{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":15,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":15,"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":"ca24bf11500f","filters":{"venue":"Journal of Modern Transportation"}},"results":[{"id":"W2080093988","doi":"10.1007/s40534-015-0068-0","title":"Identification of crash hotspots using kernel density estimation and kriging methods: a comparison","year":2015,"lang":"en","type":"article","venue":"Journal of Modern Transportation","topic":"Traffic and Road Safety","field":"Engineering","cited_by":158,"is_retracted":false,"has_abstract":true,"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; Minnesota Department of Transportation; U.S. Department of Transportation","keywords":"Hotspot (geology); Kernel density estimation; Kriging; Crash; Computer science; Statistics; Data mining; Geography; Mathematics; Geology","authors":[{"name":"Lalita Thakali","is_ca":true},{"name":"Tae J. Kwon","is_ca":true},{"name":"Liping Fu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03982573114077832,"gpt":0.3218337965003856,"spread":0.2820080653596073,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005369239,0.0007392851,0.001258684,0.003445924,0.0002675201,0.0009242205,0.0009071757,0.0007501314,0.0004162637],"category_scores_gemma":[0.01931125,0.0003575064,0.0009159938,0.001902277,0.0003147508,0.00145713,0.0006303167,0.0005951081,0.0001586096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007208009,"about_ca_system_score_gemma":0.001001004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01062336,"about_ca_topic_score_gemma":0.008866925,"domain_scores_codex":[0.9971411,0.001487655,0.0002114324,0.0003329428,0.0007104744,0.0001163235],"domain_scores_gemma":[0.9867507,0.009991012,0.0007198455,0.0007283822,0.00166565,0.0001444812],"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":[0.00166854,0.0003740822,0.1738958,0.00112536,0.001245389,0.0001711905,0.001326292,0.3419358,0.004215503,0.005324439,0.0006202954,0.4680974],"study_design_scores_gemma":[0.00006333192,0.0006957061,0.08973781,0.0001121395,0.0002820652,0.0002612062,0.000903182,0.9000132,0.004214127,0.001948469,0.001647854,0.0001209114],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6517041,0.003435243,0.340327,0.00022786,0.00005877164,0.0001985956,0.0003207227,0.0005779044,0.003149803],"genre_scores_gemma":[0.9248142,0.0009926572,0.07361638,0.00001449012,0.00001170812,0.00004504846,0.0002138176,0.00003516303,0.0002565378],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01062336,"threshold_uncertainty_score":0.02839565,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2952894872","doi":"10.1007/s40534-019-0188-z","title":"Statistical delay distribution analysis on high-speed railway trains","year":2019,"lang":"en","type":"article","venue":"Journal of Modern Transportation","topic":"Railway Systems and Energy Efficiency","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"National Natural Science Foundation of China; China Railway","keywords":"Train; Log-normal distribution; Exponential distribution; Goodness of fit; Distribution fitting; Statistics; Logistic distribution; Gamma distribution; Probability distribution; Mathematics; Distribution (mathematics); Computer science; Logistic regression; Mathematical analysis","authors":[{"name":"Yuxiang Yang","is_ca":false},{"name":"Ping Huang","is_ca":true},{"name":"Qiyuan Peng","is_ca":false},{"name":"Jie Li","is_ca":false},{"name":"Chao Wen","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.005781184182445611,"gpt":0.2020242286007375,"spread":0.1962430444182919,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002308806,0.0007058915,0.0004476407,0.002234857,0.0003984645,0.0009560165,0.0009487745,0.0006713425,0.001338834],"category_scores_gemma":[0.009226197,0.0002853473,0.001049268,0.002464246,0.0006613778,0.001604683,0.0004590284,0.0007819691,0.0003386957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001743204,"about_ca_system_score_gemma":0.001070444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0114155,"about_ca_topic_score_gemma":0.004513946,"domain_scores_codex":[0.9986978,0.00027486,0.00006805734,0.0003044835,0.0004901016,0.000164604],"domain_scores_gemma":[0.9941434,0.003310613,0.0009436343,0.0004391074,0.001046194,0.0001170404],"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":[0.0001745447,0.00008079192,0.05915609,0.0001279871,0.0001163222,0.0004194135,0.000367167,0.8898003,0.004847823,0.01652447,0.000779591,0.02760559],"study_design_scores_gemma":[0.00000654834,0.00006977466,0.02130621,0.00001116022,0.00002172527,0.0002378134,0.000179632,0.969843,0.001315678,0.00598274,0.0009891888,0.00003647282],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6089678,0.000568443,0.3857995,0.0002047115,0.00003511906,0.00009610248,0.0008400722,0.0005577442,0.002930513],"genre_scores_gemma":[0.9917183,0.0002581091,0.006470334,0.00001484808,0.00001711051,0.00003769796,0.0006614235,0.00003591812,0.0007861609],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0114155,"threshold_uncertainty_score":0.0226981,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2277193729","doi":"10.1007/s40534-016-0096-4","title":"Injury severity analysis: comparison of multilevel logistic regression models and effects of collision data aggregation","year":2016,"lang":"en","type":"article","venue":"Journal of Modern Transportation","topic":"Traffic and Road Safety","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"McGill University; University of Waterloo","funders":"","keywords":"Multinomial logistic regression; Collision; Logistic regression; Mixed logit; Statistics; Econometrics; Multilevel model; Computer science; Logit; Multinomial distribution; Mathematics; Computer security","authors":[{"name":"Taimur Usman","is_ca":true},{"name":"Liping Fu","is_ca":true},{"name":"Luis Miranda-Moreno","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03837490287601782,"gpt":0.2986560194257104,"spread":0.2602811165496925,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.07337215,0.001529831,0.002098835,0.003433638,0.0007806278,0.002659692,0.00309057,0.00128768,0.002954493],"category_scores_gemma":[0.2023194,0.0007714516,0.009018033,0.00480446,0.001055343,0.003889038,0.004239231,0.002937041,0.0004484818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002252032,"about_ca_system_score_gemma":0.002625681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01811835,"about_ca_topic_score_gemma":0.01320695,"domain_scores_codex":[0.9036863,0.08147238,0.003230161,0.004799997,0.00547815,0.001333093],"domain_scores_gemma":[0.6224709,0.340665,0.01574595,0.01185872,0.007875513,0.001383893],"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":[0.009130814,0.001736864,0.6662566,0.001670981,0.02022917,0.0005094804,0.005033967,0.1247261,0.001573393,0.01379039,0.003344405,0.1519978],"study_design_scores_gemma":[0.0005955825,0.006588645,0.3040955,0.000651802,0.007766658,0.0003380413,0.003457966,0.6596882,0.001858221,0.01073862,0.003882077,0.0003387072],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8425058,0.002340712,0.1466472,0.001854557,0.0001806946,0.00113146,0.001543852,0.0005683603,0.003227397],"genre_scores_gemma":[0.9428432,0.0007004333,0.05355643,0.0001448376,0.00007029095,0.0009219851,0.000928369,0.0001490077,0.0006854614],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07337215,"threshold_uncertainty_score":0.3880336,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2063254307","doi":"10.1007/s40534-013-0008-9","title":"Evaluation of alternative criteria for determining the optimal location of RWIS stations","year":2013,"lang":"en","type":"article","venue":"Journal of Modern Transportation","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Set (abstract data type); Process (computing); Grid; Operations research; Geography","authors":[{"name":"Tae J. Kwon","is_ca":true},{"name":"Liping Fu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03900888496326321,"gpt":0.3030561287850885,"spread":0.2640472438218253,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008797889,0.001444862,0.001668198,0.006289825,0.0008762384,0.003010266,0.002041039,0.001420981,0.002368913],"category_scores_gemma":[0.02304158,0.0007180473,0.001173294,0.003746074,0.001179582,0.002090762,0.001786156,0.000745594,0.000182141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003783502,"about_ca_system_score_gemma":0.004084326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0124488,"about_ca_topic_score_gemma":0.01541754,"domain_scores_codex":[0.9941804,0.002831746,0.0003832815,0.000455869,0.001722843,0.0004258728],"domain_scores_gemma":[0.9899783,0.00620439,0.001047098,0.0002886901,0.00220708,0.0002743278],"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":[0.0001158353,0.00007504828,0.004246357,0.0002319184,0.00009726318,0.00008649397,0.0001678705,0.932866,0.0009081861,0.01580656,0.0004198326,0.04497865],"study_design_scores_gemma":[0.00003318582,0.0001653284,0.001358557,0.00005671561,0.00004589253,0.00003727284,0.000270044,0.9912741,0.001029485,0.004914301,0.0007857038,0.0000294251],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1002017,0.0004971381,0.8926253,0.0002267374,0.00002443329,0.0004755848,0.000300388,0.0001409121,0.00550787],"genre_scores_gemma":[0.5986723,0.0002752127,0.399285,0.00003066906,0.00001718711,0.0004346406,0.0003088125,0.00004734785,0.0009287713],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0124488,"threshold_uncertainty_score":0.04652822,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1996849344","doi":"10.1007/s40534-013-0005-z","title":"Road traffic congestion measurement considering impacts on travelers","year":2013,"lang":"en","type":"article","venue":"Journal of Modern Transportation","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Ministry of Transportation of Ontario","funders":"National Natural Science Foundation of China","keywords":"Traffic congestion; Transport engineering; Feeling; Regression analysis; Variables; Logit; Econometrics; Statistics; Economics; Engineering; Psychology; Mathematics; Social psychology","authors":[{"name":"Liang Ye","is_ca":true},{"name":"Ying Hui","is_ca":false},{"name":"Dongyuan Yang","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04366804696731401,"gpt":0.2739622429850059,"spread":0.2302941960176919,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009033431,0.0004430282,0.0002470802,0.001397144,0.0002596564,0.0007394261,0.0002405823,0.0002327729,0.001667142],"category_scores_gemma":[0.003039308,0.0001222896,0.0004253665,0.001863341,0.0002321621,0.00106227,0.0005181595,0.0002697154,0.0001098787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004576101,"about_ca_system_score_gemma":0.0003485682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004900353,"about_ca_topic_score_gemma":0.005824257,"domain_scores_codex":[0.999106,0.000313716,0.00006994093,0.00009556036,0.0003188959,0.00009600814],"domain_scores_gemma":[0.9989526,0.000269098,0.0002482044,0.0000461908,0.0004037513,0.0000801827],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002491791,0.0003393869,0.8638374,0.0003381353,0.0002565171,0.0001710117,0.00116751,0.02958938,0.004071165,0.001633651,0.001181617,0.09716493],"study_design_scores_gemma":[0.000008023131,0.000476825,0.9368215,0.0000465451,0.0001851193,0.0001104324,0.005081268,0.05175126,0.002900301,0.0009980256,0.001555882,0.00006485744],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9844195,0.0001726231,0.01051547,0.00007190279,0.0000190715,0.00006717601,0.0003411546,0.00003355642,0.004359493],"genre_scores_gemma":[0.9981439,0.0000791237,0.001362796,0.000004704537,0.000006062075,0.00002881288,0.0001757436,0.000001983857,0.0001968659],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004900353,"threshold_uncertainty_score":0.00974369,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1820980500","doi":"10.1007/s40534-015-0073-3","title":"Using microscopic video data measures for driver behavior analysis during adverse winter weather: opportunities and challenges","year":2015,"lang":"en","type":"article","venue":"Journal of Modern Transportation","topic":"Traffic and Road Safety","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Waterloo; Polytechnique Montréal; McGill University","funders":"","keywords":"Adverse weather; Crash; Collision; Environmental science; Transport engineering; Weather station; Computer science; Engineering; Meteorology; Geography","authors":[{"name":"Ting Fu","is_ca":true},{"name":"Sohail Zangenehpour","is_ca":true},{"name":"Paul St-Aubin","is_ca":true},{"name":"Liping Fu","is_ca":true},{"name":"Luis Miranda-Moreno","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1730624912072958,"gpt":0.2916771509029646,"spread":0.1186146596956688,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002995118,0.0009986878,0.0007309595,0.002825931,0.0005207026,0.002108817,0.001280486,0.0006290816,0.0006847699],"category_scores_gemma":[0.007714839,0.0003653324,0.0004768767,0.001851965,0.0006148407,0.001559254,0.000618801,0.0006414011,0.0002395169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001091075,"about_ca_system_score_gemma":0.001613592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0333635,"about_ca_topic_score_gemma":0.06420004,"domain_scores_codex":[0.997407,0.0008565386,0.0001738276,0.0003268179,0.001087593,0.0001482087],"domain_scores_gemma":[0.9899595,0.003384863,0.001533636,0.000969725,0.003905535,0.0002466855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003526022,0.0005701844,0.4716407,0.001511521,0.000545503,0.0003099667,0.001964416,0.02409989,0.04130894,0.003363323,0.004259283,0.4500737],"study_design_scores_gemma":[0.00007475208,0.001270318,0.6818853,0.0008320314,0.0004150496,0.0008433728,0.01047779,0.2260983,0.04514893,0.008424182,0.02416556,0.0003644708],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6542218,0.004006598,0.3212687,0.001474377,0.0004188566,0.0008892472,0.003395679,0.001059794,0.01326499],"genre_scores_gemma":[0.8888487,0.001900962,0.1065465,0.0001865874,0.0001270236,0.0002910372,0.001030164,0.00007875752,0.0009902606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0333635,"threshold_uncertainty_score":0.0663386,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1904545932","doi":"10.1007/s40534-015-0082-2","title":"Analysis and modeling of highway truck traffic volume variations during severe winter weather conditions in Canada","year":2015,"lang":"en","type":"article","venue":"Journal of Modern Transportation","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada; University of Regina","keywords":"Truck; Snow; Environmental science; Trailer; Traffic volume; Meteorology; Transport engineering; Regression analysis; Cold weather; Geography; Engineering; Statistics; Mathematics; Automotive engineering","authors":[{"name":"Hyuk-Jae Roh","is_ca":true},{"name":"Satish C. Sharma","is_ca":true},{"name":"Prasanta K. Sahu","is_ca":false},{"name":"Sandeep Datla","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.00992629501360899,"gpt":0.2016660750472407,"spread":0.1917397800336317,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003829178,0.0006401184,0.0004293002,0.0007533948,0.0008741486,0.001169953,0.001210392,0.0004934879,0.0008514422],"category_scores_gemma":[0.001024544,0.0003795965,0.0005186111,0.001047341,0.0004645896,0.0003053227,0.0003636034,0.0003895452,0.0001050671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009510234,"about_ca_system_score_gemma":0.00742613,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9712133,"about_ca_topic_score_gemma":0.9517299,"domain_scores_codex":[0.9997483,0.000022664,0.000008755818,0.00005671859,0.00006295527,0.0001006616],"domain_scores_gemma":[0.9996428,0.00009852715,0.00004407096,0.00001254988,0.0001641976,0.00003776627],"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":[0.00008276761,0.00006272869,0.07529804,0.00002332262,0.00004048779,0.0001263051,0.0001031658,0.9169198,0.001071214,0.0006631947,0.000628285,0.004980681],"study_design_scores_gemma":[0.00000527475,0.00001459144,0.03423415,0.00000276274,0.0000110857,0.00001306208,0.0001467903,0.9648802,0.0002176187,0.0001064178,0.0003561937,0.00001173611],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947346,0.00007367577,0.002357129,0.00005496159,0.000006300966,0.00002247211,0.001085311,0.00006598594,0.001599524],"genre_scores_gemma":[0.9969447,0.00006730614,0.0008442718,0.00000687411,0.000002113341,0.00001069241,0.0009745401,0.00001213678,0.001137387],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02878672,"threshold_uncertainty_score":0.06900191,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2607394547","doi":"10.1007/s40534-017-0128-8","title":"A modern congestion pricing policy for urban traffic: subsidy plus toll","year":2017,"lang":"en","type":"article","venue":"Journal of Modern Transportation","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Toll; Subsidy; Road pricing; Equity (law); Congestion pricing; Business; Traffic congestion; Transport engineering; Profit (economics); Economics; Public economics; Computer science; Operations research; Microeconomics; Engineering; Political science; Market economy","authors":[{"name":"Saeed Asadi Bagloee","is_ca":false},{"name":"Majid Sarvi","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03536838524781753,"gpt":0.3285264594862877,"spread":0.2931580742384702,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008736295,0.0005193346,0.0006200428,0.0006999567,0.0006501754,0.00159257,0.001290709,0.001458132,0.003755067],"category_scores_gemma":[0.002785145,0.0002144041,0.0005560883,0.002138849,0.000608111,0.001589836,0.0005722201,0.001556351,0.0005658128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00296525,"about_ca_system_score_gemma":0.002433609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07032979,"about_ca_topic_score_gemma":0.0859912,"domain_scores_codex":[0.9990121,0.0003603565,0.00003805588,0.0002844596,0.0001672566,0.0001377078],"domain_scores_gemma":[0.9994146,0.0001903978,0.00007766562,0.0001128858,0.0001450935,0.00005936431],"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":[0.0006272248,0.0008071222,0.03004227,0.0009601981,0.0002019689,0.0003358412,0.0002683463,0.4913658,0.002968354,0.06824925,0.1370559,0.2671178],"study_design_scores_gemma":[0.0002280601,0.0002198162,0.02548949,0.00008262238,0.00008864723,0.0002067445,0.0004020974,0.8508974,0.001779107,0.03648937,0.0840316,0.00008504129],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4897675,0.003465026,0.3974588,0.01459628,0.001096038,0.001282736,0.04049292,0.004037654,0.04780307],"genre_scores_gemma":[0.9038017,0.0006604517,0.08021248,0.0005337158,0.0001486577,0.0002983201,0.009605406,0.00009156054,0.004647662],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07032979,"threshold_uncertainty_score":0.1398408,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2136575324","doi":"10.1007/s40534-015-0072-4","title":"Performance-based intersection layout under a flyover for heterogeneous traffic","year":2015,"lang":"en","type":"article","venue":"Journal of Modern Transportation","topic":"Traffic control and management","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Regina","funders":"Indian Institute of Technology Guwahati; Indian Institute of Technology Bombay","keywords":"Intersection (aeronautics); Queue; Microsimulation; Traffic flow (computer networking); Sensitivity (control systems); Computer science; Traffic volume; Transport engineering; Simulation; Engineering; Real-time computing; Computer network; Electronic engineering","authors":[{"name":"Avijit Maji","is_ca":false},{"name":"Akhilesh Kumar Maurya","is_ca":false},{"name":"Suresh Nama","is_ca":false},{"name":"Prasanta K. Sahu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01917319393994791,"gpt":0.2096399389598246,"spread":0.1904667450198767,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002514521,0.0005684594,0.0004003175,0.0005466702,0.0006391482,0.001165308,0.000983417,0.000448723,0.00412791],"category_scores_gemma":[0.0006014018,0.0001993794,0.0003691034,0.0005307194,0.0003883718,0.0007711855,0.0006089917,0.0003333601,0.0004739833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001430173,"about_ca_system_score_gemma":0.00148385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01202954,"about_ca_topic_score_gemma":0.01556451,"domain_scores_codex":[0.9996488,0.00006276892,0.00001356624,0.00007254747,0.00008071765,0.000121618],"domain_scores_gemma":[0.9996244,0.00006740112,0.0000777149,0.00005441174,0.0001168456,0.00005914167],"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":[0.0002596785,0.0001517316,0.008171542,0.00006569661,0.00003257755,0.0003189617,0.0001056156,0.944234,0.01929369,0.003869382,0.00109217,0.022405],"study_design_scores_gemma":[0.00004340414,0.0005899837,0.009916239,0.00001895749,0.00006951603,0.0001961453,0.0003906522,0.9729624,0.01099014,0.002060864,0.002701379,0.00006032693],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7707439,0.0002680916,0.210351,0.0001555897,0.00006265361,0.0001788734,0.0007502054,0.002261125,0.01522856],"genre_scores_gemma":[0.9866489,0.00006940325,0.01160101,0.00000674827,0.000003384436,0.00002781877,0.0002061925,0.00002097349,0.001415627],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01202954,"threshold_uncertainty_score":0.02391905,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2956059769","doi":"10.1007/s40534-019-0190-5","title":"Case study scenarios in site selection of hazardous material facilities based on transportation preferences","year":2019,"lang":"en","type":"article","venue":"Journal of Modern Transportation","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Regina; University of Manitoba","funders":"","keywords":"Hazardous waste; Site selection; Transport engineering; Facility location problem; Flow network; Rank (graph theory); Computer science; Selection (genetic algorithm); Function (biology); Set (abstract data type); Operations research; Engineering; Artificial intelligence; Mathematics; Mathematical optimization","authors":[{"name":"Babak Mehran","is_ca":true},{"name":"Musharraf Ahmad Khan","is_ca":true},{"name":"Mina Mehran","is_ca":true},{"name":"Hyuk-Jae Roh","is_ca":true},{"name":"Satish C. Sharma","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0510034346571668,"gpt":0.3142449782630256,"spread":0.2632415436058588,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003036621,0.001249074,0.0006063848,0.002011777,0.00124962,0.001662467,0.002013407,0.001896167,0.003175865],"category_scores_gemma":[0.004396378,0.0004309319,0.001163619,0.002865617,0.0008963486,0.001137567,0.001207999,0.0007257796,0.0002027492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004132873,"about_ca_system_score_gemma":0.002371879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02566839,"about_ca_topic_score_gemma":0.04905603,"domain_scores_codex":[0.9970369,0.001732484,0.0001037851,0.0002101431,0.000537182,0.000379514],"domain_scores_gemma":[0.9954093,0.003091973,0.0003258381,0.0001767924,0.0006475098,0.0003485507],"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":[0.0008310763,0.001064066,0.04017353,0.0004101406,0.000243893,0.006075128,0.0007534926,0.8895659,0.005021524,0.02247779,0.003037859,0.03034561],"study_design_scores_gemma":[0.0001557534,0.0006755305,0.01142304,0.00006898504,0.0001225186,0.0008067118,0.004326731,0.966271,0.005518166,0.007213823,0.003336465,0.00008130835],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.858268,0.0002484025,0.1207075,0.0004074723,0.00003912919,0.001860675,0.001656432,0.0001171354,0.01669546],"genre_scores_gemma":[0.9147779,0.0001524434,0.08178263,0.00003116872,0.000007148514,0.0005409383,0.0005346734,0.00001165662,0.002161409],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02566839,"threshold_uncertainty_score":0.05103797,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2938098978","doi":"10.1007/s40534-019-0187-0","title":"Event management architecture for the monitoring and diagnosis of a fleet of trains: a case study","year":2019,"lang":"en","type":"article","venue":"Journal of Modern Transportation","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Bombardier (Canada)","funders":"Centre National de la Recherche Scientifique","keywords":"Train; Architecture; Event (particle physics); Key (lock); Fleet management; Asynchronous communication; Computer science; Systems architecture; Systems engineering; Event management; Operations research; Management system; Engineering; Telecommunications; Operations management; Computer security","authors":[{"name":"Adoum Fadil","is_ca":true},{"name":"Damien Trentesaux","is_ca":false},{"name":"Guillaume Branger","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01499920374885197,"gpt":0.2701996423248611,"spread":0.2552004385760091,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001251704,0.000420992,0.0003161827,0.0005806598,0.0006480733,0.001059654,0.0009986588,0.001464613,0.001422273],"category_scores_gemma":[0.002319206,0.0001778314,0.0004046624,0.0006166215,0.0006334145,0.001045038,0.0007544865,0.000680955,0.000182562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001207347,"about_ca_system_score_gemma":0.0006858667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006996103,"about_ca_topic_score_gemma":0.00548373,"domain_scores_codex":[0.9991026,0.0003821043,0.00006737994,0.0001347702,0.0002021716,0.0001110287],"domain_scores_gemma":[0.9987317,0.0007447115,0.00009497671,0.0001533031,0.0001724344,0.0001029517],"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":[0.001503414,0.001501602,0.04432039,0.0007651253,0.0001599411,0.01027629,0.003529303,0.6902339,0.03807482,0.02587732,0.004341235,0.1794167],"study_design_scores_gemma":[0.0001469897,0.0006605738,0.01074142,0.00004430761,0.00007177213,0.001156127,0.001661566,0.9498476,0.02042463,0.003445471,0.01176153,0.00003796707],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8130966,0.0002885417,0.1769499,0.0006693292,0.00004568628,0.0005052662,0.0003587574,0.0007823695,0.007303566],"genre_scores_gemma":[0.9523275,0.0001591206,0.0449902,0.00003345978,0.00001394976,0.0001060935,0.0002081354,0.00001753753,0.00214406],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006996103,"threshold_uncertainty_score":0.01391077,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2403195195","doi":"10.1007/s40534-014-0041-3","title":"The influence of Laval nozzle throat size on supersonic molecular beam injection","year":2014,"lang":"en","type":"article","venue":"Journal of Modern Transportation","topic":"Gas Dynamics and Kinetic Theory","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; Southwest Jiaotong University","keywords":"Nozzle; Mach number; Supersonic speed; Throat; Beam (structure); Finite element method; Mechanics; Physics; Materials science; Aerospace engineering; Structural engineering; Optics; Engineering; Anatomy; Biology","authors":[{"name":"Xinkui He","is_ca":false},{"name":"Xianfu Feng","is_ca":false},{"name":"Mingmin Zhong","is_ca":false},{"name":"Fujun Gou","is_ca":false},{"name":"Shuiquan Deng","is_ca":false},{"name":"Yong Zhao","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.007510284895393523,"gpt":0.241096066632687,"spread":0.2335857817372935,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004654739,0.0003894865,0.0003929735,0.0003013058,0.0003676826,0.0007626837,0.0004503804,0.0004395146,0.002125805],"category_scores_gemma":[0.002649159,0.000253912,0.0002584831,0.0001181787,0.000529917,0.0007312375,0.0004172597,0.0003259724,0.0001635646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004194023,"about_ca_system_score_gemma":0.0003071844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001029896,"about_ca_topic_score_gemma":0.001111797,"domain_scores_codex":[0.9997519,0.00005128119,0.0000145991,0.00004516646,0.00006600668,0.00007112596],"domain_scores_gemma":[0.9982869,0.001044443,0.0002980689,0.00008157279,0.0001739859,0.0001149422],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001656026,0.0004312574,0.0181727,0.0005808152,0.00009552632,0.001895053,0.0003933847,0.2571828,0.68678,0.005602924,0.0009382316,0.02627134],"study_design_scores_gemma":[0.00009496634,0.001852075,0.03224034,0.00008802649,0.0002258798,0.0003648245,0.0004498099,0.439303,0.5211371,0.0008638377,0.003245796,0.0001343544],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9812797,0.0007863487,0.01173431,0.0001015922,0.00007433539,0.00002266656,0.0001035134,0.0001978096,0.005699835],"genre_scores_gemma":[0.9981819,0.0001450095,0.001380692,0.00001101477,0.000004935002,0.000005470312,0.00002375656,0.00002283374,0.000224373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002125805,"threshold_uncertainty_score":0.00711149,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2589054564","doi":"10.1007/s40534-016-0121-7","title":"Identifying Achilles-heel roads in real-sized networks","year":2017,"lang":"en","type":"article","venue":"Journal of Modern Transportation","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Closure (psychology); Heel; Index (typography); Transport engineering; Process (computing); Computer science; Engineering; Economics","authors":[{"name":"Saeed Asadi Bagloee","is_ca":false},{"name":"Majid Sarvi","is_ca":false},{"name":"Russell G. Thompson‬‬","is_ca":false},{"name":"Abbas Rajabifard","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04034162213689606,"gpt":0.3374833895946778,"spread":0.2971417674577817,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002993774,0.0008959729,0.0008819237,0.004934828,0.001415389,0.002649666,0.001959332,0.001694414,0.001291525],"category_scores_gemma":[0.01405805,0.0006262909,0.0006196264,0.002645866,0.001437849,0.00392738,0.001869481,0.0009029962,0.0002441921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001875144,"about_ca_system_score_gemma":0.00110732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01080543,"about_ca_topic_score_gemma":0.01379055,"domain_scores_codex":[0.9977419,0.0007726552,0.0001393322,0.0006048142,0.0003675755,0.0003738056],"domain_scores_gemma":[0.9881243,0.00656159,0.002524132,0.0007948206,0.001369366,0.0006259214],"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":[0.0003782187,0.0001872684,0.08581775,0.0002817019,0.0001240359,0.001056734,0.0008860892,0.8373168,0.003412696,0.01459313,0.001424529,0.05452115],"study_design_scores_gemma":[0.000007020476,0.0000811177,0.01095274,0.0000313536,0.00002355139,0.0001964759,0.0008668614,0.9747251,0.001487819,0.01071111,0.0008925879,0.00002429751],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6886131,0.000636088,0.3063113,0.0003046411,0.00003611556,0.0003141371,0.0007758496,0.0004168777,0.002591911],"genre_scores_gemma":[0.937635,0.0001960792,0.06050628,0.00003138898,0.00002083566,0.00009985383,0.0007077838,0.00003604243,0.0007668248],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01080543,"threshold_uncertainty_score":0.02148509,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2067341699","doi":"10.1007/s40534-014-0063-x","title":"Relative efficiency appraisal of discrete choice modeling algorithms using small-scale maximum likelihood estimator through empirically tailored computing environment","year":2014,"lang":"en","type":"article","venue":"Journal of Modern Transportation","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University; University of Regina","funders":"","keywords":"Hessian matrix; Estimator; Convergence (economics); Flexibility (engineering); Computer science; Algorithm; Discrete choice; Mathematical optimization; Software; Function (biology); Key (lock); Mathematics; Applied mathematics; Statistics; Machine learning","authors":[{"name":"Hyuk-Jae Roh","is_ca":true},{"name":"Prasanta K. Sahu","is_ca":false},{"name":"Ata M. Khan","is_ca":true},{"name":"Satish C. Sharma","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07666892359815522,"gpt":0.2613298995300429,"spread":0.1846609759318877,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01510022,0.0006855041,0.0008670986,0.001337584,0.0004174387,0.001838534,0.001252517,0.0009455763,0.001270924],"category_scores_gemma":[0.08496078,0.0003546179,0.000677879,0.001262374,0.0009853992,0.00220043,0.001525197,0.001229736,0.0002742564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001150539,"about_ca_system_score_gemma":0.001729962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00228512,"about_ca_topic_score_gemma":0.001652126,"domain_scores_codex":[0.9863814,0.01075964,0.0004893854,0.00056033,0.001614291,0.0001950012],"domain_scores_gemma":[0.9209458,0.06962083,0.001931319,0.004555791,0.002643429,0.0003028342],"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":[0.0008214668,0.000450971,0.01055186,0.000477178,0.0001983615,0.0001248123,0.0003459017,0.6534971,0.002879046,0.0804387,0.0009704764,0.2492443],"study_design_scores_gemma":[0.0000348049,0.0001169017,0.0008468151,0.00002895215,0.00002184156,0.00003929232,0.00006058405,0.9869381,0.001480883,0.00997969,0.0004393037,0.00001283718],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08860051,0.000558608,0.9061282,0.0005098108,0.00003232378,0.0001606787,0.00004562664,0.0003746295,0.003589573],"genre_scores_gemma":[0.5229952,0.0004211977,0.4755118,0.00007240282,0.00003085762,0.0002709258,0.000104949,0.000115311,0.0004772879],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01510022,"threshold_uncertainty_score":0.07985848,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2622207138","doi":"10.1007/s40534-017-0133-y","title":"Investigation of the factors affecting the consistency of short-period traffic counts","year":2017,"lang":"en","type":"article","venue":"Journal of Modern Transportation","topic":"Traffic and Road Safety","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Regina","funders":"","keywords":"Environmental science; Statistics; Traffic volume; Sample (material); Snow; Animal science; Geography; Meteorology; Mathematics; Transport engineering; Biology; Engineering","authors":[{"name":"Solomon Yadessa Kenno","is_ca":false},{"name":"Prasanta K. Sahu","is_ca":false},{"name":"Babak Mehran","is_ca":true},{"name":"Satish C. Sharma","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02421919603259089,"gpt":0.2240377844846118,"spread":0.1998185884520209,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00630801,0.0002829374,0.0004540996,0.00154502,0.0005021543,0.001154863,0.001012395,0.0003959583,0.0004213539],"category_scores_gemma":[0.04166251,0.0002505656,0.0002979076,0.002523428,0.0004131463,0.0006572276,0.0003993248,0.0003602461,0.0001527293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001070949,"about_ca_system_score_gemma":0.0009903461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05541202,"about_ca_topic_score_gemma":0.08807853,"domain_scores_codex":[0.994105,0.001427046,0.0007944269,0.0009214933,0.002449918,0.0003020655],"domain_scores_gemma":[0.9374927,0.03416108,0.01241584,0.003578062,0.01192761,0.0004247259],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001533032,0.00003521135,0.9734442,0.00007248178,0.0001066621,0.00008353413,0.000642519,0.001616315,0.002773092,0.00007867996,0.0002087202,0.02078516],"study_design_scores_gemma":[0.000002124654,0.0000717266,0.9936454,0.00001412366,0.00003504374,0.0001602557,0.0004303649,0.003488695,0.001503559,0.00004633301,0.000590278,0.00001216343],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9892419,0.0005151249,0.008146664,0.00004677876,0.00003649643,0.00003883325,0.0005063188,0.00006619645,0.001401796],"genre_scores_gemma":[0.9956673,0.0001214032,0.003060433,0.00001701889,0.00002064024,0.00001642732,0.0007276479,0.00001983321,0.0003491486],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05541202,"threshold_uncertainty_score":0.110179,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}