{"meta":{"query_hash":"e2bcd632a4fe","filters":{"venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board"},"cohort_total":55,"direct_labels_cover":0,"predictions_cover":55,"exported":55,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/e2bcd632a4fe","api":"https://metacan.xera.ac/api/v1/cohort?venue=Transportation+Research+Board+91st+Annual+MeetingTransportation+Research+Board"},"results":[{"id":"W102130764","doi":"","title":"Developing Collision Prediction Models with Weather and Driver Characteristics Related Variables","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Traffic and Road Safety","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Thursday; Collision; Names of the days of the week; Snow; Multinomial logistic regression; Daylight; Statistics; Collision frequency; Demography; Meteorology; Geography; Mathematics; Computer science; Computer security; Physics","score_opus":0.04061907884714777,"score_gpt":0.2995827284703945,"score_spread":0.25896364962324675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W102130764","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97971356,0.00057897955,0.014458705,0.00036030394,0.0002777355,0.0013100203,0.00049745856,0.0006675261,0.002135739],"genre_scores_gemma":[0.98919135,0.002110448,0.006937105,0.000018149123,0.00019312798,0.00026736007,0.00063493376,0.00015547754,0.000492068],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9938499,0.00043649756,0.0009647541,0.000638325,0.0024652022,0.0016453406],"domain_scores_gemma":[0.99672174,0.00056263,0.000097263815,0.00037418745,0.0016003466,0.00064384553],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003701953,0.00043020307,0.00047448697,0.0008700288,0.0008850194,0.00013483792,0.00030954703,0.00043994517,0.00012213373],"category_scores_gemma":[0.00006186971,0.00039238215,0.000084760766,0.0017032132,0.00060357567,0.0016880371,0.000012010279,0.0015251078,0.000055311637],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022474155,0.00066975475,0.677269,0.0026476046,0.00093274564,0.0002013647,0.07723976,0.0959629,0.004556483,0.11999522,0.005303781,0.012974018],"study_design_scores_gemma":[0.0018112799,0.00031678914,0.96548,0.000665519,0.00007720567,0.0000031688642,0.0068124705,0.0103226965,0.0009425284,0.0009880341,0.011905261,0.0006750108],"about_ca_topic_score_codex":0.0006165905,"about_ca_topic_score_gemma":0.0007712099,"teacher_disagreement_score":0.28821108,"about_ca_system_score_codex":0.00028238705,"about_ca_system_score_gemma":0.00025129184,"threshold_uncertainty_score":0.99985284},"labels":[],"label_agreement":null},{"id":"W1265405808","doi":"","title":"Mobility Tool Ownership and Peak Period Non-Work Travel Mode Choice","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"TRIPS architecture; Mode choice; Car ownership; Work (physics); Discrete choice; Context (archaeology); Mode (computer interface); Econometrics; Demographic economics; Population; Preference; Economics; Transport engineering; Geography; Public transport; Microeconomics; Computer science; Engineering; Demography","score_opus":0.08407936181728813,"score_gpt":0.4129384469751384,"score_spread":0.32885908515785023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1265405808","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98581964,0.0006686796,0.00040355633,0.0030259746,0.0003769345,0.0028933228,0.00043208958,0.0002896779,0.0060901465],"genre_scores_gemma":[0.99304754,0.00042545187,0.0010714491,0.00009149109,0.0010137096,0.0006974162,0.0004152535,0.000114474766,0.0031232005],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.98453116,0.0022913734,0.0015820842,0.0015643965,0.006250818,0.0037801408],"domain_scores_gemma":[0.9914191,0.002097649,0.00026072602,0.0008904875,0.0035345873,0.0017974757],"candidate_categories":["metaepi_narrow","sts","research_integrity","insufficient_payload"],"consensus_categories":["sts"],"category_scores_codex":[0.017458638,0.0006095428,0.0008160916,0.0010472741,0.003708542,0.0004928225,0.0011611702,0.0007335288,0.001131958],"category_scores_gemma":[0.0011411414,0.0006104126,0.00036371313,0.0038081177,0.0038121205,0.003124567,0.0000242626,0.0027923628,0.00014976496],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00075632404,0.00077263825,0.90131855,0.00045914343,0.000079893536,0.000033065633,0.08596622,0.00004413459,0.000935213,0.004926881,0.0018380514,0.002869914],"study_design_scores_gemma":[0.0011956823,0.00019115586,0.9405848,0.00018824937,0.000058838847,1.104705e-7,0.037426256,0.000031300147,0.0005162133,0.0009144146,0.018230233,0.00066275016],"about_ca_topic_score_codex":0.06755698,"about_ca_topic_score_gemma":0.08637455,"teacher_disagreement_score":0.048539966,"about_ca_system_score_codex":0.0004562115,"about_ca_system_score_gemma":0.0011429137,"threshold_uncertainty_score":0.99978113},"labels":[],"label_agreement":null},{"id":"W1543474051","doi":"","title":"City of Saskatoon’s Pavement Management System: Network-Level Structural Evaluation","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Pavement management; Road surface; Asset management; Deflection (physics); Engineering; Transport engineering; Forensic engineering; Civil engineering; Business","score_opus":0.0751069237645569,"score_gpt":0.35852371574753245,"score_spread":0.28341679198297554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1543474051","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9862356,0.0008811776,0.0030643067,0.00008875242,0.0013106895,0.0026403237,0.00034739843,0.00035985815,0.0050718696],"genre_scores_gemma":[0.9913172,0.00020887241,0.006147778,0.00001097759,0.00077138917,0.0007126858,0.00046179234,0.00011468454,0.00025460136],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.989497,0.00072367396,0.0014204393,0.00062404864,0.0053669577,0.0023678616],"domain_scores_gemma":[0.995101,0.00036603145,0.00017871395,0.00064888404,0.0031484233,0.00055695546],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.009580263,0.0004660996,0.0005725383,0.0009792097,0.00067162636,0.000098538694,0.0006076609,0.00030520567,0.00029505778],"category_scores_gemma":[0.00005925711,0.00046753144,0.00022979447,0.0019096067,0.00044227592,0.0010437794,0.000021495172,0.0012803461,0.00004819651],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011519699,0.00035365752,0.6580213,0.009887085,0.001456469,0.0001235523,0.033882532,0.1697106,0.009228329,0.05202491,0.020256963,0.043902654],"study_design_scores_gemma":[0.0016393622,0.00022041514,0.96505034,0.00080991973,0.00013639593,8.6660526e-7,0.015632687,0.0029920326,0.0065909564,0.00069123565,0.0056554247,0.00058036135],"about_ca_topic_score_codex":0.0018386297,"about_ca_topic_score_gemma":0.0028942006,"teacher_disagreement_score":0.30702907,"about_ca_system_score_codex":0.0007657213,"about_ca_system_score_gemma":0.00016743987,"threshold_uncertainty_score":0.9997776},"labels":[],"label_agreement":null},{"id":"W159492747","doi":"","title":"Cell Transmission Model-Based Variable Speed Limit Control for Freeways","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Traffic control and management","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Cell Transmission Model; Speed limit; Bottleneck; VisSim; Queue; Traffic flow (computer networking); Queueing theory; Control theory (sociology); Simulation; Model predictive control; Variable (mathematics); Traffic simulation; Traffic congestion; Computer science; Engineering; Microsimulation; Control (management); Mathematics; Transport engineering","score_opus":0.04062069192438035,"score_gpt":0.30987316204122317,"score_spread":0.26925247011684283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W159492747","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31448358,0.002388561,0.6600907,0.0017416012,0.0007209708,0.008134645,0.0020960546,0.0018021382,0.008541747],"genre_scores_gemma":[0.9799142,0.00027750502,0.015852833,0.00011186634,0.00039182135,0.0012709202,0.00074350066,0.0002303213,0.0012070241],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9912981,0.00044893642,0.0012720397,0.00085842086,0.0031368057,0.002985688],"domain_scores_gemma":[0.9945061,0.0014222746,0.00010873473,0.00065750413,0.0021585068,0.0011468554],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.006625787,0.000596348,0.0006986392,0.0012914826,0.0008852916,0.00018449737,0.00076809985,0.0004540382,0.00033463605],"category_scores_gemma":[0.00011227947,0.00061786297,0.00038781634,0.0016000427,0.0003608784,0.0009999186,0.0000064774417,0.0014514884,0.00010545254],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001893477,0.00088365324,0.0038581754,0.0025828227,0.00021045556,0.000021235648,0.00484334,0.91302943,0.026225708,0.00862014,0.031273086,0.0065584807],"study_design_scores_gemma":[0.01755527,0.0012461965,0.06294888,0.0005835203,0.00038674832,3.0730774e-7,0.0043822336,0.67294234,0.011999124,0.002107794,0.22377016,0.00207742],"about_ca_topic_score_codex":0.00091104716,"about_ca_topic_score_gemma":0.00082970335,"teacher_disagreement_score":0.6654306,"about_ca_system_score_codex":0.00029804057,"about_ca_system_score_gemma":0.00038927532,"threshold_uncertainty_score":0.9996273},"labels":[],"label_agreement":null},{"id":"W170792156","doi":"","title":"Investigating Effects of Psychological Factors on Commuting Mode Choice Behavior","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Psychology; Structural equation modeling; Mode (computer interface); Social psychology; Likert scale; Habit; Developmental psychology; Statistics; Mathematics; Computer science","score_opus":0.14621719127992427,"score_gpt":0.47985740293030665,"score_spread":0.3336402116503824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W170792156","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9916985,0.00025375132,0.00008624888,0.00046384824,0.00046495377,0.002550478,0.00023445755,0.00029224332,0.0039555407],"genre_scores_gemma":[0.99689025,0.00013767055,0.0010022211,0.00006909784,0.0005045699,0.00049692293,0.00034677557,0.0000881101,0.00046436192],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9854115,0.0030593032,0.0015341957,0.0010302697,0.006181468,0.0027832515],"domain_scores_gemma":[0.98880184,0.0059724506,0.0004000219,0.0007452014,0.0027161245,0.0013643368],"candidate_categories":["metaepi_narrow","sts","research_integrity"],"consensus_categories":["sts"],"category_scores_codex":[0.009330534,0.0004902021,0.0007441707,0.0011092288,0.002552281,0.0001600196,0.0012511337,0.000631282,0.0004053631],"category_scores_gemma":[0.0025367497,0.00046912822,0.0003841941,0.003155535,0.00312549,0.0015424001,0.000017525268,0.0027570152,0.000060977283],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014682386,0.0013207614,0.93969923,0.00042459002,0.000040822175,0.000017677468,0.045151066,0.000057181333,0.0038165976,0.007515635,0.0005828456,0.0012267831],"study_design_scores_gemma":[0.0009714816,0.0004879996,0.9708957,0.00039563546,0.000059606842,3.0518237e-8,0.017186232,0.000009369862,0.0063143005,0.00061893655,0.0026190197,0.0004416568],"about_ca_topic_score_codex":0.056056093,"about_ca_topic_score_gemma":0.028437773,"teacher_disagreement_score":0.031196514,"about_ca_system_score_codex":0.00031024654,"about_ca_system_score_gemma":0.000408914,"threshold_uncertainty_score":0.99977607},"labels":[],"label_agreement":null},{"id":"W178821265","doi":"","title":"Uses of Social Media in Public Transportation: Summary of Findings from TCRP Synthesis SB-20","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Social media; Staffing; Agency (philosophy); Public relations; Dissemination; Business; Service (business); Public service; Advertising; Internet privacy; Political science; Computer science; Sociology; Marketing; World Wide Web","score_opus":0.08234193365698336,"score_gpt":0.3419716386726636,"score_spread":0.2596297050156803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W178821265","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98928714,0.00051506696,0.00052140246,0.00070979446,0.00036202944,0.0012057694,0.00587962,0.0002929348,0.0012262552],"genre_scores_gemma":[0.99350804,0.00050724647,0.0016932143,0.000019677449,0.00020907413,0.00066317624,0.0031712812,0.0001552881,0.0000729918],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9896622,0.0007339732,0.0029008088,0.00077044836,0.0040188627,0.0019137117],"domain_scores_gemma":[0.99193966,0.003486175,0.00027054778,0.000590391,0.0031397296,0.00057347555],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00516741,0.00056522887,0.0010848248,0.002997992,0.00039731848,0.0000677769,0.0008562786,0.00062786514,0.0011798813],"category_scores_gemma":[0.0005446872,0.0006461304,0.000389577,0.005475771,0.0012624934,0.0018379363,0.0000065915942,0.001749479,0.000044016102],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00092852156,0.0016030634,0.8003939,0.0020442817,0.0004867786,0.0000488406,0.10306818,0.0027411587,0.04171418,0.03873062,0.0048520584,0.0033884265],"study_design_scores_gemma":[0.0013757388,0.00009023516,0.9447576,0.00036178535,0.000081902894,1.1897992e-7,0.01972275,0.00009472974,0.025571233,0.00068045757,0.006717578,0.0005458981],"about_ca_topic_score_codex":0.003519001,"about_ca_topic_score_gemma":0.06119299,"teacher_disagreement_score":0.14436369,"about_ca_system_score_codex":0.00025611828,"about_ca_system_score_gemma":0.0004645456,"threshold_uncertainty_score":0.99973315},"labels":[],"label_agreement":null},{"id":"W201398544","doi":"","title":"Vehice-Pedestrian Accidents at Signalized Intersections: Exposure Measures and Geometric Designs","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Traffic and Road Safety","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Pedestrian; Intersection (aeronautics); Geometric design; Transport engineering; Pedestrian crossing; Negative binomial distribution; Poison control; Computer science; Engineering; Mathematics; Statistics","score_opus":0.08787154282251072,"score_gpt":0.34730947717020083,"score_spread":0.25943793434769014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W201398544","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98819107,0.0038376,0.00300152,0.00030315996,0.0005193818,0.0016228736,0.00028576204,0.00072167796,0.0015169814],"genre_scores_gemma":[0.9942319,0.0026877967,0.00076876796,0.000028720178,0.00033495526,0.0005327736,0.0003631272,0.00017293793,0.00087905664],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9908702,0.0010066382,0.001248117,0.0008198577,0.0037028668,0.002352343],"domain_scores_gemma":[0.99502426,0.0013740992,0.000118342454,0.000543892,0.0017057599,0.0012336355],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0064013274,0.0005554861,0.0006201154,0.0024239651,0.0013647644,0.00019732861,0.0005835562,0.0005217029,0.00058388786],"category_scores_gemma":[0.00037252132,0.0005639447,0.0002422281,0.0035289489,0.00069292606,0.0014260528,0.000025066456,0.0019447971,0.0002674038],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020378458,0.0005142319,0.9234171,0.0012428134,0.0005639214,0.000118715165,0.024618065,0.008234216,0.009661567,0.00062297983,0.014345696,0.014622845],"study_design_scores_gemma":[0.0022185955,0.00038299785,0.9613512,0.00022787263,0.00007737614,0.0000028684665,0.007893754,0.00025896565,0.0032986428,0.0001294011,0.023501983,0.0006563497],"about_ca_topic_score_codex":0.0048273923,"about_ca_topic_score_gemma":0.01925476,"teacher_disagreement_score":0.03793409,"about_ca_system_score_codex":0.0004758276,"about_ca_system_score_gemma":0.00018437301,"threshold_uncertainty_score":0.9999353},"labels":[],"label_agreement":null},{"id":"W2052352752","doi":"","title":"Improving the Efficiency of Dynamic Traffic Assignment Through Computational Methods Based on Combinatorial Algorithm","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Algorithm; Cell Transmission Model; Convergence (economics); Queue; Mathematical optimization; FIFO (computing and electronics); Path (computing); Mathematics; Traffic congestion; Engineering","score_opus":0.05754672257237923,"score_gpt":0.4272030779018701,"score_spread":0.36965635532949087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2052352752","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.52394575,0.00062618026,0.45906797,0.0043913936,0.0019743186,0.004800304,0.0009080235,0.0005450019,0.0037410276],"genre_scores_gemma":[0.94495124,0.00012842314,0.053044047,0.000106928295,0.0002935123,0.0003798599,0.000745829,0.00008335287,0.0002668093],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.98401546,0.0048339884,0.001477286,0.00086214615,0.0068403725,0.0019707277],"domain_scores_gemma":[0.98911726,0.0056430013,0.00047645892,0.0004895136,0.0037070073,0.00056678196],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.020839997,0.00042142769,0.0005463794,0.0009834078,0.002975981,0.00019119811,0.0008960927,0.00043239264,0.00036255477],"category_scores_gemma":[0.0009014479,0.00037742706,0.00032294745,0.0035923126,0.0021809614,0.0010501433,0.000008968347,0.0017249079,0.00004741687],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025743213,0.0050331806,0.030188795,0.0008866353,0.0003287182,0.00005536525,0.2833904,0.47932163,0.0014704226,0.09952695,0.0034709042,0.09375267],"study_design_scores_gemma":[0.012082035,0.0036694391,0.5282292,0.0013675429,0.00043786285,8.1218343e-7,0.15916845,0.2318724,0.004556495,0.0068387827,0.04885648,0.0029205165],"about_ca_topic_score_codex":0.009716959,"about_ca_topic_score_gemma":0.002516714,"teacher_disagreement_score":0.4980404,"about_ca_system_score_codex":0.00044885793,"about_ca_system_score_gemma":0.0014174622,"threshold_uncertainty_score":0.99986774},"labels":[],"label_agreement":null},{"id":"W2215616635","doi":"","title":"Analysis of Injury Severity Outcomes of Highway Winter Crashes: A Multi-level Modeling Approach","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Traffic and Road Safety","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Multinomial logistic regression; Collision; Road surface; Multilevel model; Transport engineering; Speed limit; Visibility; Poison control; Logistic regression; Traffic volume; Statistics; Environmental science; Meteorology; Computer science; Geography; Engineering; Mathematics; Medicine; Computer security","score_opus":0.09210248970115419,"score_gpt":0.36459689995488553,"score_spread":0.27249441025373133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2215616635","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9569736,0.0003730122,0.038361788,0.00008608824,0.00018911857,0.0010251349,0.0019868067,0.0002953915,0.00070904027],"genre_scores_gemma":[0.9895648,0.00038096868,0.00873666,0.0000113526485,0.00007943612,0.00021497469,0.00064667687,0.00011622456,0.00024892695],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9914459,0.0006485564,0.0019465412,0.00069056754,0.0035525141,0.0017159019],"domain_scores_gemma":[0.9949686,0.00068582525,0.00019099997,0.00075547525,0.0027704479,0.00062867434],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.005837946,0.0004959173,0.0012438027,0.0029853717,0.0003408556,0.000042568034,0.00076999154,0.0004572202,0.00022257566],"category_scores_gemma":[0.00018979165,0.00047318844,0.000678337,0.0047399765,0.00070168293,0.0009789853,0.000019701773,0.0015249695,0.000023537152],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005550262,0.001074468,0.73562866,0.0013051298,0.0025203687,0.00000775695,0.024037631,0.22821414,0.002855824,0.001035236,0.00051471655,0.0022510067],"study_design_scores_gemma":[0.0009566828,0.00012725641,0.9150209,0.00011889891,0.0003903237,1.03055626e-7,0.008501847,0.07206756,0.0020064537,0.000028865974,0.00032770715,0.00045341506],"about_ca_topic_score_codex":0.0039103804,"about_ca_topic_score_gemma":0.00450723,"teacher_disagreement_score":0.1793922,"about_ca_system_score_codex":0.00018007032,"about_ca_system_score_gemma":0.000205478,"threshold_uncertainty_score":0.99977195},"labels":[],"label_agreement":null},{"id":"W2577979035","doi":"","title":"Cement Stabilization of Conventional Granular Base and Recycled Crushed Portland Cement Concrete","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Asphalt Pavement Performance Evaluation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Compaction; Base course; Portland cement; Crushed stone; Cement; Granular material; Aggregate (composite); Geotechnical engineering; Subgrade; Environmental science; Drainage; California bearing ratio; Materials science; Waste management; Geology; Engineering; Composite material; Asphalt","score_opus":0.0672240637425136,"score_gpt":0.35650017118542876,"score_spread":0.28927610744291515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2577979035","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9895322,0.0010179551,0.005406303,0.0002517687,0.00027437272,0.0018207508,0.0005503008,0.00021369774,0.00093266927],"genre_scores_gemma":[0.99362046,0.0014814133,0.0018570893,0.000025482668,0.00018502856,0.00056764344,0.001968245,0.00010248225,0.00019214617],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9914744,0.00071750156,0.0015520222,0.0006054818,0.0042053373,0.0014452556],"domain_scores_gemma":[0.99564826,0.00055414985,0.00021221554,0.00044936012,0.0025131472,0.0006228638],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007816579,0.0004050818,0.000515512,0.0011835182,0.0005064309,0.0000796703,0.00031599886,0.0002637764,0.0010389655],"category_scores_gemma":[0.0001556539,0.00043827097,0.00014764149,0.0014680991,0.0006330351,0.0014434302,0.000015494901,0.0007893424,0.000040368817],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013430704,0.00039197417,0.89140224,0.0030814738,0.0003949596,0.000026882928,0.013767751,0.007261906,0.056962714,0.013356193,0.00592665,0.0060841707],"study_design_scores_gemma":[0.00508006,0.0008396588,0.9097938,0.0005621439,0.00014937083,7.6372766e-7,0.008381593,0.013144857,0.047631785,0.0008532505,0.012684824,0.00087788224],"about_ca_topic_score_codex":0.0014570245,"about_ca_topic_score_gemma":0.0014183861,"teacher_disagreement_score":0.018391557,"about_ca_system_score_codex":0.00028769698,"about_ca_system_score_gemma":0.00021884868,"threshold_uncertainty_score":0.99987423},"labels":[],"label_agreement":null},{"id":"W2890856151","doi":"","title":"Bus Rapid Transit and Economic Development Case Study of the Eugene-Springfield, Oregon, BRT System","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Metropolitan area; Bus rapid transit; Recreation; Quarter (Canadian coin); Transport engineering; Business; Public transport; Regional science; Geography; Economic growth; Engineering; Political science; Economics","score_opus":0.08634956768781636,"score_gpt":0.3890055455929229,"score_spread":0.3026559779051065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890856151","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9935597,0.00059677765,0.000079790065,0.00047956643,0.0004187976,0.0032440668,0.00014027022,0.00015239758,0.0013285907],"genre_scores_gemma":[0.99826664,0.00013824868,0.00042117378,0.000016240461,0.00031005742,0.0003959295,0.00004218242,0.00006314556,0.00034641157],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99005103,0.0020788638,0.0016349313,0.0009279874,0.003483893,0.0018232879],"domain_scores_gemma":[0.9953094,0.00089212094,0.00030866638,0.0007003495,0.0019611835,0.0008282864],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.012863798,0.00039303544,0.0006147347,0.0006976113,0.0031815106,0.00017201118,0.0009041013,0.0003565737,0.00027056487],"category_scores_gemma":[0.00014862952,0.00034273483,0.00020496368,0.0016136998,0.0015498634,0.0011663537,0.000023625378,0.0013452639,0.000027459997],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003275386,0.0006667385,0.78707874,0.00050058804,0.00013510144,0.00017620836,0.20429988,0.000098832614,0.00021602582,0.0023573942,0.00022136011,0.0039216033],"study_design_scores_gemma":[0.0012881196,0.00021364164,0.7102337,0.00016353918,0.00006989313,0.0000017183626,0.27882564,0.000016507716,0.0012000301,0.000035455334,0.0076085553,0.00034323055],"about_ca_topic_score_codex":0.118382744,"about_ca_topic_score_gemma":0.37980148,"teacher_disagreement_score":0.26141873,"about_ca_system_score_codex":0.0004275229,"about_ca_system_score_gemma":0.0012346144,"threshold_uncertainty_score":0.9999025},"labels":[],"label_agreement":null},{"id":"W298825548","doi":"","title":"Metropolitan Transportation Governance Institutions: International Experience for Metropolitan Areas in Developing Countries","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Metropolitan area; Stakeholder; Scope (computer science); Business; Corporate governance; Environmental planning; Regional science; Finance; Political science; Geography; Public relations; Computer science","score_opus":0.11626910486950391,"score_gpt":0.4516876439799556,"score_spread":0.33541853911045166,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W298825548","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9735722,0.0011854818,0.0037182516,0.008186895,0.0011285505,0.003323166,0.001627601,0.0002954591,0.0069624176],"genre_scores_gemma":[0.98756415,0.002276634,0.0051459675,0.00021447624,0.0008108281,0.0018176254,0.0011720048,0.000089980196,0.0009083423],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9871195,0.0010791462,0.0019238378,0.0012741573,0.0054571084,0.0031462263],"domain_scores_gemma":[0.9918746,0.0016720159,0.00037030573,0.00056010165,0.0046137944,0.00090919016],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":["sts"],"category_scores_codex":[0.010258518,0.0005269558,0.0006971784,0.00149158,0.0025269485,0.00035305688,0.001437131,0.00052572845,0.0006394138],"category_scores_gemma":[0.0011178105,0.00058020983,0.00034750687,0.0037741454,0.0028082805,0.004603396,0.000010608527,0.0013275376,0.000063074694],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000634077,0.00032980493,0.5967586,0.0002212886,0.00005779809,0.000021972055,0.0381598,0.00004525165,0.00010675701,0.36221763,0.0010248302,0.00042217225],"study_design_scores_gemma":[0.0012986738,0.000105569095,0.6911891,0.00027870372,0.000028437802,7.003241e-8,0.07586477,0.00001721159,0.0008465054,0.0024383292,0.22740138,0.0005312631],"about_ca_topic_score_codex":0.099482864,"about_ca_topic_score_gemma":0.34523022,"teacher_disagreement_score":0.3597793,"about_ca_system_score_codex":0.0038729487,"about_ca_system_score_gemma":0.0021182168,"threshold_uncertainty_score":0.999951},"labels":[],"label_agreement":null},{"id":"W3022309789","doi":"","title":"Analysis of GHG Emissions for city passenger trains: is electricity an obvious option for Montreal commuter trains?","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Railway Systems and Energy Efficiency","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Concordia University; McGill University","funders":"","keywords":"Train; Electrification; Electricity; Greenhouse gas; Diesel fuel; Renewable energy; Environmental science; Capital cost; Transport engineering; Engineering; Automotive engineering; Electrical engineering","score_opus":0.07924191067854185,"score_gpt":0.37657152650990966,"score_spread":0.2973296158313678,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3022309789","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95487976,0.00045204087,0.037905294,0.00028824442,0.00022000753,0.0024832876,0.002931931,0.0002999784,0.0005394292],"genre_scores_gemma":[0.99191076,0.00032708648,0.0032358414,0.000031655843,0.0003210033,0.0015485298,0.0021025178,0.00013475299,0.00038786384],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99248147,0.000535478,0.0015876512,0.00079283083,0.00245164,0.0021509228],"domain_scores_gemma":[0.9934692,0.0014279794,0.00020081284,0.0007094636,0.00330326,0.00088931696],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0071164374,0.00048054126,0.0009563725,0.0023971824,0.00087491097,0.00011745623,0.0006714268,0.000512914,0.00016530878],"category_scores_gemma":[0.00025019574,0.0004829262,0.0006994828,0.0039112037,0.00038486542,0.0011222413,0.000006063471,0.0009048659,0.000005717769],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0053172545,0.006028157,0.25243273,0.0063212174,0.0074566356,0.000035798723,0.21957217,0.28217164,0.11213264,0.022739254,0.023663675,0.06212883],"study_design_scores_gemma":[0.0029806413,0.0013462269,0.85573757,0.0002077787,0.00077071064,4.0350164e-7,0.011659122,0.09858724,0.011845367,0.0006166022,0.01519969,0.0010486302],"about_ca_topic_score_codex":0.007418609,"about_ca_topic_score_gemma":0.019250348,"teacher_disagreement_score":0.60330486,"about_ca_system_score_codex":0.0002513044,"about_ca_system_score_gemma":0.00023599845,"threshold_uncertainty_score":0.99976224},"labels":[],"label_agreement":null},{"id":"W3024259511","doi":"","title":"Joint Modelling of Propensity and Distance for Walking Trip Generation","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"TRIPS architecture; Econometric model; Baseline (sea); Econometrics; Work (physics); Trip generation; Travel behavior; Preferred walking speed; Distance decay; Economics; Transport engineering; Computer science; Engineering; Physical medicine and rehabilitation","score_opus":0.2905167700668444,"score_gpt":0.4129203287131816,"score_spread":0.12240355864633717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3024259511","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96624845,0.0009896056,0.02714107,0.00094460684,0.00024819802,0.0029476662,0.00036164685,0.000116873794,0.0010018537],"genre_scores_gemma":[0.99131525,0.0005994181,0.0058458974,0.000024910421,0.00063728873,0.0004443248,0.00035648746,0.0000604774,0.0007159507],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9915304,0.0011857945,0.00129315,0.0008390617,0.0033434422,0.0018081418],"domain_scores_gemma":[0.99323887,0.00096027984,0.0002997379,0.00040230813,0.004383007,0.0007158279],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.016310807,0.00030485407,0.00059479236,0.000710279,0.0021569077,0.00016864657,0.0004384062,0.00034360372,0.00014054857],"category_scores_gemma":[0.00051547424,0.0003099434,0.00022630954,0.0015495718,0.0016931304,0.0019087186,0.000009940807,0.0009177776,0.000007971444],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014287567,0.0008514912,0.803009,0.0015086143,0.00012897365,0.000011978292,0.11614618,0.0012731926,0.0086557595,0.05779166,0.0015485171,0.007645918],"study_design_scores_gemma":[0.0025848108,0.00051727117,0.9173465,0.0004843867,0.00012459634,9.8370116e-8,0.031527422,0.0022650792,0.012808361,0.0049645356,0.02646289,0.00091405207],"about_ca_topic_score_codex":0.020573698,"about_ca_topic_score_gemma":0.03911187,"teacher_disagreement_score":0.11433753,"about_ca_system_score_codex":0.0002094562,"about_ca_system_score_gemma":0.000593941,"threshold_uncertainty_score":0.99993527},"labels":[],"label_agreement":null},{"id":"W309430217","doi":"","title":"Weather or Not to Walk: The Effect of Weather and Temporal Trends During Temperate and Winter on Sidewalk Pedestrian Volumes in Montreal, Canada","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Precipitation; Environmental science; Temperate climate; Pedestrian; Geography; Morning; Climatology; Meteorology; Medicine; Ecology","score_opus":0.03860598780502542,"score_gpt":0.3721654118484054,"score_spread":0.33355942404337996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W309430217","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99298763,0.00021234376,0.0000035162902,0.0037118169,0.00011882859,0.0014968856,0.00027182442,0.00004650709,0.0011506202],"genre_scores_gemma":[0.99453074,0.00017437544,0.00005051991,0.000059587157,0.00020300953,0.00025786905,0.00005397733,0.000053991807,0.004615912],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9917746,0.0018570975,0.00094640837,0.00077529997,0.0030419913,0.0016046136],"domain_scores_gemma":[0.99629235,0.0017022799,0.00014704638,0.00041309194,0.00067880267,0.00076644885],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00820694,0.00037155498,0.0005885404,0.0008473049,0.0011283332,0.00015655792,0.00051638525,0.00023564967,0.00046804798],"category_scores_gemma":[0.00045521779,0.00026675232,0.00011056131,0.0020067738,0.0011057219,0.0007398725,0.000015157226,0.0010833284,0.000008414688],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0038872845,0.00011481896,0.9545276,0.00026316656,0.00004645587,0.000048921236,0.035930958,0.00003448499,0.00059038744,0.00011282871,0.000734026,0.0037090685],"study_design_scores_gemma":[0.0014900166,0.0005785917,0.9759224,0.0002391951,0.0000271606,1.3104629e-7,0.016113423,0.000009453428,0.0021256118,0.00003118601,0.0031812054,0.00028159327],"about_ca_topic_score_codex":0.8696462,"about_ca_topic_score_gemma":0.9884106,"teacher_disagreement_score":0.118764386,"about_ca_system_score_codex":0.00025301627,"about_ca_system_score_gemma":0.0005627043,"threshold_uncertainty_score":0.9999785},"labels":[],"label_agreement":null},{"id":"W3146347962","doi":"","title":"Inconsistencies in Associations Between Crime and Walking: A Reflection of Poverty and Density","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Poverty; Demographic economics; Census; Survey data collection; Demography; General Social Survey; Poison control; Human factors and ergonomics; Perception; Psychology; Economics; Environmental health; Social psychology; Sociology; Medicine; Economic growth; Statistics; Population","score_opus":0.15712712383348904,"score_gpt":0.45702582547365617,"score_spread":0.29989870164016713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3146347962","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9928435,0.00044420155,0.0001442894,0.0016820185,0.00009878076,0.0008612447,0.00030478902,0.00006214022,0.0035590143],"genre_scores_gemma":[0.99782354,0.000621988,0.0005882675,0.000034456218,0.00017125327,0.00009169032,0.00014593589,0.00002841009,0.0004944548],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9934171,0.0017985937,0.0009399974,0.00049419986,0.0022041972,0.0011459384],"domain_scores_gemma":[0.9954944,0.001596937,0.00020233408,0.00021713488,0.0020126873,0.00047645322],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011445341,0.00019474773,0.00043442578,0.001211923,0.0011849878,0.00012044619,0.0002319832,0.00028817824,0.00020739064],"category_scores_gemma":[0.0010813114,0.00021153377,0.00012208348,0.0016999857,0.0011426763,0.0011767107,0.000019460944,0.00097357406,0.000010713165],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000084819025,0.00019596478,0.9339661,0.00014122261,0.000044361142,0.0000044392605,0.049324162,0.0000024354126,0.0012028834,0.012333047,0.00081525126,0.0018852872],"study_design_scores_gemma":[0.0005376675,0.0001688786,0.9598755,0.00018399266,0.000032059044,1.07376266e-7,0.032443892,0.0000052122823,0.0010896603,0.0016803233,0.0037934517,0.00018921621],"about_ca_topic_score_codex":0.09615609,"about_ca_topic_score_gemma":0.13667987,"teacher_disagreement_score":0.04052378,"about_ca_system_score_codex":0.0002567508,"about_ca_system_score_gemma":0.00029736938,"threshold_uncertainty_score":0.9114088},"labels":[],"label_agreement":null},{"id":"W561002847","doi":"","title":"Sustainability of Using Crushed Reclaimed Asphalt Pavement (RAP) and Portland Cement Concrete (PCC) in a Road Structure","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Asphalt Pavement Performance Evaluation","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Sustainability; Portland cement; Aggregate (composite); Asphalt; Civil engineering; Road construction; Waste management; Environmental science; Cement; Engineering; Materials science","score_opus":0.057447378853587604,"score_gpt":0.37371570976050755,"score_spread":0.31626833090691997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W561002847","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99420184,0.0010203128,0.00068634364,0.00025547497,0.00019142852,0.0029765666,0.00031323882,0.00013041172,0.00022435558],"genre_scores_gemma":[0.9965935,0.00055042794,0.0017391539,0.000017622755,0.00014729443,0.00030710924,0.0004779314,0.000096897864,0.0000700734],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9909977,0.0008838381,0.0017757427,0.0007094009,0.0036677057,0.0019656366],"domain_scores_gemma":[0.99565446,0.0004540343,0.00021727051,0.00053318834,0.0025579163,0.00058311754],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.008800195,0.0004637833,0.00067055435,0.0015445263,0.00039463319,0.000075764154,0.0003769606,0.0003582155,0.00041592147],"category_scores_gemma":[0.0002528738,0.0004907148,0.00012095592,0.0021093674,0.000653452,0.0014519112,0.000020951233,0.0013936403,0.0000070877804],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00085877464,0.0001888088,0.8863613,0.0032782657,0.00020297203,0.000038361835,0.027506914,0.02829781,0.04551838,0.0012948611,0.0004091668,0.0060443985],"study_design_scores_gemma":[0.0031671186,0.0004165665,0.9382791,0.0004151854,0.00006537072,6.180282e-7,0.01577522,0.014438039,0.02475616,0.0005853154,0.0014765409,0.0006247656],"about_ca_topic_score_codex":0.0061404873,"about_ca_topic_score_gemma":0.005484548,"teacher_disagreement_score":0.051917814,"about_ca_system_score_codex":0.00081634615,"about_ca_system_score_gemma":0.0004647697,"threshold_uncertainty_score":0.9997544},"labels":[],"label_agreement":null},{"id":"W564553463","doi":"","title":"Metros and Gentrification In Montreal - A Survival Analysis Approach","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Gentrification; Economic geography; Public transport; Transit (satellite); Urban transit; Rail transit; Regional science; Rapid transit; Geography; Sociology; Transport engineering; Civil engineering; Engineering","score_opus":0.09519568239898918,"score_gpt":0.4139929610813148,"score_spread":0.3187972786823256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W564553463","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9846515,0.0009586876,0.0012500176,0.0009306507,0.00015441932,0.0019207997,0.00027805413,0.00016851831,0.009687357],"genre_scores_gemma":[0.99472946,0.0008240061,0.0014277531,0.00002693846,0.00036730248,0.0005241401,0.0007556108,0.000053504886,0.0012912829],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9866502,0.003050354,0.0013481599,0.0012174814,0.005089131,0.0026446315],"domain_scores_gemma":[0.99448025,0.0013509947,0.00022010562,0.00059326866,0.0021801395,0.0011752204],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.020557595,0.00039159664,0.0007641328,0.0030692169,0.0016408158,0.0002981103,0.0007496107,0.00049832475,0.00049750204],"category_scores_gemma":[0.0005297784,0.00041100476,0.00031101386,0.009318414,0.0018543109,0.0021412978,0.0000133167105,0.0017237505,0.000052509135],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004113187,0.0007041603,0.9347485,0.00015728908,0.00018368229,0.000017636898,0.053159177,0.0001707127,0.00020024745,0.008200387,0.0002624521,0.0017844376],"study_design_scores_gemma":[0.00096084335,0.000077594304,0.9501538,0.000037179736,0.00015412543,2.845002e-8,0.04335802,0.00015272902,0.00010807476,0.00071241177,0.0038989391,0.00038622817],"about_ca_topic_score_codex":0.23012257,"about_ca_topic_score_gemma":0.40310052,"teacher_disagreement_score":0.17297795,"about_ca_system_score_codex":0.0004013096,"about_ca_system_score_gemma":0.00047494558,"threshold_uncertainty_score":0.9998342},"labels":[],"label_agreement":null},{"id":"W565964238","doi":"","title":"Modeling Commuters’ Response to Pre-Trip Information Provided for Prolonged and Large-Scale Network Disruptions: Case study of West LRT Construction in the City Calgary, Canada","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Transport engineering; TRIPS architecture; Scale (ratio); Quality (philosophy); Travel behavior; Sample (material); Traffic congestion; Perception; Geography; Computer science; Engineering","score_opus":0.056130365215050056,"score_gpt":0.3838431198488567,"score_spread":0.32771275463380667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W565964238","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97835106,0.00008022616,0.012233213,0.0018064923,0.00020004979,0.006751787,0.00041893093,0.00007430098,0.00008395035],"genre_scores_gemma":[0.99310523,0.000061012946,0.004451043,0.00009420894,0.00014258432,0.0016467131,0.000422583,0.000030911935,0.000045726443],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99047035,0.0031770763,0.0014033767,0.0004921907,0.0029868572,0.0014701505],"domain_scores_gemma":[0.9937743,0.002252437,0.00023387221,0.00038693481,0.0028680307,0.00048444828],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.02028218,0.0002749838,0.0004164662,0.00084837613,0.0023986076,0.00019328427,0.00044074462,0.00023990445,0.000027807944],"category_scores_gemma":[0.00094619056,0.00026203674,0.00008061215,0.0026656603,0.00035128894,0.0017368535,0.000010245766,0.0009349059,0.0000018602486],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003833548,0.0005436483,0.4962667,0.0002255425,0.000046226498,0.000048669106,0.45528483,0.040424008,0.000024433357,0.0017690179,0.00049212226,0.0010412598],"study_design_scores_gemma":[0.0024212466,0.0006587791,0.50727606,0.0001679195,0.0000550889,0.00000295687,0.48067835,0.0043736403,0.000014855671,0.00012981129,0.0039036702,0.0003176512],"about_ca_topic_score_codex":0.72160906,"about_ca_topic_score_gemma":0.9712245,"teacher_disagreement_score":0.24961545,"about_ca_system_score_codex":0.00030185876,"about_ca_system_score_gemma":0.0012950482,"threshold_uncertainty_score":0.9999832},"labels":[],"label_agreement":null},{"id":"W570856088","doi":"","title":"Life Cycle Assessment of Roadways Using a Pavement Sustainability Tool","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Asphalt Pavement Performance Evaluation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Sustainability; Transport engineering; Engineering; General partnership; Life-cycle assessment; Variety (cybernetics); Environmental impact assessment; Business; Computer science; Production (economics)","score_opus":0.07460948296951722,"score_gpt":0.4137571990190446,"score_spread":0.3391477160495274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W570856088","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98557943,0.0004114102,0.008999349,0.00032433195,0.0003409159,0.002827503,0.00022450439,0.0003170363,0.00097550865],"genre_scores_gemma":[0.9926358,0.00031381482,0.0054015084,0.000029665815,0.00031479416,0.0006437738,0.0003954389,0.00013448593,0.0001307025],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.98823154,0.0010097702,0.0019346892,0.0006887046,0.0057739415,0.0023613586],"domain_scores_gemma":[0.9925427,0.0006990155,0.00023064586,0.0007748351,0.004813885,0.0009389211],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.013861545,0.00047985296,0.000654346,0.0013962053,0.0006937791,0.00010245672,0.00060587155,0.0003326167,0.0006940715],"category_scores_gemma":[0.0005353632,0.00051969517,0.00025576245,0.002579198,0.0006488851,0.0020570545,0.000023349538,0.0015494832,0.000037635287],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003189315,0.0011240662,0.56717354,0.0039248173,0.00037384502,0.00002079177,0.017872415,0.373909,0.018771626,0.009524331,0.0017717453,0.0052148975],"study_design_scores_gemma":[0.0017055119,0.00041596012,0.8983105,0.00025973102,0.00008037717,2.3103814e-7,0.014317807,0.07444825,0.006141978,0.0006761488,0.0030024888,0.0006410476],"about_ca_topic_score_codex":0.0026059237,"about_ca_topic_score_gemma":0.0010804695,"teacher_disagreement_score":0.3311369,"about_ca_system_score_codex":0.0012143095,"about_ca_system_score_gemma":0.0013328666,"threshold_uncertainty_score":0.99972546},"labels":[],"label_agreement":null},{"id":"W576447651","doi":"","title":"Study on Calibration and Validation of Fundamental Diagram for Urban Arterials","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diagram; Flow (mathematics); Traffic flow (computer networking); Calibration; Maximum flow problem; Data collection; Statistics; Simulation; Statistical physics; Mechanics; Environmental science; Meteorology; Computer science; Mathematics; Physics; Mathematical optimization","score_opus":0.07486028133228853,"score_gpt":0.37294250127365824,"score_spread":0.29808221994136974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W576447651","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98428434,0.00011700158,0.009367551,0.00017566292,0.00030053293,0.0038163546,0.00045926505,0.0009518981,0.00052739104],"genre_scores_gemma":[0.996677,0.0001768597,0.00084975315,0.000015972633,0.00023488773,0.0013684502,0.0005078103,0.00008178744,0.000087525295],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9954201,0.00047627997,0.00091259956,0.00046361177,0.0018179399,0.00090947974],"domain_scores_gemma":[0.99784946,0.0006110336,0.000104846295,0.0003312347,0.00075720355,0.0003462135],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0045969635,0.00028720076,0.000383741,0.0010908389,0.00037974727,0.00010795147,0.00024724705,0.0001866303,0.00004292551],"category_scores_gemma":[0.0001242582,0.00029997464,0.00011040104,0.0008506062,0.0002924677,0.00093535293,0.000007968354,0.00052312185,0.000008750464],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027849097,0.0043356763,0.7176392,0.0028486883,0.0008095227,0.000027913551,0.08959228,0.005069923,0.048497997,0.031211082,0.081648484,0.015534337],"study_design_scores_gemma":[0.0033749887,0.0029299813,0.90165514,0.0002593148,0.00011035498,2.7830552e-7,0.02748339,0.0021210613,0.053615298,0.00036045542,0.0074464567,0.0006433],"about_ca_topic_score_codex":0.0003843671,"about_ca_topic_score_gemma":0.00048718188,"teacher_disagreement_score":0.18401593,"about_ca_system_score_codex":0.00011696114,"about_ca_system_score_gemma":0.000053020427,"threshold_uncertainty_score":0.9999452},"labels":[],"label_agreement":null},{"id":"W576953925","doi":"","title":"Cycle-Tracks, Bicycle Lanes, and On-street Cycling in Montreal, Canada: A Preliminary Comparison of the Cyclist Injury Risk","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Traffic and Road Safety","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Cycling; Transport engineering; Poison control; Injury prevention; Visibility; Geography; Engineering; Environmental health; Medicine; Meteorology; Forestry","score_opus":0.027389074869736466,"score_gpt":0.32572539216118596,"score_spread":0.2983363172914495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W576953925","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9946463,0.0010580792,0.0000402095,0.00042977615,0.00027151007,0.001112942,0.0011205184,0.0001235096,0.0011971507],"genre_scores_gemma":[0.9983663,0.0007410338,0.00019369271,0.0000225116,0.00014168068,0.00016467315,0.00018116324,0.00008561919,0.00010333782],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9931699,0.0008293357,0.0012583946,0.00054715405,0.0026840926,0.001511104],"domain_scores_gemma":[0.9968298,0.0013647985,0.00017176471,0.00055359653,0.00057977426,0.0005002485],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0032847247,0.00039038446,0.0005847306,0.0006678917,0.00059438834,0.000045019955,0.00056929834,0.00030281077,0.000059829494],"category_scores_gemma":[0.0002348669,0.00033795022,0.00013266044,0.0016332315,0.00060163526,0.000444537,0.000018460443,0.0023225022,0.000014023848],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065776845,0.000338835,0.9372847,0.0004657696,0.000075026976,0.0000197302,0.009802541,0.040901154,0.00047797457,0.00040737004,0.004767392,0.0048017288],"study_design_scores_gemma":[0.00082539814,0.00021801144,0.9828924,0.00031082093,0.00003071472,2.1939273e-7,0.008982319,0.002018867,0.0020063529,0.00009333857,0.0022985511,0.00032302458],"about_ca_topic_score_codex":0.52262497,"about_ca_topic_score_gemma":0.89246345,"teacher_disagreement_score":0.36983845,"about_ca_system_score_codex":0.00028029486,"about_ca_system_score_gemma":0.00035505355,"threshold_uncertainty_score":0.9999792},"labels":[],"label_agreement":null},{"id":"W577047802","doi":"","title":"Implementing Weigh-in-Motion for Generation of Carbon Offset Credits in Canada","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Transport Systems and Technology","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Greenhouse gas; Carbon offset; Offset (computer science); Carbon footprint; Environmental economics; Carbon credit; Kyoto Protocol; Business; Revenue; Enforcement; Emissions trading; Truck; Transport engineering; Engineering; Computer science; Accounting; Automotive engineering; Economics","score_opus":0.0623104396155848,"score_gpt":0.3312997735515157,"score_spread":0.2689893339359309,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W577047802","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99429303,0.000886673,0.00074310094,0.00022226012,0.00057992555,0.0020506387,0.00048768148,0.000120059834,0.00061664445],"genre_scores_gemma":[0.9966477,0.000285263,0.0008399933,0.000008376204,0.0002758804,0.0009179521,0.0008713301,0.00009997956,0.000053526404],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9929629,0.00033915858,0.001778188,0.00057009654,0.002048653,0.0023010252],"domain_scores_gemma":[0.9974203,0.0005387208,0.0001547494,0.00039634426,0.0011846736,0.00030519205],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.005836593,0.000343875,0.00062394515,0.001738252,0.00015804413,0.000021087826,0.00040562855,0.00031859806,0.00010887773],"category_scores_gemma":[0.00012101317,0.00039212286,0.00011926521,0.0017267579,0.00018026927,0.000599743,0.000007247244,0.0010991758,0.0000036124409],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023698542,0.00021311457,0.9477679,0.0015768482,0.00007293177,0.000038948037,0.0061684144,0.009111673,0.022576038,0.0057338485,0.0018706564,0.0046326015],"study_design_scores_gemma":[0.002302489,0.00017931293,0.9472844,0.0003371593,0.000022333734,4.5995907e-7,0.007653183,0.009085974,0.020143766,0.00020186228,0.012274246,0.0005148358],"about_ca_topic_score_codex":0.7719706,"about_ca_topic_score_gemma":0.98399854,"teacher_disagreement_score":0.21202792,"about_ca_system_score_codex":0.0013349066,"about_ca_system_score_gemma":0.00089158845,"threshold_uncertainty_score":0.9998531},"labels":[],"label_agreement":null},{"id":"W577751950","doi":"","title":"Evaluating the Impact of Travel Demand Management Strategies on GHGs for Downtown Commuters in Rail Catchment Areas","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Downtown; Greenhouse gas; Public transport; Transport engineering; Mode choice; Land use; Population; Transit (satellite); TRIPS architecture; Catchment area; Business; Environmental science; Geography; Engineering; Drainage basin; Civil engineering","score_opus":0.14753944464117225,"score_gpt":0.4905458445086879,"score_spread":0.34300639986751563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W577751950","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9844683,0.00024951168,0.0026428131,0.0015360583,0.00019576114,0.004196457,0.0004412587,0.00009522782,0.0061746347],"genre_scores_gemma":[0.99379414,0.00051368965,0.0029182772,0.0000359369,0.00018540895,0.0011689721,0.00065742474,0.00006214644,0.0006640189],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.98968554,0.0021980465,0.0013486062,0.00067707343,0.0041535683,0.001937182],"domain_scores_gemma":[0.99350274,0.0028699492,0.0003341909,0.0004956114,0.0023117752,0.00048575792],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.019813804,0.0003781021,0.00051467697,0.0012966107,0.0016815163,0.00021399895,0.00079883187,0.0002876052,0.00025827836],"category_scores_gemma":[0.00033867362,0.00031528884,0.0003531397,0.0024644174,0.0011317431,0.0011017408,0.000007419029,0.0010629711,0.00001934244],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005457285,0.0017526267,0.39663115,0.0008291297,0.00042997583,0.000027092423,0.31284776,0.16329132,0.0010631725,0.103056975,0.0033105097,0.011302982],"study_design_scores_gemma":[0.002221275,0.0010208645,0.8781961,0.00041687235,0.000054034692,9.399875e-8,0.11441492,0.00088387553,0.00033076908,0.0013853572,0.00072526664,0.00035056108],"about_ca_topic_score_codex":0.041947316,"about_ca_topic_score_gemma":0.024591243,"teacher_disagreement_score":0.48156494,"about_ca_system_score_codex":0.00049347605,"about_ca_system_score_gemma":0.0008801322,"threshold_uncertainty_score":0.9999299},"labels":[],"label_agreement":null},{"id":"W581260361","doi":"","title":"North Sound Rail Operations Simulation 2011","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Transport and Economic Policies","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Train; Service (business); Freight trains; Sound (geography); Transport engineering; Engineering; Work (physics); Line (geometry); State (computer science); Rail freight transport; Telecommunications; Computer science; Business; History; Marketing; Archaeology","score_opus":0.09750317356244527,"score_gpt":0.357956993328695,"score_spread":0.26045381976624976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W581260361","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98607993,0.00035285656,0.0014485555,0.001653142,0.0006635906,0.0017846097,0.00030495587,0.0005069964,0.0072053676],"genre_scores_gemma":[0.99172294,0.00014467101,0.0005665562,0.0004678874,0.0028501844,0.0005252013,0.0019001819,0.00017103396,0.0016513462],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99124205,0.00024279935,0.0015693875,0.0010190981,0.0030545471,0.0028721073],"domain_scores_gemma":[0.99453664,0.0006736519,0.0002406311,0.00076309755,0.0034265062,0.00035944744],"candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0056950194,0.0005970611,0.00064383436,0.0023924722,0.0022652089,0.0006734269,0.00091029634,0.00037489663,0.0025522741],"category_scores_gemma":[0.0002685813,0.0006244523,0.00034727753,0.0024167055,0.00091803423,0.0069668805,0.000031521457,0.0016589412,0.004014223],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00063378207,0.0006998847,0.8982844,0.0005797764,0.00014851762,0.000031511758,0.0068783252,0.041911487,0.0003626972,0.037010357,0.011781305,0.001677991],"study_design_scores_gemma":[0.0012901499,0.00007321626,0.8699341,0.00008016357,0.00007628416,2.4773468e-7,0.0046719,0.0024225155,0.00010581999,0.0014562655,0.119181365,0.0007080039],"about_ca_topic_score_codex":0.034004133,"about_ca_topic_score_gemma":0.12253647,"teacher_disagreement_score":0.10740006,"about_ca_system_score_codex":0.0002370356,"about_ca_system_score_gemma":0.0002666038,"threshold_uncertainty_score":0.9996207},"labels":[],"label_agreement":null},{"id":"W584136151","doi":"","title":"Neighborhood-Coordinated Multiagent Reinforcement Learning for Networked Adaptive Traffic Signal Control","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Traffic control and management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Reinforcement learning; Adaptive control; SIGNAL (programming language); Controller (irrigation); Computer science; Traffic congestion; Real-time computing; Network traffic control; Network congestion; Control (management); Engineering; Computer network; Transport engineering; Artificial intelligence","score_opus":0.03919644254207663,"score_gpt":0.3114759096612348,"score_spread":0.2722794671191582,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W584136151","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7358613,0.003237726,0.23346949,0.0017272183,0.0015188033,0.014742301,0.00054174504,0.0031094977,0.0057919403],"genre_scores_gemma":[0.9933015,0.0003871126,0.0009847777,0.000063694264,0.00067253044,0.002737956,0.0007399833,0.0002031144,0.0009093156],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9907864,0.0007677163,0.0014321711,0.0008428422,0.0029117286,0.003259161],"domain_scores_gemma":[0.99450684,0.0016385225,0.00015990215,0.000441988,0.002242788,0.0010099673],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0066879843,0.0006354917,0.0007385027,0.0011945161,0.0010999101,0.00018267249,0.0006340435,0.00037601727,0.00043987564],"category_scores_gemma":[0.00013198775,0.0006594614,0.0004153283,0.0016932425,0.00041246685,0.0010251431,0.000012635537,0.0019247156,0.00013704614],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017966244,0.00029802075,0.004727852,0.0005010205,0.0005105831,0.000029257577,0.0062987,0.9481864,0.0013288385,0.0028539451,0.008260554,0.02520818],"study_design_scores_gemma":[0.017161356,0.0028526785,0.17294568,0.0005497714,0.00040583985,0.000001011515,0.01759511,0.61662525,0.0011039564,0.00025472787,0.16826911,0.0022355001],"about_ca_topic_score_codex":0.0008658181,"about_ca_topic_score_gemma":0.0021318502,"teacher_disagreement_score":0.33156115,"about_ca_system_score_codex":0.00044298064,"about_ca_system_score_gemma":0.00018323814,"threshold_uncertainty_score":0.9995857},"labels":[],"label_agreement":null},{"id":"W589490469","doi":"","title":"Evaluating the Safety Estimates of Transit Operations and City Transportation Plans","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Traffic and Road Safety","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Transport engineering; Plan (archaeology); Transit (satellite); Macro; Transportation planning; Computer science; Engineering; Public transport; Geography","score_opus":0.09436734009643179,"score_gpt":0.39767290336941824,"score_spread":0.30330556327298647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W589490469","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9832448,0.001322501,0.009560954,0.00086888374,0.00028208722,0.0018470428,0.0016911697,0.00038113366,0.0008014617],"genre_scores_gemma":[0.99176455,0.001271445,0.0051682205,0.000025648855,0.00021671249,0.00035820054,0.00093202625,0.00011581316,0.0001473682],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99234086,0.000702448,0.0015687224,0.0006310431,0.0031010953,0.0016558552],"domain_scores_gemma":[0.9952247,0.0017692379,0.00010292867,0.0005510028,0.0017685471,0.0005835418],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0076775127,0.00047788193,0.00060552644,0.0007189032,0.001380653,0.00010618327,0.0005644563,0.00036261725,0.00026335174],"category_scores_gemma":[0.00020485643,0.00040591412,0.00021974761,0.0018740712,0.0011872797,0.0011931348,0.0000066624557,0.0017403057,0.00002951221],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022342259,0.0007995553,0.39613205,0.0026356129,0.00075302523,0.000037245172,0.10996791,0.39609665,0.03474164,0.027869623,0.0019571597,0.026775315],"study_design_scores_gemma":[0.0014794131,0.0004498374,0.9684012,0.00025845662,0.00013768584,0.0000011650754,0.0108344015,0.009077606,0.0057293405,0.00034504608,0.0027663882,0.0005194688],"about_ca_topic_score_codex":0.003225866,"about_ca_topic_score_gemma":0.01343992,"teacher_disagreement_score":0.57226914,"about_ca_system_score_codex":0.00013625265,"about_ca_system_score_gemma":0.0002497136,"threshold_uncertainty_score":0.9999194},"labels":[],"label_agreement":null},{"id":"W589876814","doi":"","title":"Cycling and Weather: A Multi-city and Multi-facility Study in North America","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Cycling; Dew point; Precipitation; Recreation; Environmental science; Meteorology; Morning; Geography; Climatology; Forestry","score_opus":0.13007334190473216,"score_gpt":0.43578269714298434,"score_spread":0.30570935523825216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W589876814","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9935698,0.0008555815,0.0003899928,0.0007436984,0.0001325428,0.0034074741,0.00043938984,0.00019259201,0.00026892064],"genre_scores_gemma":[0.9957062,0.0007910813,0.0021018505,0.000046738245,0.00015526003,0.00049461797,0.0001969192,0.00004841189,0.00045891534],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.98858327,0.0028136931,0.0013405598,0.0013468728,0.0034510456,0.002464565],"domain_scores_gemma":[0.995005,0.0013449973,0.0001938737,0.00051833194,0.0016799873,0.0012577911],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.013024878,0.00045177655,0.00070685835,0.0011166573,0.002091569,0.00027677452,0.0006049656,0.0003380979,0.00026176666],"category_scores_gemma":[0.00078864716,0.00046474874,0.00013974169,0.0031496468,0.0026725412,0.0020663776,0.000027318687,0.0021382659,0.000037512433],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034829875,0.0016057752,0.8463521,0.00016087573,0.00004144011,0.00004610971,0.1461211,0.000028499291,0.00009417759,0.0000991626,0.000046001864,0.0050564627],"study_design_scores_gemma":[0.0021332186,0.00022867446,0.8941876,0.00006566819,0.000030005343,5.1370456e-8,0.09963044,0.00008879605,0.000037395854,0.00005813531,0.0031303735,0.00040959593],"about_ca_topic_score_codex":0.16211993,"about_ca_topic_score_gemma":0.6898177,"teacher_disagreement_score":0.5276978,"about_ca_system_score_codex":0.00026683373,"about_ca_system_score_gemma":0.0004891417,"threshold_uncertainty_score":0.9997804},"labels":[],"label_agreement":null},{"id":"W600941191","doi":"","title":"Evaluation of Portland-Limestone Cement Concretes Containing High Volume of Fly Ash","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Concrete and Cement Materials Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Portland cement; Fly ash; Clinker (cement); Cement; Materials science; Compressive strength; Composite material","score_opus":0.07942812155883103,"score_gpt":0.37042173959037783,"score_spread":0.2909936180315468,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W600941191","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99217266,0.0014819418,0.00027916938,0.0001591217,0.00034488234,0.002167951,0.0006580686,0.00016934038,0.0025668552],"genre_scores_gemma":[0.9964077,0.0007023379,0.00071012304,0.000008728595,0.00026113965,0.00061354786,0.0009269494,0.00012123517,0.00024826988],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9841436,0.0017764452,0.0019481984,0.0006101207,0.00954547,0.00197618],"domain_scores_gemma":[0.9890993,0.0008441914,0.0002676771,0.0006676757,0.008550495,0.0005706587],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.025275143,0.00043320074,0.0008367958,0.0015001161,0.0003537384,0.00007874306,0.00065035786,0.00034206666,0.0022447773],"category_scores_gemma":[0.00044971667,0.0004586571,0.00023332406,0.0019039583,0.0008015247,0.0010136274,0.000025312991,0.0010518321,0.000092170805],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002469931,0.0006852289,0.34060356,0.004067401,0.0014756994,0.00004261096,0.03103264,0.015502549,0.5674424,0.008057025,0.0074073975,0.021213565],"study_design_scores_gemma":[0.005095436,0.0016711752,0.6607651,0.0007740474,0.0003731768,7.341422e-7,0.016328776,0.003926315,0.30470163,0.00061926176,0.0048534125,0.00089092215],"about_ca_topic_score_codex":0.0068730074,"about_ca_topic_score_gemma":0.0016966596,"teacher_disagreement_score":0.32016158,"about_ca_system_score_codex":0.0003598011,"about_ca_system_score_gemma":0.0006664055,"threshold_uncertainty_score":0.9997865},"labels":[],"label_agreement":null},{"id":"W607487780","doi":"","title":"Overcoming Barriers to Using Social Media in Public Transportation: Summary of Findings from TCRP Synthesis SB-20","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Social Media and Politics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Social media; Staffing; Transparency (behavior); Business; Public relations; Agency (philosophy); Internet privacy; Political science; Computer science; Computer security; Sociology; World Wide Web","score_opus":0.12760425072938894,"score_gpt":0.409613431915453,"score_spread":0.2820091811860641,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W607487780","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99028486,0.00025113652,0.0001245991,0.0036449376,0.0006708828,0.0014905736,0.0021747143,0.00013756647,0.0012207448],"genre_scores_gemma":[0.99548805,0.00026648675,0.0018194164,0.000114533745,0.0011676088,0.0004153094,0.00049955235,0.00011736086,0.00011167979],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.98459554,0.0029705763,0.0017948438,0.00091609184,0.0064561274,0.0032668237],"domain_scores_gemma":[0.9867333,0.0073210355,0.00026761275,0.00039955878,0.002928713,0.002349788],"candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.009476923,0.000464773,0.00093182764,0.0023505588,0.0020835164,0.00019292375,0.0010681307,0.0007632704,0.0014452151],"category_scores_gemma":[0.0055252034,0.000554584,0.00036060813,0.005274591,0.0019353256,0.0018960485,0.000014421127,0.0017347843,0.000056840912],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046975212,0.00024575557,0.60464865,0.00017406636,0.00008685728,0.000040312785,0.37121403,0.00006672055,0.004343806,0.016104529,0.0015594526,0.0010460949],"study_design_scores_gemma":[0.0011674489,0.000095790034,0.61885095,0.00049010135,0.000089036505,6.091449e-8,0.34068903,0.000020844069,0.0053913305,0.0017997924,0.030684233,0.0007214036],"about_ca_topic_score_codex":0.08113003,"about_ca_topic_score_gemma":0.23489869,"teacher_disagreement_score":0.15376866,"about_ca_system_score_codex":0.0008328786,"about_ca_system_score_gemma":0.0025680882,"threshold_uncertainty_score":0.9996906},"labels":[],"label_agreement":null},{"id":"W608535412","doi":"","title":"Wearing Surfaces: An Experimental Study for an Orthotropic Steel Deck","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Mechanical stress and fatigue analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Deck; Orthotropic material; Truck; Snow; Durability; Cracking; Abrasion (mechanical); Slab; Environmental science; Structural engineering; Geotechnical engineering; Forensic engineering; Materials science; Geology; Composite material; Engineering","score_opus":0.12610680445670228,"score_gpt":0.4063787220576128,"score_spread":0.2802719176009105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W608535412","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99317485,0.00056596444,0.001895207,0.00005404444,0.00025066995,0.0027468943,0.00034040448,0.00048968353,0.0004822825],"genre_scores_gemma":[0.99398404,0.00015790075,0.0028138123,0.000016513479,0.0004072838,0.0014765281,0.0007256621,0.00018700137,0.00023122905],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99111605,0.0009871713,0.0012501753,0.0009817318,0.0033242947,0.0023406066],"domain_scores_gemma":[0.99531174,0.0006292526,0.00010390713,0.00083082926,0.0016968955,0.0014274],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.005791439,0.00051130966,0.00066688214,0.00093661546,0.0011268586,0.00029296195,0.0008396582,0.00032604125,0.0004807345],"category_scores_gemma":[0.00012063927,0.00052015093,0.0002618574,0.0016206888,0.00029035547,0.0022677165,0.0000141671835,0.0012727854,0.000070956434],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022871427,0.010009643,0.72745866,0.0013071179,0.0009828313,0.00009859708,0.08692071,0.03312174,0.11755099,0.0106254155,0.0018250039,0.0078121596],"study_design_scores_gemma":[0.004218689,0.005662717,0.828112,0.00019084921,0.00018716772,3.9405396e-7,0.11811008,0.012709618,0.02274353,0.00036299127,0.006233323,0.0014686577],"about_ca_topic_score_codex":0.0056429687,"about_ca_topic_score_gemma":0.018993294,"teacher_disagreement_score":0.10065332,"about_ca_system_score_codex":0.00022739617,"about_ca_system_score_gemma":0.0001260458,"threshold_uncertainty_score":0.999725},"labels":[],"label_agreement":null},{"id":"W609884583","doi":"","title":"Understanding and Promoting Multimodal Freight Transportation System Performance within Mega-Regions: Lessons from Great Lakes-Saint Lawrence Basin","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Transport and Economic Policies","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Work (physics); Transport engineering; Business; Population; Multimodal transport; Regional science; Environmental planning; Engineering; Geography","score_opus":0.13299017487046239,"score_gpt":0.32392963168660216,"score_spread":0.19093945681613977,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W609884583","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99097955,0.00037578758,0.001320591,0.0020696716,0.00053827104,0.0018654714,0.0006049126,0.00060117024,0.0016445793],"genre_scores_gemma":[0.9947245,0.00025591018,0.0010140915,0.0001554514,0.001269807,0.0004946871,0.0016944186,0.0001803486,0.00021079555],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9911359,0.00030596746,0.0018284934,0.001382731,0.0027990954,0.0025478327],"domain_scores_gemma":[0.996169,0.00077051687,0.0005643305,0.000644205,0.0014252388,0.00042675794],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.006591763,0.00075748604,0.00089871173,0.0017909972,0.0023493269,0.00066523254,0.0007715196,0.00048884813,0.00026365233],"category_scores_gemma":[0.00015443684,0.0007668814,0.00027400485,0.0021292637,0.0011361632,0.0057629463,0.00002163619,0.0017983086,0.0001904158],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00096004206,0.00033910948,0.84345424,0.0024336437,0.00022507911,0.000084370804,0.019774262,0.0011346982,0.0021036717,0.12730683,0.0009794672,0.0012045656],"study_design_scores_gemma":[0.0021797563,0.0001342465,0.9451729,0.0015713723,0.00021016317,0.0000012135043,0.031251535,0.0055299676,0.0014228106,0.0018593458,0.009530701,0.001135987],"about_ca_topic_score_codex":0.062222872,"about_ca_topic_score_gemma":0.05537477,"teacher_disagreement_score":0.12544748,"about_ca_system_score_codex":0.0006610517,"about_ca_system_score_gemma":0.00025671587,"threshold_uncertainty_score":0.9994782},"labels":[],"label_agreement":null},{"id":"W623030489","doi":"","title":"Reliability-Based Assessment of Steel-Free Deck System Bridges","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Structural engineering; Bridge (graph theory); Reliability (semiconductor); Deck; Engineering; Deflection (physics); Cracking; Bridge deck; Finite element method; Reliability engineering; Structural load; Structural system; Materials science","score_opus":0.033377655201569795,"score_gpt":0.3496690688528286,"score_spread":0.3162914136512588,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W623030489","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9863766,0.0003586038,0.0061274553,0.000169698,0.0008197886,0.0015324443,0.00063768076,0.00058924785,0.0033885],"genre_scores_gemma":[0.9872623,0.00013190438,0.011039011,0.0000133676795,0.0004969988,0.00049065193,0.00029979082,0.00015487711,0.00011110737],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99039936,0.00075751316,0.0015007881,0.0006768659,0.0043983217,0.0022671788],"domain_scores_gemma":[0.9932694,0.0010649143,0.0001695886,0.0011262599,0.0036526206,0.00071724696],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0076389303,0.0004851948,0.0007075681,0.0013227344,0.00055548106,0.00010073763,0.000981889,0.0003969165,0.00012865146],"category_scores_gemma":[0.00024449444,0.00048427784,0.0002989463,0.0019360571,0.0006977491,0.0010020592,0.00001887879,0.0019115127,0.000037124777],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006592603,0.000528214,0.7965824,0.009403776,0.0002735028,0.00010117136,0.009260059,0.09678024,0.04848107,0.026984531,0.0087898765,0.0021559303],"study_design_scores_gemma":[0.0015664694,0.00030413718,0.95328605,0.00075795973,0.000050676437,5.3107374e-7,0.010679935,0.0038306736,0.022407362,0.00016100238,0.006438012,0.0005171602],"about_ca_topic_score_codex":0.0026402813,"about_ca_topic_score_gemma":0.0014911016,"teacher_disagreement_score":0.15670371,"about_ca_system_score_codex":0.00070813537,"about_ca_system_score_gemma":0.00046103523,"threshold_uncertainty_score":0.99976087},"labels":[],"label_agreement":null},{"id":"W624137399","doi":"","title":"Framework for Microsurfacing Project Selection: Key to Long-Term Performance","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Asphalt Pavement Performance Evaluation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Agency (philosophy); State highway; Engineering; Process (computing); Transport engineering; Key (lock); Selection (genetic algorithm); Term (time); Highway maintenance; Construction engineering; Civil engineering; Risk analysis (engineering); Computer science; Business","score_opus":0.10139555867881056,"score_gpt":0.41395080850312066,"score_spread":0.3125552498243101,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W624137399","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9491381,0.0003233842,0.04315486,0.00035552733,0.0006651818,0.004867404,0.00028406014,0.00066852215,0.00054298056],"genre_scores_gemma":[0.96751356,0.00046128838,0.026584236,0.00006378043,0.00091537234,0.002930371,0.00065559126,0.00022387697,0.00065193424],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99076617,0.00041828706,0.0013233734,0.00085793005,0.003640815,0.0029934116],"domain_scores_gemma":[0.9943584,0.0009655124,0.00012847432,0.0005435498,0.003229371,0.00077467476],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.008344198,0.0005559938,0.00053967006,0.0017954716,0.0014566435,0.0002446543,0.00067145185,0.0004549915,0.0003261299],"category_scores_gemma":[0.0003246561,0.00061352376,0.00021848513,0.0036251429,0.00029696754,0.0021783288,0.000015499247,0.0017805932,0.00036287255],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001226442,0.00043967782,0.8839971,0.0034423664,0.00025666435,0.000008802655,0.029937461,0.032288473,0.022646323,0.0030948638,0.009068029,0.0135938],"study_design_scores_gemma":[0.0013186359,0.0009516367,0.92297167,0.0007595722,0.00006129517,8.66904e-7,0.002518094,0.0031649123,0.05677325,0.00016884162,0.010422357,0.0008888866],"about_ca_topic_score_codex":0.00040427936,"about_ca_topic_score_gemma":0.0019577083,"teacher_disagreement_score":0.038974557,"about_ca_system_score_codex":0.00066656846,"about_ca_system_score_gemma":0.0003887122,"threshold_uncertainty_score":0.9998433},"labels":[],"label_agreement":null},{"id":"W626894379","doi":"","title":"Analyzing Fuzzy Logic, Logistic-Decision Tree, and Neural Network Classification for Extracting Subzonal Land Uses from Remote Sensing Imagery","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Decision tree; Land cover; Data mining; Geographic information system; Artificial neural network; Remote sensing; Artificial intelligence; Land use; Geography; Engineering","score_opus":0.10845363435030646,"score_gpt":0.37358366914792324,"score_spread":0.26513003479761676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W626894379","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98274475,0.0006023291,0.01319639,0.0007809155,0.00029228762,0.0013006113,0.00030613685,0.00014247213,0.0006340913],"genre_scores_gemma":[0.9735384,0.00043668848,0.024184432,0.00007098066,0.0007843799,0.00004840772,0.0007748269,0.000080646285,0.00008126779],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9927302,0.00080125337,0.0011472193,0.0010933391,0.0022812975,0.0019467154],"domain_scores_gemma":[0.99395674,0.0039004928,0.0003196741,0.00047204364,0.00065068004,0.0007003455],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0072800145,0.00040886196,0.0005300727,0.0003869452,0.0016323526,0.00032013256,0.00042479046,0.0003381087,0.00034449363],"category_scores_gemma":[0.00048273365,0.0003711045,0.00018440012,0.001290593,0.00034352066,0.0017115618,0.000037404523,0.0010040596,0.000103214494],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016397015,0.00014532782,0.9253856,0.00025465232,0.000086205095,0.00004648636,0.003694856,0.0054359557,0.004914948,0.00024906604,0.0018382667,0.056308962],"study_design_scores_gemma":[0.0011315495,0.00020827982,0.96398824,0.00026668032,0.00007484775,0.0000012719717,0.0031261353,0.023485068,0.00035596103,0.004165717,0.0027173453,0.00047888246],"about_ca_topic_score_codex":0.020619921,"about_ca_topic_score_gemma":0.0567545,"teacher_disagreement_score":0.05583008,"about_ca_system_score_codex":0.0002165614,"about_ca_system_score_gemma":0.000074378346,"threshold_uncertainty_score":0.9998741},"labels":[],"label_agreement":null},{"id":"W628308758","doi":"","title":"Predictors of Driving Among Families Living Within 2 km from School","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Psychosocial; Demographics; Descriptive statistics; Logistic regression; Psychology; Demography; Test (biology); Minor (academic); Geography; Developmental psychology; Sociology; Statistics; Mathematics; Humanities","score_opus":0.05073304890170818,"score_gpt":0.3766892335225725,"score_spread":0.3259561846208643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W628308758","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9888738,0.0005576129,0.00024652496,0.00043386742,0.00073863566,0.001857477,0.00062540534,0.0003628212,0.0063038776],"genre_scores_gemma":[0.9947799,0.00053699483,0.0014066597,0.000028477853,0.0011214882,0.00033145546,0.000438951,0.00011228938,0.0012437743],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9836556,0.0028623643,0.0020818275,0.001173328,0.0074391603,0.0027877234],"domain_scores_gemma":[0.9890186,0.0036946798,0.0005192536,0.0008324244,0.0041402364,0.0017947963],"candidate_categories":["metaepi_narrow","sts","research_integrity","insufficient_payload"],"consensus_categories":["sts"],"category_scores_codex":[0.01728187,0.00050854805,0.00082152814,0.0015352449,0.0022726934,0.0002662295,0.0014271948,0.00065638457,0.00222004],"category_scores_gemma":[0.0025900856,0.0005305944,0.00040879427,0.0037460786,0.0039454605,0.0037375975,0.000028650169,0.002453833,0.000121306795],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001898277,0.0004665107,0.8964437,0.00019839598,0.00014124978,0.000016950775,0.09731394,0.00012211368,0.0014303429,0.0020590774,0.0011927043,0.00042514646],"study_design_scores_gemma":[0.0005272357,0.00014564603,0.90793794,0.0006076264,0.00007063128,1.7142021e-8,0.08350192,0.000024865354,0.002039204,0.00055991486,0.0041282508,0.00045675473],"about_ca_topic_score_codex":0.17456903,"about_ca_topic_score_gemma":0.25108147,"teacher_disagreement_score":0.07651245,"about_ca_system_score_codex":0.00040513623,"about_ca_system_score_gemma":0.0013976198,"threshold_uncertainty_score":0.99984753},"labels":[],"label_agreement":null},{"id":"W629362891","doi":"","title":"Current State of the Pavement Warranty in the United States and Canada","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Warranty; State (computer science); Agency (philosophy); Business; Engineering; Transport engineering; Forensic engineering; Computer science; Political science; Sociology; Law","score_opus":0.028990771879116445,"score_gpt":0.31519705074544563,"score_spread":0.2862062788663292,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W629362891","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9966521,0.0007853666,0.00012705121,0.0005572322,0.0004232705,0.0010299481,0.00029133083,0.00003984524,0.000093799215],"genre_scores_gemma":[0.9975924,0.0017257839,0.00009921887,0.000040614417,0.000117801996,0.00019687659,0.00015740847,0.00004224072,0.000027688837],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9944202,0.00062150083,0.0007630705,0.0002905607,0.0026028848,0.0013017977],"domain_scores_gemma":[0.9976882,0.0006825199,0.00008031115,0.00038349463,0.0009434683,0.00022203509],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004121504,0.00024399467,0.00026914978,0.00049880135,0.00039448505,0.000055326112,0.000543542,0.00006871922,0.000019061279],"category_scores_gemma":[0.00009567557,0.00017235236,0.00007104036,0.0016420482,0.00044099762,0.00032474104,0.000011893351,0.0014810882,0.0000021927776],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024386366,0.00018558383,0.8559696,0.0016318874,0.00011047249,0.000033316166,0.06790909,0.04674707,0.002863273,0.001806137,0.0075988914,0.0149008315],"study_design_scores_gemma":[0.0005182939,0.000055845478,0.9614899,0.00026915883,0.000012921294,2.746892e-7,0.009986955,0.0005269113,0.0043858853,0.0003941793,0.022158979,0.000200692],"about_ca_topic_score_codex":0.44197726,"about_ca_topic_score_gemma":0.74001026,"teacher_disagreement_score":0.29803303,"about_ca_system_score_codex":0.0002300195,"about_ca_system_score_gemma":0.00030577794,"threshold_uncertainty_score":0.7028325},"labels":[],"label_agreement":null},{"id":"W629545554","doi":"","title":"An Analysis of Empirical Evidence of Cyclists’ Route Choice and Its Implications for Planning","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Cycling; TRIPS architecture; Destinations; Transport engineering; Shortest path problem; Recreation; Investment (military); Work (physics); Geography; Computer science; Operations research; Tourism; Engineering; Graph","score_opus":0.27702028215872776,"score_gpt":0.5372751067481093,"score_spread":0.26025482458938154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W629545554","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9921235,0.0015845487,0.0014520033,0.0014884294,0.00008143997,0.0018007165,0.0010503439,0.00009088166,0.00032813614],"genre_scores_gemma":[0.9968927,0.00037775218,0.0013932653,0.000028345812,0.00021391705,0.00040027115,0.0004819639,0.000042134452,0.00016963467],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9921556,0.0013377822,0.0014584373,0.000846921,0.002695591,0.0015056554],"domain_scores_gemma":[0.98784083,0.0048298505,0.00040319265,0.00056279567,0.005457657,0.00090568507],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.012764841,0.0002774572,0.00076849665,0.0017586849,0.0012618017,0.000095539835,0.00085482426,0.00036104632,0.00017565777],"category_scores_gemma":[0.0014619973,0.00028810443,0.00034590554,0.0049731364,0.0014830589,0.002391819,0.000009822146,0.0007271264,0.000002669538],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043409166,0.00044264444,0.94218653,0.00048038276,0.00024171438,0.0000011107421,0.04315948,0.00042094517,0.0047510113,0.007175487,0.00013894176,0.0005676356],"study_design_scores_gemma":[0.00047951235,0.00027691436,0.9822125,0.00021088618,0.00038073314,1.4616771e-8,0.012798121,0.00024284326,0.0011616652,0.0004714938,0.0015021126,0.00026324703],"about_ca_topic_score_codex":0.021995574,"about_ca_topic_score_gemma":0.046946097,"teacher_disagreement_score":0.0400259,"about_ca_system_score_codex":0.00016022159,"about_ca_system_score_gemma":0.0006889535,"threshold_uncertainty_score":0.9999571},"labels":[],"label_agreement":null},{"id":"W629869814","doi":"","title":"Design of Light-Rail Transit Signal Priority to Improve Arterial Traffic Mobility","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"VisSim; Preemption; Intersection (aeronautics); Transit (satellite); Transport engineering; Light rail transit; Public transport; Reliability (semiconductor); Signal timing; Computer science; Engineering; Real-time computing; Traffic signal","score_opus":0.03992808178393959,"score_gpt":0.3253704689680129,"score_spread":0.28544238718407333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W629869814","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84834254,0.00024685232,0.14158234,0.0005982824,0.0006312677,0.0044797678,0.00049059116,0.0026187988,0.0010095711],"genre_scores_gemma":[0.991061,0.00026409118,0.0068243262,0.0000319359,0.00036166917,0.0010139421,0.00017257164,0.00013148121,0.00013900739],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99122596,0.0009122015,0.0015190796,0.0008261368,0.0034673242,0.0020493155],"domain_scores_gemma":[0.9957487,0.0006079451,0.00011315253,0.00069104973,0.0018204333,0.0010187427],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.008028445,0.00051028014,0.0006860307,0.0015655508,0.00045227952,0.000114579656,0.00077508925,0.00042392785,0.0002960802],"category_scores_gemma":[0.00011702784,0.00054766255,0.00025858733,0.0023167045,0.00045111918,0.001170906,0.000014650181,0.0014764708,0.00011227628],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0066347294,0.0038407522,0.008691557,0.004951253,0.0009062629,0.00011225412,0.080807984,0.16686435,0.578141,0.008133625,0.084698245,0.056218013],"study_design_scores_gemma":[0.00885763,0.005046091,0.5347646,0.0011927998,0.00037410573,0.0000020112866,0.021160858,0.021927986,0.31829873,0.00083388586,0.08391978,0.0036215591],"about_ca_topic_score_codex":0.0006697539,"about_ca_topic_score_gemma":0.0011012459,"teacher_disagreement_score":0.52607304,"about_ca_system_score_codex":0.00028396142,"about_ca_system_score_gemma":0.00023053001,"threshold_uncertainty_score":0.9996975},"labels":[],"label_agreement":null},{"id":"W631000591","doi":"","title":"Investigation of Piezoelectric Weigh-in-Motion Sensors’ Performance in Asphalt Concrete Pavements in Cold Temperatures of Southern Ontario","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Weigh in motion; Asphalt; Calibration; Piezoelectric sensor; Full scale; Piezoelectricity; Axle; Sensitivity (control systems); Environmental science; Ceramic; Transverse plane; Automotive engineering; Structural engineering; Engineering; Acoustics; Materials science; Composite material; Electrical engineering; Electronic engineering","score_opus":0.03450190798090175,"score_gpt":0.2906104585238668,"score_spread":0.25610855054296505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W631000591","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99767303,0.00008734188,0.000010293195,0.00008876451,0.00016662249,0.0015502941,0.000091128335,0.000027817183,0.00030469036],"genre_scores_gemma":[0.9984961,0.00013602982,0.0006732397,0.000013012083,0.000043980966,0.00023389077,0.00019003611,0.00004515154,0.00016853609],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99247736,0.0011480817,0.0016529139,0.00063626096,0.0028030325,0.0012823247],"domain_scores_gemma":[0.99822074,0.00040361026,0.0003351564,0.00034732447,0.00042635365,0.000266822],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.007576188,0.0002959922,0.0005287393,0.0015531157,0.0001194127,0.000024454584,0.0003826608,0.00028429696,0.00087618054],"category_scores_gemma":[0.00016062414,0.0003191407,0.00009248198,0.0026954985,0.0008331146,0.0011567051,0.000017974404,0.0011254618,0.00007833048],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00059725007,0.00008734255,0.91211575,0.00025688278,0.000012335571,0.000014218095,0.022224354,0.0011449071,0.0630326,0.0002130956,0.000057762147,0.00024350798],"study_design_scores_gemma":[0.0016007603,0.00027933953,0.94281024,0.0003217275,0.000009188599,4.121857e-7,0.0036951178,0.00018535511,0.050459456,0.000112457696,0.0002835462,0.00024240198],"about_ca_topic_score_codex":0.23206022,"about_ca_topic_score_gemma":0.37699187,"teacher_disagreement_score":0.14493166,"about_ca_system_score_codex":0.0012469498,"about_ca_system_score_gemma":0.00032795043,"threshold_uncertainty_score":0.9999261},"labels":[],"label_agreement":null},{"id":"W632216912","doi":"","title":"Assessing Time and Weather Effects on Collision Frequency by Severity in Edmonton Using Multivariate Safety Performance Functions","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Traffic and Road Safety","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Multivariate statistics; Proxy (statistics); Snow; Collision; Multivariate analysis; Environmental science; Precipitation; Statistics; Regression analysis; Meteorology; Econometrics; Climatology; Mathematics; Geography; Computer science","score_opus":0.033358281638213645,"score_gpt":0.3337010655413501,"score_spread":0.30034278390313646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W632216912","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99400455,0.00061714085,0.0010103199,0.00020812164,0.00026486377,0.0013981317,0.0003734437,0.00033359564,0.0017898371],"genre_scores_gemma":[0.99642193,0.00057759567,0.0017084264,0.000026490728,0.00019882893,0.00015946776,0.00048092246,0.00012984073,0.00029652216],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9935333,0.000864902,0.00094701146,0.0007091248,0.0021564756,0.0017891938],"domain_scores_gemma":[0.99707377,0.0011626359,0.00008992863,0.0003872534,0.0006762415,0.00061016507],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0048232,0.00046389445,0.0005258924,0.0009959484,0.00096192205,0.00016409275,0.00029670907,0.00043794757,0.00014999494],"category_scores_gemma":[0.0001372003,0.00046768217,0.00011295455,0.0018065115,0.00036627197,0.0021154988,0.000011458406,0.0019452823,0.00010433758],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022340391,0.0015030834,0.69978297,0.002996865,0.00034036272,0.0001358796,0.02794798,0.09478658,0.12501942,0.00080140104,0.005596016,0.038855445],"study_design_scores_gemma":[0.0017865656,0.00025966443,0.9716866,0.0007347643,0.000031611064,7.9275225e-7,0.0021796077,0.015947258,0.003995558,0.00003200221,0.0027795103,0.0005660379],"about_ca_topic_score_codex":0.0041417554,"about_ca_topic_score_gemma":0.0018777068,"teacher_disagreement_score":0.2719037,"about_ca_system_score_codex":0.0004554684,"about_ca_system_score_gemma":0.00017116035,"threshold_uncertainty_score":0.9997775},"labels":[],"label_agreement":null},{"id":"W636224762","doi":"","title":"Is It Safe? How Does Safety Play a Role in a Child’s Mode of Travel Between Home and School?","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Thematic analysis; Population; Psychology; Safety behaviors; Human factors and ergonomics; Poison control; Applied psychology; Social psychology; Qualitative research; Environmental health; Sociology; Medicine","score_opus":0.056266836422232444,"score_gpt":0.3960877437661518,"score_spread":0.33982090734391934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W636224762","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97843903,0.0006071238,0.00014826584,0.0090356665,0.00011989067,0.002098161,0.0015996691,0.000076143464,0.007876022],"genre_scores_gemma":[0.99473697,0.0012442779,0.000869696,0.00006739967,0.0004683681,0.00024190563,0.00037724475,0.000075821394,0.0019183403],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9876278,0.0018306223,0.0015843026,0.0011564575,0.0051652715,0.0026355584],"domain_scores_gemma":[0.9939626,0.0015481769,0.00031245025,0.0005865678,0.002139299,0.0014509199],"candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.011775854,0.00047863313,0.0009522325,0.0016762633,0.0015064641,0.0002150528,0.00095330685,0.00063352444,0.0013312891],"category_scores_gemma":[0.00047152807,0.0004413839,0.0002888072,0.0031746211,0.002489299,0.0025011431,0.000020376256,0.00229417,0.000050497223],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006677423,0.000354507,0.89141357,0.00038961932,0.00007739706,0.000021138841,0.10191748,0.000014319911,0.0006147971,0.00284783,0.0005357119,0.0011458843],"study_design_scores_gemma":[0.0015477451,0.00016538825,0.9162907,0.00038223556,0.000045240213,8.1525876e-8,0.06961983,0.000015175593,0.001669246,0.0022052005,0.0075823036,0.00047685485],"about_ca_topic_score_codex":0.07374144,"about_ca_topic_score_gemma":0.15409698,"teacher_disagreement_score":0.08035553,"about_ca_system_score_codex":0.00033445618,"about_ca_system_score_gemma":0.00090333895,"threshold_uncertainty_score":0.9998038},"labels":[],"label_agreement":null},{"id":"W636679090","doi":"","title":"Use of CANDE and Design Codes to Assess Stability of Deteriorated Metal Culverts","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Geotechnical Engineering and Underground Structures","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Culvert; Thrust; Finite element method; Structural engineering; Engineering; Compression (physics); Geotechnical engineering; Design load; Numerical analysis; Geology; Materials science; Mathematics; Mechanical engineering; Composite material","score_opus":0.1408358233529041,"score_gpt":0.3539686987651376,"score_spread":0.2131328754122335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W636679090","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97490263,0.0003040972,0.02284887,0.00008663286,0.000117974334,0.0010792352,0.00038610442,0.00019442043,0.000080006896],"genre_scores_gemma":[0.98771274,0.00024369673,0.011642341,0.00000674773,0.000043746513,0.0001544089,0.000092024056,0.0000711181,0.000033176948],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9947993,0.00059176376,0.0010080023,0.00043670437,0.0020124733,0.0011517619],"domain_scores_gemma":[0.99544895,0.0015161426,0.00008294219,0.00042427078,0.0018676315,0.00066005974],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0039617843,0.00031907312,0.00060478726,0.00086350203,0.00019902778,0.00006542693,0.000312137,0.0002758719,0.00008744001],"category_scores_gemma":[0.0005203604,0.000314211,0.00012221205,0.0016588017,0.0005572202,0.00077317224,0.00001295267,0.0008706251,0.000004300172],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016696741,0.0004919615,0.13431138,0.0036592563,0.0005230255,0.000033990473,0.017649602,0.21200529,0.6186766,0.004779648,0.0013080739,0.004891521],"study_design_scores_gemma":[0.00076024287,0.00065490045,0.78042686,0.00031911524,0.000070914684,8.1223135e-7,0.0029668463,0.004063454,0.20787787,0.00035718392,0.0019426438,0.00055913697],"about_ca_topic_score_codex":0.004824565,"about_ca_topic_score_gemma":0.0026984997,"teacher_disagreement_score":0.6461155,"about_ca_system_score_codex":0.000108628534,"about_ca_system_score_gemma":0.00014794798,"threshold_uncertainty_score":0.999931},"labels":[],"label_agreement":null},{"id":"W638548272","doi":"","title":"Effects of a Feedback/Reward System on Speed Compliance Rates and the Degree of Speeding during Noncompliance","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Traffic and Road Safety","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Headway; Speed limit; Driving simulator; Compliance (psychology); Limit (mathematics); Crash; Degree (music); Simulation; Computer science; Psychology; Control theory (sociology); Engineering; Mathematics; Social psychology; Control (management); Transport engineering","score_opus":0.0730360739613509,"score_gpt":0.3335008493253044,"score_spread":0.2604647753639535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W638548272","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99301237,0.0019443417,0.00037880108,0.00021985538,0.00029028274,0.0018704917,0.00016785997,0.00022817217,0.0018878405],"genre_scores_gemma":[0.9976707,0.00091155194,0.00077188195,0.000006826202,0.00020756779,0.00014423348,0.00004222928,0.00009610817,0.00014888734],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9936137,0.0006859719,0.0012211772,0.0005093491,0.0025766736,0.0013931331],"domain_scores_gemma":[0.99486274,0.0026587443,0.00020725724,0.00044584495,0.0013962149,0.00042921293],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00450119,0.00040443186,0.000810815,0.0007104409,0.000561796,0.000051054813,0.0005825836,0.00023763126,0.000027570637],"category_scores_gemma":[0.00021220412,0.00032839327,0.0002219654,0.0015926062,0.0014747335,0.0005188375,0.000016341473,0.0013063245,0.00003760266],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.020656979,0.0016212345,0.46951684,0.08214714,0.0019420693,0.0002602684,0.11490898,0.05982513,0.14057176,0.09384989,0.0031043035,0.01159542],"study_design_scores_gemma":[0.004251108,0.00021684573,0.94086134,0.0022945183,0.0000621932,0.0000012799711,0.008066647,0.0014076157,0.04213703,0.00007026716,0.00029357214,0.00033757978],"about_ca_topic_score_codex":0.0011928498,"about_ca_topic_score_gemma":0.0004753015,"teacher_disagreement_score":0.4713445,"about_ca_system_score_codex":0.00016152057,"about_ca_system_score_gemma":0.000091986934,"threshold_uncertainty_score":0.9999168},"labels":[],"label_agreement":null},{"id":"W638843832","doi":"","title":"Winter Cycling in North American Cities: Climate and Roadway Surface Conditions","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Cycling; Environmental science; Precipitation; Snow; Population; Geography; Meteorology; Climatology; Demography","score_opus":0.06599496726980868,"score_gpt":0.41574197577712474,"score_spread":0.34974700850731605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W638843832","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9914418,0.0004070179,0.000057284284,0.0017349235,0.00020050863,0.0016714535,0.0006961961,0.00023396661,0.003556887],"genre_scores_gemma":[0.99597675,0.0014266352,0.000680671,0.00009363778,0.00037194113,0.00026188535,0.0005443402,0.00008218323,0.0005619749],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9885113,0.0020583726,0.0013670702,0.0010532085,0.0037332212,0.0032767933],"domain_scores_gemma":[0.9944505,0.0018386552,0.0002492075,0.00049033546,0.001768563,0.0012027001],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":["sts"],"category_scores_codex":[0.011065366,0.00042048338,0.00066906627,0.0011729194,0.0022505152,0.0003023193,0.00070122624,0.0002562952,0.000513288],"category_scores_gemma":[0.00042568575,0.0004520565,0.00019951967,0.004509701,0.0040624673,0.0024787837,0.000019741386,0.0020468303,0.0001007842],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003447383,0.00033697987,0.93191355,0.00020114043,0.000036888283,0.000041965897,0.062851384,0.00016332703,0.0002692068,0.0024465495,0.00042936878,0.00096490106],"study_design_scores_gemma":[0.00078278914,0.0001509813,0.92662203,0.00014378513,0.000024406181,7.998774e-8,0.065027855,0.000022448405,0.00023770488,0.0002693615,0.006279018,0.00043952384],"about_ca_topic_score_codex":0.062094722,"about_ca_topic_score_gemma":0.56862307,"teacher_disagreement_score":0.5065284,"about_ca_system_score_codex":0.00036291513,"about_ca_system_score_gemma":0.0005519239,"threshold_uncertainty_score":0.9997931},"labels":[],"label_agreement":null},{"id":"W640143065","doi":"","title":"How Are We Doing? Opinion Mining Customer Sentiment in US Transit Agencies and Airlines via Twitter","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Sentiment analysis; Lexicon; Cluster analysis; Social media; Simple (philosophy); Advertising; Transit (satellite); Computer science; Public opinion; Business; Data science; Political science; Artificial intelligence; World Wide Web; Public transport; Law","score_opus":0.09195928560226266,"score_gpt":0.3939173482296893,"score_spread":0.30195806262742664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W640143065","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97364956,0.0020586653,0.0054039136,0.013511041,0.0006421416,0.0021792646,0.00020993092,0.0004220525,0.001923426],"genre_scores_gemma":[0.9875962,0.003700873,0.005221669,0.00012682416,0.0005563304,0.00040502616,0.00044630986,0.00009857823,0.0018481901],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9891557,0.0018740814,0.0011313881,0.0010289593,0.0043707923,0.0024390637],"domain_scores_gemma":[0.9950639,0.0011054227,0.00030131402,0.00038271045,0.002184373,0.00096226996],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.008587228,0.0004873218,0.0006194276,0.002052565,0.0018402741,0.00046171076,0.00049897854,0.0005312286,0.0001940139],"category_scores_gemma":[0.0002360061,0.00052112987,0.00019257526,0.0031406851,0.0013689861,0.0025155223,0.000010304817,0.001415328,0.000046412602],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005525077,0.00038202794,0.7806096,0.0005422394,0.00008160657,0.000078045356,0.20255034,0.0037117498,0.0006851336,0.002055545,0.004821918,0.0039292886],"study_design_scores_gemma":[0.001703914,0.00016623427,0.7104014,0.00067931315,0.00004289825,6.582772e-7,0.15387654,0.000464829,0.0004991112,0.00014667187,0.13130479,0.00071364077],"about_ca_topic_score_codex":0.012920065,"about_ca_topic_score_gemma":0.045606695,"teacher_disagreement_score":0.12648286,"about_ca_system_score_codex":0.00035948466,"about_ca_system_score_gemma":0.0004722944,"threshold_uncertainty_score":0.99972403},"labels":[],"label_agreement":null},{"id":"W640379923","doi":"","title":"P-TRANE: Modeling Bus Transit Network Evolution in a GIS-Based Framework","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Transit (satellite); Transport engineering; Component (thermodynamics); Public transport; Service (business); Computer science; Process (computing); Geographic information system; Overcrowding; Engineering; Geography; Business","score_opus":0.07729415988429858,"score_gpt":0.4030854607749061,"score_spread":0.3257913008906075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W640379923","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8731603,0.0014815689,0.11370531,0.003439814,0.0007873317,0.0030004794,0.00028545508,0.00067344843,0.0034662818],"genre_scores_gemma":[0.98317367,0.0005804168,0.013016896,0.00014141333,0.0010118737,0.00068505167,0.00082611584,0.00014811511,0.00041644156],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9829169,0.0033973786,0.0018758551,0.0012430812,0.006420207,0.0041465973],"domain_scores_gemma":[0.9919615,0.0023214666,0.00025806087,0.00063967524,0.003522907,0.0012963926],"candidate_categories":["metaepi_narrow","sts","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.019144278,0.0005740744,0.0007373097,0.0021929736,0.0028214604,0.00029994617,0.00092990417,0.0010161026,0.00067625125],"category_scores_gemma":[0.0009078176,0.00066842773,0.00034618977,0.0073377443,0.0012212027,0.0022189445,0.0000065106974,0.003235281,0.0001696121],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001292761,0.00068982405,0.35755387,0.0003060221,0.00006009234,0.00007215831,0.07542299,0.50104994,0.00016494401,0.06146839,0.000823906,0.0010950834],"study_design_scores_gemma":[0.0037769,0.00048398037,0.86053306,0.0019384663,0.00011979493,4.3243705e-7,0.086971335,0.018187685,0.00017954245,0.008851679,0.017234005,0.0017231113],"about_ca_topic_score_codex":0.05963474,"about_ca_topic_score_gemma":0.12746905,"teacher_disagreement_score":0.5029792,"about_ca_system_score_codex":0.0008514333,"about_ca_system_score_gemma":0.0017434026,"threshold_uncertainty_score":0.9995767},"labels":[],"label_agreement":null},{"id":"W651512165","doi":"","title":"Exploring Changes Affecting Travel Behavior of Seniors","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Cohort effect; Cohort; Population ageing; Population; Demography; Public transport; Period (music); Geography; Gerontology; Demographic economics; Transport engineering; Medicine; Economics; Sociology; Engineering","score_opus":0.23370607897455012,"score_gpt":0.4356159157640858,"score_spread":0.2019098367895357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W651512165","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9906096,0.0004782772,0.0002150329,0.0010438191,0.00059684075,0.0023976443,0.00033624982,0.00025649968,0.004066047],"genre_scores_gemma":[0.9948829,0.00083101034,0.0011203748,0.000024737266,0.0008895443,0.0010028426,0.00023945306,0.000109392146,0.0008997705],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9858977,0.0021965674,0.0013613785,0.0009925222,0.0064074593,0.00314436],"domain_scores_gemma":[0.99196196,0.0019014955,0.0003488552,0.0006464196,0.0038943102,0.0012469649],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.017615035,0.0004542786,0.0007512159,0.0016865416,0.002309012,0.0001563648,0.0010168742,0.00041547563,0.0008479662],"category_scores_gemma":[0.0007145446,0.00048193004,0.00035581447,0.0041098846,0.0023529322,0.0029235454,0.000016879134,0.0019715428,0.000077441604],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040046938,0.00082339434,0.8492944,0.0005079991,0.00007229383,0.00004206854,0.12726876,0.000027102018,0.008353768,0.0057644146,0.00035627245,0.0070890347],"study_design_scores_gemma":[0.000745707,0.00024705776,0.87122566,0.0002516025,0.00007225352,8.427099e-8,0.106791414,0.000004338784,0.013602082,0.00017888722,0.006433912,0.00044703248],"about_ca_topic_score_codex":0.067568235,"about_ca_topic_score_gemma":0.09992935,"teacher_disagreement_score":0.032361113,"about_ca_system_score_codex":0.00033818523,"about_ca_system_score_gemma":0.0007145552,"threshold_uncertainty_score":0.99976325},"labels":[],"label_agreement":null},{"id":"W657606557","doi":"","title":"Microscopic Analysis on the Causal Factors of Capacity Drop in Highway Merging Sections","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Drop (telecommunication); Bottleneck; Mechanics; Breakup; Environmental science; Computer science; Engineering; Physics; Operations management; Mechanical engineering","score_opus":0.06089647938680954,"score_gpt":0.33950192618590935,"score_spread":0.2786054467990998,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W657606557","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99070644,0.00012034569,0.003981235,0.0003852669,0.00025428119,0.0011262618,0.00033434806,0.00089929905,0.0021924968],"genre_scores_gemma":[0.9983457,0.0003236257,0.00042034796,0.000021055544,0.000088505025,0.00035927392,0.0002264621,0.00006503685,0.0001499966],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9941275,0.0007384114,0.0009975022,0.0004809413,0.0023317994,0.0013238568],"domain_scores_gemma":[0.9971441,0.0010735568,0.00010231259,0.0005494691,0.00079901493,0.00033152246],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.004808338,0.0003334055,0.00048637865,0.0029831873,0.00048539648,0.00007429179,0.0005284823,0.00024395832,0.0001925299],"category_scores_gemma":[0.00016670424,0.00028829713,0.00026665328,0.005503192,0.0005587861,0.00061506906,0.000010127948,0.001676439,0.000028959977],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002576277,0.0009514911,0.8330417,0.0008287572,0.001240107,0.000024548246,0.038089797,0.04838134,0.024486627,0.036162876,0.015648397,0.00088670995],"study_design_scores_gemma":[0.0004462765,0.00016429879,0.9613592,0.0001447849,0.00010299397,6.3629024e-8,0.008014797,0.0020666907,0.022745766,0.000112543974,0.0045439373,0.00029864386],"about_ca_topic_score_codex":0.007269778,"about_ca_topic_score_gemma":0.021230536,"teacher_disagreement_score":0.12831748,"about_ca_system_score_codex":0.00027950443,"about_ca_system_score_gemma":0.00007861559,"threshold_uncertainty_score":0.9999569},"labels":[],"label_agreement":null},{"id":"W65872913","doi":"","title":"Identifying High Collision Locations Without Traffic Volume Data","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Traffic and Road Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Collision; Computer science; Traffic volume; Volume (thermodynamics); Negative binomial distribution; Binomial distribution; Overdispersion; Simulation; Data mining; Transport engineering; Statistics; Engineering; Computer security; Mathematics","score_opus":0.09699712958836344,"score_gpt":0.3772918317837832,"score_spread":0.2802947021954198,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W65872913","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98213387,0.0015323116,0.008064836,0.00081547,0.0010235328,0.0019978872,0.0017487358,0.0013116339,0.001371726],"genre_scores_gemma":[0.9859461,0.0013971719,0.005619866,0.00002891453,0.0007598345,0.00039502312,0.004205108,0.00024609064,0.001401852],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.98872197,0.000877286,0.0015618444,0.0011931102,0.004753842,0.0028919464],"domain_scores_gemma":[0.9940093,0.0008105564,0.00013843215,0.0016845538,0.0021416026,0.0012155672],"candidate_categories":["metaepi_narrow","sts","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.008316629,0.00060229603,0.00068239874,0.0015794274,0.0015669367,0.00029564864,0.0017963994,0.00053605984,0.0006301415],"category_scores_gemma":[0.00024493402,0.00063288014,0.00019539209,0.0032370868,0.0008745794,0.00307519,0.00004753594,0.0026061994,0.0009946683],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015837863,0.002382116,0.39771152,0.0040237405,0.0011307747,0.00023202434,0.055949114,0.3078604,0.00604224,0.014508195,0.1723727,0.036203396],"study_design_scores_gemma":[0.001962572,0.00022185167,0.89114636,0.0004656138,0.00012274607,0.000001915639,0.014736331,0.013607117,0.0010767014,0.00019122305,0.07538953,0.0010780385],"about_ca_topic_score_codex":0.002961039,"about_ca_topic_score_gemma":0.008842607,"teacher_disagreement_score":0.49343485,"about_ca_system_score_codex":0.00037402898,"about_ca_system_score_gemma":0.00041599452,"threshold_uncertainty_score":0.99978316},"labels":[],"label_agreement":null},{"id":"W766256399","doi":"","title":"Investigating the Link Between Cyclist Volumes and Pollution Levels Along Bicycle Facilities in Dense Urban Core","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Cycling; Environmental science; Air pollution; Nitrogen oxides; Pollution; Nitrogen dioxide; Particulates; Transport engineering; Environmental health; Geography; Meteorology; Engineering; Waste management; Forestry","score_opus":0.09262236356404123,"score_gpt":0.3499600137332155,"score_spread":0.25733765016917426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W766256399","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99403733,0.0013626545,0.00018074716,0.0017569894,0.00014739885,0.0010225807,0.00061626534,0.0002461348,0.00062988873],"genre_scores_gemma":[0.9970151,0.00043039085,0.0006707356,0.000030101422,0.00072538055,0.00027292487,0.00024493266,0.00008829935,0.0005221412],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9938072,0.0005688725,0.0010990971,0.00053463463,0.0021560807,0.0018341343],"domain_scores_gemma":[0.9970222,0.0009861537,0.00009328064,0.0004522929,0.000772858,0.0006732301],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.006615354,0.000383927,0.0004373827,0.0009124513,0.0011301537,0.00018890148,0.00047251486,0.00033998393,0.00012251605],"category_scores_gemma":[0.00035107075,0.00034044211,0.00010933237,0.0019807087,0.001068239,0.0013169429,0.000019647763,0.002216275,0.00005362799],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049179835,0.000027714459,0.9488439,0.00055040774,0.00004715528,0.000011915756,0.030191919,0.0027824847,0.0032503265,0.00095529255,0.001319716,0.011969977],"study_design_scores_gemma":[0.0006646801,0.00010026726,0.9680827,0.00032916563,0.000016424267,6.399099e-7,0.0118331155,0.0027395983,0.0015910718,0.00048907916,0.013779124,0.00037413562],"about_ca_topic_score_codex":0.0078024007,"about_ca_topic_score_gemma":0.010829659,"teacher_disagreement_score":0.019238787,"about_ca_system_score_codex":0.00020784269,"about_ca_system_score_gemma":0.00019499505,"threshold_uncertainty_score":0.99990475},"labels":[],"label_agreement":null},{"id":"W783011726","doi":"","title":"Estimating intersection delays to transit vehicles using archived AVL/APC data","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Transit (satellite); Bus priority; Transport engineering; Intersection (aeronautics); Public transport; Queue; Computer science; Prioritization; Service (business); Real-time computing; Engineering; Computer network","score_opus":0.11810147212221835,"score_gpt":0.3888203689650491,"score_spread":0.2707188968428308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W783011726","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.72911465,0.00021118287,0.26214457,0.00045000264,0.00073546224,0.0019692702,0.0006687487,0.0031050032,0.0016011219],"genre_scores_gemma":[0.9552464,0.00014933934,0.042308643,0.00007104079,0.00062306155,0.00033240148,0.00097436924,0.00018191405,0.00011287007],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9919088,0.000669662,0.0012458004,0.0009970834,0.002994621,0.0021840392],"domain_scores_gemma":[0.9961598,0.0005399975,0.00009715664,0.0010883363,0.0010791856,0.0010355304],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0066003874,0.0005054495,0.00051183114,0.0021370556,0.0008987376,0.00024749918,0.0012713178,0.0002993076,0.0001327485],"category_scores_gemma":[0.00022744646,0.0005656175,0.00016493985,0.0020217537,0.00039556634,0.0022591178,0.000050383696,0.0018581545,0.00015796849],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023560259,0.0016799641,0.0826639,0.004409535,0.0012561809,0.00026010638,0.10007444,0.39092234,0.13550106,0.008309781,0.16321814,0.109348536],"study_design_scores_gemma":[0.003330157,0.0009618405,0.42100093,0.0018124428,0.00029913065,0.000006198575,0.025633786,0.46220496,0.014123333,0.00071029284,0.06736868,0.0025482543],"about_ca_topic_score_codex":0.00348899,"about_ca_topic_score_gemma":0.006704076,"teacher_disagreement_score":0.33833703,"about_ca_system_score_codex":0.00037099933,"about_ca_system_score_gemma":0.00015845225,"threshold_uncertainty_score":0.9996795},"labels":[],"label_agreement":null},{"id":"W813784564","doi":"","title":"Analysis of U.S. Truck Size and Weight Policy in Relation to Vehicle Mass","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Truck; Productivity; Fuel efficiency; Axle; Inefficiency; Transport engineering; Articulated vehicle; Tractor; Engineering; Agricultural economics; Automotive engineering; Business; Economics; Economic growth","score_opus":0.02984668188431554,"score_gpt":0.3421620304937034,"score_spread":0.31231534860938787,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W813784564","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9957026,0.00046332128,0.00045423157,0.0006526594,0.000084769425,0.0007842712,0.0002687909,0.000121881414,0.0014674594],"genre_scores_gemma":[0.99655336,0.0009121491,0.0016802491,0.000026669404,0.00014754069,0.00019514469,0.00014628225,0.00006611495,0.0002724837],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9946397,0.00039868875,0.0010658768,0.00048502086,0.0020230776,0.0013876666],"domain_scores_gemma":[0.9968987,0.0010084888,0.000078697274,0.00041679607,0.0008663936,0.0007308936],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.004399382,0.00028360574,0.0005562388,0.003514476,0.0002828627,0.00005580112,0.00033164167,0.00027875576,0.00026844378],"category_scores_gemma":[0.0003077631,0.0002964412,0.00014757618,0.008470642,0.00027744932,0.00090731983,0.00001015787,0.0010554238,0.000035490808],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032485416,0.00012954518,0.91206765,0.0003926482,0.00021315104,0.000011614298,0.015060833,0.045031358,0.021376908,0.0016924839,0.00034249903,0.0033564705],"study_design_scores_gemma":[0.0006765164,0.00013637515,0.9826766,0.00014234634,0.00006260588,9.659481e-8,0.0021507668,0.0064788004,0.0034021502,0.00016072944,0.0038269951,0.00028600075],"about_ca_topic_score_codex":0.0052567753,"about_ca_topic_score_gemma":0.0055612414,"teacher_disagreement_score":0.07060898,"about_ca_system_score_codex":0.0002247804,"about_ca_system_score_gemma":0.00015202357,"threshold_uncertainty_score":0.9999488},"labels":[],"label_agreement":null},{"id":"W845890631","doi":"","title":"An Evaluation of the Impacts of Introducing a New Transit System on Commuting Mode Choice and Transit Ridership: A Case Study of the VIVA BRT-Lite System in Toronto","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"TRIPS architecture; Transit (satellite); Public transport; Transport engineering; Ticket; Service (business); Work (physics); Mode choice; Mode (computer interface); Business; Transit system; Geography; Computer science; Marketing; Engineering; Computer security","score_opus":0.09567294675971046,"score_gpt":0.4336774062137098,"score_spread":0.3380044594539994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W845890631","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9939483,0.00036867824,0.00025234776,0.00032845882,0.00022348877,0.0039817817,0.00019677012,0.00006965735,0.0006305535],"genre_scores_gemma":[0.99923337,0.000051597966,0.00026772975,0.000007904131,0.00015082452,0.00015159138,0.000048174003,0.00005313414,0.000035688157],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.98360306,0.00678543,0.0018075949,0.00066502346,0.0060617374,0.00107716],"domain_scores_gemma":[0.99310267,0.0015569667,0.0006337546,0.0007959481,0.0034445117,0.0004661453],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.020561663,0.00032687205,0.0006463056,0.0006252714,0.0012066402,0.0000773832,0.00074329285,0.00030184045,0.00004112514],"category_scores_gemma":[0.0005862363,0.000265112,0.00018876321,0.0025731314,0.00072866894,0.0012453387,0.000007875038,0.0009904319,7.9451235e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00064948335,0.00077602273,0.48366198,0.0010336977,0.00009393488,0.000011243072,0.44354495,0.06299143,0.0015952715,0.0042054257,0.00003279161,0.0014037659],"study_design_scores_gemma":[0.002211913,0.0004593854,0.51679736,0.0011192695,0.00015509759,0.0000011772812,0.4755251,0.0025085437,0.0009880203,0.000017342412,0.00003323813,0.00018356447],"about_ca_topic_score_codex":0.5312735,"about_ca_topic_score_gemma":0.6781485,"teacher_disagreement_score":0.14687502,"about_ca_system_score_codex":0.0007619611,"about_ca_system_score_gemma":0.0011536053,"threshold_uncertainty_score":0.9999801},"labels":[],"label_agreement":null},{"id":"W92661221","doi":"","title":"Evaluation of Accuracy of Weigh-in-Motion Systems in Alberta, Canada, and Its Effects on Pavement Design","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Transport Systems and Technology","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Weigh in motion; Axle; Truck; Engineering; Asphalt pavement; Transport engineering; Asphalt; Structural engineering; Automotive engineering; Geography","score_opus":0.05874193986337663,"score_gpt":0.3351460362399476,"score_spread":0.276404096376571,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W92661221","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99309564,0.002544003,0.00025182494,0.00012264437,0.0003478714,0.0031956513,0.00010511029,0.000053838543,0.00028342192],"genre_scores_gemma":[0.99825054,0.00050312595,0.00013011854,0.000004762401,0.000061968065,0.00083437964,0.00011072845,0.00006859365,0.000035787227],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9908213,0.0014233327,0.0015279352,0.0005126965,0.004491158,0.0012235485],"domain_scores_gemma":[0.99497736,0.0021705586,0.00019484694,0.00037549876,0.0019959556,0.00028575762],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.012426527,0.00033522447,0.0006719992,0.0017628494,0.00008378362,0.000015495281,0.00031927772,0.00034013207,0.000060510316],"category_scores_gemma":[0.00049357495,0.0003514219,0.00007286422,0.0014699096,0.00016811037,0.00053981954,0.0000052579676,0.0009819579,0.0000067442115],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009593391,0.001133604,0.6745393,0.0109345075,0.000402829,0.0001075732,0.022040261,0.19875775,0.045417078,0.02922452,0.0008399432,0.015643243],"study_design_scores_gemma":[0.0023751783,0.00036406034,0.9505826,0.0012413848,0.00005323191,3.7949795e-7,0.0020343647,0.008967521,0.033220436,0.00019004186,0.0006332395,0.00033752134],"about_ca_topic_score_codex":0.6034866,"about_ca_topic_score_gemma":0.79453784,"teacher_disagreement_score":0.2760433,"about_ca_system_score_codex":0.0008629106,"about_ca_system_score_gemma":0.0007170438,"threshold_uncertainty_score":0.9998938},"labels":[],"label_agreement":null}]}