,0.00005193761,0.001091832,0.00008359174,0.00001735572],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5305466,"threshold_uncertainty_score":0.9999989,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4387642787","doi":"10.1016/j.treng.2023.100208","title":"Macroscopic traffic characterization based on driver memory and traffic stimuli","year":2023,"lang":"en","type":"article","venue":"Transportation Engineering","topic":"Traffic control and management","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"Higher Education Commision, Pakistan; University of Engineering and Technology, Peshawar","keywords":"Bottleneck; Headway; Zhàng; Traffic flow (computer networking); Traffic bottleneck; Traffic model; Computer science; Function (biology); Traffic wave; Simulation; Flow (mathematics); Traffic congestion reconstruction with Kerner's three-phase theory; Characterization (materials science); Microscopic traffic flow model; Traffic generation model; Real-time computing; Floating car data; Traffic optimization; Engineering; Traffic congestion; Mechanics; Physics; Computer network; Transport engineering; Embedded system; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.006360435535643829,"gpt":0.1879761023360367,"spread":0.1816156668003928,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006561281,0.0001778338,0.0001471266,0.0002406004,0.00003707995,0.00002638591,0.0000567821,0.00005542201,0.00003606895],"category_scores_gemma":[0.000002418918,0.0002005035,0.00004051922,0.000306097,0.000009260915,0.0001099346,0.0000010995,0.00009894912,0.00004150797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002545857,"about_ca_system_score_gemma":0.000005392793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.713331e-7,"about_ca_topic_score_gemma":0.000009988944,"domain_scores_codex":[0.999239,0.000004467679,0.0001967418,0.0001812524,0.0001493288,0.000229223],"domain_scores_gemma":[0.9997554,0.00003267383,0.00001519327,0.000112977,0.00001154913,0.00007215986],"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":[0.000006545296,0.000009845132,0.00002086208,0.0001732257,0.00001755998,0.00001340757,0.0004255235,0.971045,0.006580411,0.00004801478,0.00004599785,0.02161367],"study_design_scores_gemma":[0.0006412942,0.00002170994,0.1365036,0.00004392852,0.00002364087,1.773519e-7,0.0000261495,0.860935,0.0001699578,3.550129e-7,0.001455167,0.0001789739],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9812202,0.00002464114,0.015843,0.00007443175,0.0003996365,0.0002505414,0.00003426426,0.002103652,0.00004966067],"genre_scores_gemma":[0.9991413,0.00004794007,0.0001809706,0.00003323055,0.00005063814,0.00005637805,0.0003573774,0.00005046265,0.00008167385],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1364827,"threshold_uncertainty_score":0.8176295,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4415070958","doi":"10.1016/j.treng.2025.100397","title":"Blended wing body designs for aerodynamic, stability, and control optimization: A comprehensive review","year":2025,"lang":"en","type":"review","venue":"Transportation Engineering","topic":"Advanced Aircraft Design and Technologies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"United Arab Emirates University","keywords":"Propulsion; Aerospace; Fuselage; Airworthiness; Payload (computing); Aviation; Aerodynamics; Control (management)","retraction":null,"screen_n_in":null,"score":{"opus":0.02645579968896309,"gpt":0.2724703631349373,"spread":0.2460145634459742,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001141488,0.0003359672,0.0009329183,0.00007128801,0.00006601722,0.00001345534,0.0001650566,0.0001526064,0.00008783407],"category_scores_gemma":[0.00005694129,0.0003197405,0.0001802367,0.0003055696,0.00005119314,0.0001495948,0.000009334291,0.0001707827,0.00000267155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001072733,"about_ca_system_score_gemma":0.00002889597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000290947,"about_ca_topic_score_gemma":0.000004259009,"domain_scores_codex":[0.9987094,0.00002298386,0.0005000806,0.0004186934,0.0001241194,0.0002247214],"domain_scores_gemma":[0.9992331,0.0003380896,0.0001392765,0.0002219603,0.0000192454,0.0000483857],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001335468,0.00005788709,0.00002948114,0.262865,0.0002450286,0.00001543447,0.00006354772,0.2010922,0.0001226807,0.0006023234,0.0001554849,0.5347376],"study_design_scores_gemma":[0.001427208,0.0001466908,0.0001579606,0.07164808,0.003437277,0.00001303441,0.00003013891,0.03644291,0.00002955344,0.0001663649,0.8847213,0.001779496],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[8.479577e-7,0.5564228,0.4419576,0.00002615787,0.00003976397,0.001310054,0.0000714704,0.0001580357,0.00001325631],"genre_scores_gemma":[0.00009747531,0.9688835,0.03011324,0.0000486973,0.000008735902,0.0005677136,0.0002255477,0.00003265378,0.00002244505],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8845658,"threshold_uncertainty_score":0.9999255,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}