{"meta":{"query_hash":"368865f31ced","filters":{"venue":"Computational Urban Science"},"cohort_total":6,"direct_labels_cover":0,"predictions_cover":6,"exported":6,"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/368865f31ced","api":"https://metacan.xera.ac/api/v1/cohort?venue=Computational+Urban+Science"},"results":[{"id":"W4283650591","doi":"10.1007/s43762-022-00047-w","title":"Points of Interest (POI): a commentary on the state of the art, challenges, and prospects for the future","year":2022,"lang":"en","type":"article","venue":"Computational Urban Science","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":144,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Georgia Institute of Technology; National Science Foundation","keywords":"Geospatial analysis; Geolocation; Point of interest; Data science; Fidelity; Computer science; Urban planning; Representation (politics); Geovisualization; Quality (philosophy); Data mining; Cartography; Geography; World Wide Web; Artificial intelligence; Visualization; Political science; Information visualization; Engineering","score_opus":0.05305880247960296,"score_gpt":0.29861803652621266,"score_spread":0.2455592340466097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283650591","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001205565,0.011583207,0.0004936657,0.9607654,0.024975555,0.000007808154,0.00013716178,0.000013990807,0.0019027244],"genre_scores_gemma":[0.012651981,0.021524822,0.0013660868,0.89829004,0.060971487,0.0001572204,0.00020450393,0.00017387501,0.0046599465],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9648364,0.019919002,0.0031769683,0.003993538,0.006844448,0.001229636],"domain_scores_gemma":[0.7661057,0.20774522,0.0031849134,0.00269945,0.01760013,0.002664485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03307149,0.0012989802,0.0026569322,0.004193475,0.009029106,0.012353611,0.0072125667,0.037898127,0.005575662],"category_scores_gemma":[0.16884758,0.0009546243,0.0026687598,0.0071562775,0.02944842,0.019597227,0.008317537,0.05440849,0.0028004714],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002376633,0.0000035106655,0.000085566004,0.00050371484,0.000017070395,0.00015369909,0.0046597337,0.000084564446,0.000029522718,0.06347691,0.92359895,0.0073629464],"study_design_scores_gemma":[0.00001397948,0.000009122371,0.0001396166,0.0035311568,0.000021269861,0.00017762596,0.0037760334,0.00013997016,0.000050291368,0.027518392,0.96457237,0.00005016424],"about_ca_topic_score_codex":0.04505949,"about_ca_topic_score_gemma":0.044336345,"teacher_disagreement_score":0.04505949,"about_ca_system_score_codex":0.014295225,"about_ca_system_score_gemma":0.017694777,"threshold_uncertainty_score":0.17490083},"labels":[],"label_agreement":null},{"id":"W4385578400","doi":"10.1007/s43762-023-00101-1","title":"Urban cooling potential and cost comparison of heat mitigation techniques for their impact on the lower atmosphere","year":2023,"lang":"en","type":"article","venue":"Computational Urban Science","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Nuclear Safety and Security Commission; University of Texas at Austin; National Aeronautics and Space Administration; National Oceanic and Atmospheric Administration; National Science Foundation","keywords":"Urban heat island; Environmental science; Roof; Green roof; Albedo (alchemy); Meteorology; Weather Research and Forecasting Model; Atmospheric sciences; Vegetation (pathology); Urban climate; Thermal comfort; Metropolitan area; Urban planning; Civil engineering; Geography; Engineering","score_opus":0.019180181930593034,"score_gpt":0.28612733334500107,"score_spread":0.26694715141440806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385578400","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9932902,0.00016152067,0.002001594,0.000038964252,0.000008049536,0.000043439584,0.00059114356,0.000022511436,0.0038425964],"genre_scores_gemma":[0.998252,0.000061775085,0.0008844548,0.0000038695275,0.0000014343548,0.00002070122,0.00017110916,0.000004439021,0.0006002282],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99966145,0.00013346324,0.000012691159,0.00004141049,0.000072591436,0.000078431985],"domain_scores_gemma":[0.99957603,0.00022032327,0.000048246933,0.000032684045,0.00010637903,0.000016279002],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059096015,0.0005155472,0.00037604163,0.00076499005,0.00031859282,0.00065099855,0.0004937203,0.0002584947,0.0023425072],"category_scores_gemma":[0.00051418704,0.00016139183,0.0008054391,0.0010052827,0.00022267248,0.00040220562,0.00028202197,0.00023080668,0.00017429555],"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":[0.00076772016,0.000111870475,0.036935132,0.00021883195,0.00021786388,0.00019492759,0.00003714118,0.9231751,0.015106239,0.001363628,0.00041684968,0.02145457],"study_design_scores_gemma":[0.00013130001,0.001963923,0.23687029,0.00006401456,0.0005814,0.00020300044,0.0007094446,0.7059927,0.048280094,0.0014960972,0.0036080622,0.000099668345],"about_ca_topic_score_codex":0.024182104,"about_ca_topic_score_gemma":0.045766495,"teacher_disagreement_score":0.024182104,"about_ca_system_score_codex":0.002269597,"about_ca_system_score_gemma":0.00080689014,"threshold_uncertainty_score":0.04808271},"labels":[],"label_agreement":null},{"id":"W4387939046","doi":"10.1007/s43762-023-00109-7","title":"The impact of scale on extracting urban mobility patterns using texture analysis","year":2023,"lang":"en","type":"article","venue":"Computational Urban Science","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Economic and Social Research Council; Royal Society; Directorate for Biological Sciences; American Association of Geographers; McMaster University","keywords":"Geospatial analysis; Scale (ratio); Computer science; Trajectory; Big data; Spatial ecology; Data mining; Geography; Cartography","score_opus":0.043129270808238085,"score_gpt":0.39445480432926083,"score_spread":0.35132553352102275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387939046","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9015313,0.00029864447,0.09429474,0.00018795686,0.00007635632,0.0000849907,0.00085031445,0.000391577,0.002284152],"genre_scores_gemma":[0.9768511,0.0001262775,0.022329252,0.000022944725,0.000020419766,0.000021874663,0.00037679478,0.00002963839,0.00022172686],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995977,0.000100046054,0.000032439588,0.00008533441,0.000105024206,0.00007952722],"domain_scores_gemma":[0.99763453,0.001392991,0.00021923531,0.00024947792,0.00040624852,0.000097550415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008726656,0.00044578852,0.00037660592,0.002387141,0.00033800825,0.0014274999,0.00023889952,0.0002820099,0.0009016392],"category_scores_gemma":[0.005752281,0.0001692811,0.00060815964,0.0019025492,0.0004147933,0.0008789347,0.0007143275,0.00034341292,0.00021276032],"study_design_candidate":"simulation_or_modeling","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":[0.0013213395,0.0003186576,0.32238707,0.0005804877,0.0003930165,0.00077678653,0.0012215883,0.15897173,0.04985767,0.0046827463,0.0044135894,0.45507535],"study_design_scores_gemma":[0.000038079146,0.00014135604,0.21394949,0.000048507944,0.00015916202,0.00028579947,0.0012731134,0.7653302,0.012046058,0.0037647162,0.0029026195,0.000060908245],"about_ca_topic_score_codex":0.009362014,"about_ca_topic_score_gemma":0.010765305,"teacher_disagreement_score":0.009362014,"about_ca_system_score_codex":0.00030244296,"about_ca_system_score_gemma":0.00036285078,"threshold_uncertainty_score":0.018615067},"labels":[],"label_agreement":null},{"id":"W4408003273","doi":"10.1007/s43762-025-00171-3","title":"Advancing translational human dynamics research: bridging space, mind, and computational urban science in the era of GeoAI","year":2025,"lang":"en","type":"article","venue":"Computational Urban Science","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute on Governance","funders":"","keywords":"Bridging (networking); Space (punctuation); Dynamics (music); Cognitive science; Translational science; Data science; Sociology; Computer science; Psychology; Social science","score_opus":0.03316206218588967,"score_gpt":0.380432473137555,"score_spread":0.34727041095166533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408003273","genre_codex":"commentary","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029530765,0.09282362,0.11576472,0.69099325,0.010005544,0.00014032105,0.00035366867,0.00025081317,0.060137417],"genre_scores_gemma":[0.6752533,0.15091874,0.09763258,0.051819496,0.014104042,0.0005117291,0.00036050458,0.00026105388,0.009138576],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9922454,0.0060648806,0.00014996165,0.00040331675,0.00073391077,0.00040249157],"domain_scores_gemma":[0.9589382,0.032431424,0.0011426143,0.0026946713,0.0022007795,0.0025923434],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.024511917,0.000522295,0.00081458664,0.0025811153,0.0026806465,0.010223689,0.0015656152,0.003875759,0.007643815],"category_scores_gemma":[0.024656102,0.0003033393,0.0006166042,0.002161786,0.023887929,0.013013629,0.013489257,0.006982309,0.001097353],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049269325,0.00008818886,0.0025204178,0.00091698894,0.000035679364,0.00020004208,0.010429456,0.0014494102,0.0004355699,0.8522465,0.022545679,0.10908277],"study_design_scores_gemma":[0.000011459783,0.000046583467,0.0010097318,0.0015614455,0.000014393732,0.00014243436,0.009888575,0.0017307735,0.00037234355,0.82829046,0.15690579,0.0000259442],"about_ca_topic_score_codex":0.0024763306,"about_ca_topic_score_gemma":0.0038495169,"teacher_disagreement_score":0.024511917,"about_ca_system_score_codex":0.0040848446,"about_ca_system_score_gemma":0.011396883,"threshold_uncertainty_score":0.12963295},"labels":[],"label_agreement":null},{"id":"W4412808955","doi":"10.1007/s43762-025-00193-x","title":"Reassessing Christopher Alexander’s theory of urban morphogenesis","year":2025,"lang":"en","type":"article","venue":"Computational Urban Science","topic":"Urban Design and Spatial Analysis","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":false,"ca_institutions":"Institute on Governance","funders":"Hong Kong University of Science and Technology; University of Notre Dame","keywords":"Morphogenesis; Environmental ethics; History; Philosophy; Biology","score_opus":0.012179711938546622,"score_gpt":0.23040897273347496,"score_spread":0.21822926079492835,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412808955","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09113912,0.0065772575,0.2316416,0.11528864,0.0015016053,0.000059370777,0.00023741268,0.0003440839,0.55321085],"genre_scores_gemma":[0.9629164,0.0018113913,0.015400269,0.0018452514,0.00031116622,0.000048888865,0.0000493331,0.0000808231,0.01753645],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99875164,0.0005863241,0.000027972968,0.00019952,0.00029280144,0.00014174829],"domain_scores_gemma":[0.9971336,0.0018562906,0.00013734718,0.00041883948,0.00029595976,0.00015802881],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020915272,0.0002821126,0.0004050095,0.0013291542,0.0025509088,0.004354271,0.0014152708,0.0023315428,0.004300274],"category_scores_gemma":[0.0046787104,0.00029255333,0.0005635542,0.0010794268,0.020699678,0.004203547,0.004167764,0.0021008323,0.00054595945],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000011657213,0.0000011232528,0.000058223268,0.0000050885355,7.0599333e-7,0.0000107280475,0.00026303105,0.001478752,0.000015453117,0.9962819,0.0010561981,0.000827733],"study_design_scores_gemma":[0.000002324514,0.000002362701,0.000072960785,0.00001340218,0.0000017130333,0.00002279766,0.00023228479,0.0038251753,0.00004544444,0.9701254,0.02565154,0.0000047356452],"about_ca_topic_score_codex":0.00791772,"about_ca_topic_score_gemma":0.008474791,"teacher_disagreement_score":0.00791772,"about_ca_system_score_codex":0.0040699714,"about_ca_system_score_gemma":0.0022533918,"threshold_uncertainty_score":0.02952981},"labels":[],"label_agreement":null},{"id":"W4413141550","doi":"10.1007/s43762-025-00202-z","title":"Correction: Advancing translational human dynamics research: bridging space, mind, and computational urban science in the era of GeoAI","year":2025,"lang":"en","type":"article","venue":"Computational Urban Science","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute on Governance","funders":"","keywords":"Bridging (networking); Space (punctuation); Dynamics (music); Data science; Translational science; Computer science; Cognitive science; Sociology; Psychology; Social science","score_opus":0.026275403784738815,"score_gpt":0.33328150378578986,"score_spread":0.30700610000105105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413141550","genre_codex":"editorial","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000079335165,0.0005250713,0.0006986317,0.0639653,0.9312626,0.000042919222,0.0018070107,0.0005931608,0.0010259447],"genre_scores_gemma":[0.014035687,0.0058054943,0.006240164,0.19895554,0.66291034,0.0008328959,0.0036169586,0.0024552513,0.1051477],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9863753,0.002539665,0.0026007765,0.00199315,0.005076274,0.0014148568],"domain_scores_gemma":[0.8669227,0.034097474,0.006940402,0.009693488,0.07622036,0.0061256895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008407855,0.0035063166,0.0039796834,0.006426809,0.005596563,0.008385087,0.006944989,0.017236128,0.13080373],"category_scores_gemma":[0.21079324,0.002187249,0.0027627726,0.0060461117,0.005793959,0.004901078,0.0052901763,0.020555865,0.056806464],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003602536,0.0000047223,0.00006562054,0.0002234174,0.000016587801,0.00008879365,0.00004681471,0.000033549208,0.000024393466,0.0005846283,0.99600226,0.0028731045],"study_design_scores_gemma":[0.00024494945,0.00003644447,0.001855489,0.0012100601,0.00010291765,0.00066419167,0.0003798925,0.0006013186,0.0004527066,0.004635174,0.989691,0.00012583808],"about_ca_topic_score_codex":0.029249648,"about_ca_topic_score_gemma":0.032870647,"teacher_disagreement_score":0.13080373,"about_ca_system_score_codex":0.005833182,"about_ca_system_score_gemma":0.013480477,"threshold_uncertainty_score":0.43758208},"labels":[],"label_agreement":null}]}