{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":3,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":3,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"query_hash":"cf4b35a55735","filters":{"venue":"Urban Informatics"}},"results":[{"id":"W4312197947","doi":"10.1007/s44212-022-00021-1","title":"A systematic review of the modifiable areal unit problem (MAUP) in community food environmental research","year":2022,"lang":"en","type":"review","venue":"Urban Informatics","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":42,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Wuhan University; Chinese University of Hong Kong; National Natural Science Foundation of China","keywords":"Geospatial analysis; Geography; Socioeconomic status; Unit (ring theory); Consistency (knowledge bases); Environmental health; Cartography; Computer science; Psychology; Medicine","retraction":null,"screen_n_in":null,"score":{"opus":0.1458697826424238,"gpt":0.3790569994642302,"spread":0.2331872168218064,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.01174178,0.0002825105,0.001880942,0.0002215862,0.001095011,0.00006964797,0.002620504,0.0002146797,0.0004624671],"category_scores_gemma":[0.0005290848,0.0001907481,0.0004860005,0.001610673,0.0006355545,0.0003451136,0.0004987471,0.00232602,0.00002362566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007519331,"about_ca_system_score_gemma":0.0009714803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001341997,"about_ca_topic_score_gemma":0.0007903819,"domain_scores_codex":[0.9910627,0.004217405,0.002472827,0.000119081,0.001609535,0.0005184592],"domain_scores_gemma":[0.9962227,0.001121682,0.001239273,0.001269468,0.00004806988,0.00009884958],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[8.002248e-7,0.0001641347,0.0001876662,0.9839583,0.00005668982,4.10991e-7,0.01246773,0.000001053258,1.084794e-9,0.0004746178,0.0003381847,0.002350415],"study_design_scores_gemma":[0.00009327894,0.00005715633,0.000008147174,0.5131562,0.0004358345,0.000001128926,0.0084793,0.00001101635,4.924334e-8,0.0003797731,0.4771447,0.0002333347],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00009100733,0.9662963,0.000001915874,0.00001204507,0.00008486584,0.005792645,0.0002603649,0.00002138614,0.02743947],"genre_scores_gemma":[0.0004361119,0.9979028,0.00004342405,0.00004867887,0.00002123803,0.0006281838,0.0001705414,0.00002109754,0.0007279257],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.4768066,"threshold_uncertainty_score":0.9999757,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4400510070","doi":"10.1007/s44212-024-00053-9","title":"Understanding pedestrian movement using urban sensing technologies: the promise of audio-based sensors","year":2024,"lang":"en","type":"article","venue":"Urban Informatics","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"Division of Civil, Mechanical and Manufacturing Innovation; National Science Foundation","keywords":"Pedestrian; Movement (music); Computer science; Computer vision; Human–computer interaction; Transport engineering; Engineering; Acoustics","retraction":null,"screen_n_in":null,"score":{"opus":0.1130460549984666,"gpt":0.2954515601075431,"spread":0.1824055051090765,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001210666,0.0001772509,0.0002183416,0.0002644743,0.0002016991,0.0003644012,0.0005359671,0.00009196663,0.000001800294],"category_scores_gemma":[0.0001735534,0.0001249741,0.0001080735,0.0008903164,0.0001382467,0.0004593666,0.0001669849,0.0002547613,0.000006425551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002291052,"about_ca_system_score_gemma":0.0002225516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001629103,"about_ca_topic_score_gemma":0.000003544523,"domain_scores_codex":[0.9985036,0.00007433459,0.0005742743,0.0001439357,0.0003825232,0.0003213767],"domain_scores_gemma":[0.9985871,0.0004295549,0.0002117356,0.0006759164,0.00006037617,0.00003532105],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009881783,0.0002837601,0.02244028,0.009443561,0.001310383,0.0003234447,0.137787,0.2250299,0.00553767,0.3785587,0.0265107,0.1926757],"study_design_scores_gemma":[0.0001965838,0.00005049039,0.00003620725,0.000335111,0.00001964919,0.00001228516,0.002123524,0.9842638,0.005540899,0.00532941,0.001907594,0.0001844075],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02174514,0.0002186573,0.9749923,0.0005724978,0.0004755027,0.000282475,0.000004815157,0.0005627902,0.001145766],"genre_scores_gemma":[0.8306884,0.00001159022,0.1690836,0.0001344244,0.00003615677,0.000001901659,0.000001422716,0.00001262934,0.0000298772],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8089433,"threshold_uncertainty_score":0.5096294,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4403064525","doi":"10.1007/s44212-024-00058-4","title":"Urban street clusters: unraveling the associations of street characteristics on urban vibrancy dynamics in age, time, and day","year":2024,"lang":"en","type":"article","venue":"Urban Informatics","topic":"Urban Design and Spatial Analysis","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Fulbright Canada","funders":"Fulbright Canada","keywords":"Geography; Economic geography; Dynamics (music); Sociology","retraction":null,"screen_n_in":null,"score":{"opus":0.008792034565778905,"gpt":0.2001698853383922,"spread":0.1913778507726133,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003391408,0.0002361961,0.0003583775,0.0003200186,0.00007107709,0.0001581937,0.0002196467,0.0001395474,0.00002281119],"category_scores_gemma":[0.00009274738,0.000192339,0.00009750669,0.0005375479,0.00006178427,0.0002706173,0.00005044891,0.000365409,0.00002881419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002238115,"about_ca_system_score_gemma":0.0000334132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006889348,"about_ca_topic_score_gemma":0.0004877708,"domain_scores_codex":[0.9984891,0.00003910387,0.0008107517,0.0001002932,0.000283377,0.000277397],"domain_scores_gemma":[0.9991402,0.0003352436,0.0001169494,0.0002941941,0.00004218916,0.00007119252],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000662047,0.0005190584,0.3623879,0.004760479,0.003755841,0.0001462308,0.1520554,0.09950239,0.0003871263,0.04166732,0.2744788,0.06027327],"study_design_scores_gemma":[0.0001755362,0.00004880956,0.006794555,0.0002216727,0.0001037253,5.73993e-7,0.0006382959,0.9902381,0.00004375289,0.00006553339,0.001443338,0.0002261619],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9196219,0.001606309,0.04250664,0.0002947166,0.001456305,0.001388951,0.003153083,0.001019363,0.02895277],"genre_scores_gemma":[0.9984373,0.00009119012,0.000456285,0.00007660458,0.0001148187,0.000009126105,0.0003433033,0.00003638497,0.000434942],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8907356,"threshold_uncertainty_score":0.7843357,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}