{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":16,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":16,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"8a862ad3fb17","filters":{"venue":"Advances in data mining and database management book series"}},"results":[{"id":"W2491486088","doi":"10.4018/978-1-5225-0489-4.ch009","title":"Association Rule Mining in Collaborative Filtering","year":2016,"lang":"en","type":"book-chapter","venue":"Advances in data mining and database management book series","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"","keywords":"Association rule learning; Data mining; Computer science; Bitwise operation; Collaborative filtering; Association (psychology); Information retrieval; Operator (biology); Recommender system","authors":[{"name":"Carson K. Leung","is_ca":true},{"name":"Fan Jiang","is_ca":true},{"name":"Edson M. Dela Cruz","is_ca":true},{"name":"Vijay Sekar Elango","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01818527911704608,"gpt":0.2681337246220243,"spread":0.2499484455049783,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007035471,0.0003631079,0.0004031599,0.000367547,0.0001489014,0.0002772098,0.00129601,0.0001008648,0.00003744057],"category_scores_gemma":[0.00007850646,0.000356795,0.00001827119,0.0001733566,0.00009084649,0.007901314,0.003786301,0.0001634251,0.00002199671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00013475,"about_ca_system_score_gemma":0.00004363329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006722712,"about_ca_topic_score_gemma":0.0003532358,"domain_scores_codex":[0.9974784,0.00003427354,0.0005349009,0.001222383,0.0003476963,0.0003823892],"domain_scores_gemma":[0.9973999,0.0002648185,0.0004023526,0.001822736,0.00004215495,0.00006804106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003166972,0.00004574556,0.000339483,0.0003512134,0.0001245642,0.0003339308,0.0007195538,0.000008942529,0.00001083221,0.2729344,0.02468567,0.700414],"study_design_scores_gemma":[0.0004386749,0.00002928504,0.00006230217,0.001520628,0.00002757233,0.000005757752,0.0002676538,0.001052265,0.00001061038,0.001714935,0.9943926,0.0004776833],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.00006926271,0.02659323,0.06696779,0.002771796,0.001000698,0.001313418,0.0149988,0.0003805623,0.8859044],"genre_scores_gemma":[0.00002647027,0.08484386,0.5632989,0.0003690287,0.0001774485,0.0001809847,0.004623584,0.00006398989,0.3464158],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.969707,"threshold_uncertainty_score":0.9998884,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2916505310","doi":"10.4018/978-1-5225-7432-3.ch016","title":"Role of Big Data in Internet of Things Networks","year":2019,"lang":"en","type":"book-chapter","venue":"Advances in data mining and database management book series","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University; University of Waterloo","funders":"","keywords":"Big data; Internet of Things; Data science; Computer science; Computer security; Analytics; Domain (mathematical analysis); Smart city; Data analysis; Engineering","authors":[{"name":"Vijayalakshmi Saravanan","is_ca":true},{"name":"Fatima Hussain","is_ca":true},{"name":"Naik Kshirasagar","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03182995252121435,"gpt":0.2530316491487639,"spread":0.2212016966275496,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0008839892,0.0003272266,0.0005760369,0.0003985307,0.00002979878,0.0000750153,0.004136329,0.00008906169,0.000005049038],"category_scores_gemma":[0.00003716223,0.0003332029,0.00002226281,0.0001180526,0.0001772456,0.005942416,0.01783157,0.0002469292,0.000003040877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000181984,"about_ca_system_score_gemma":0.0000374417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007249073,"about_ca_topic_score_gemma":0.00009504175,"domain_scores_codex":[0.9975218,0.00003183887,0.0007241439,0.00111824,0.0003001023,0.000303828],"domain_scores_gemma":[0.9952606,0.0001874135,0.0004949754,0.003992425,0.00002558126,0.00003899298],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008361944,0.00004638406,0.0008874313,0.001348629,0.0001000373,0.00009051961,0.0007537005,0.0000543944,0.000002964762,0.08927193,0.00937119,0.8979892],"study_design_scores_gemma":[0.0003743342,0.00006284087,0.00004799923,0.00331179,0.00003725543,0.000006766064,0.0001166234,0.07451902,0.00001045959,0.001314056,0.9197918,0.0004070273],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.0001394265,0.1202476,0.2258222,0.0001662068,0.008521871,0.001190032,0.0004054353,0.0001538922,0.6433534],"genre_scores_gemma":[0.002267163,0.1822097,0.613048,0.0009722542,0.001725412,0.00002217592,0.02863875,0.0002288672,0.1708877],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9104207,"threshold_uncertainty_score":0.999912,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2483307344","doi":"10.4018/978-1-4666-4309-3.ch006","title":"Virtual Reality Technologies (Visual, Haptics, and Audio) in Large Datasets Analysis","year":2013,"lang":"en","type":"book-chapter","venue":"Advances in data mining and database management book series","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Haptic technology; Computer science; Virtual reality; Human–computer interaction; Modalities; Data science; Multimedia; Artificial intelligence","authors":[{"name":"Bob-Antoine J. Ménélas","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04867027963402397,"gpt":0.3266706756789908,"spread":0.2780003960449668,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002100684,0.0004297091,0.0005830919,0.0009138079,0.0001978978,0.0001951871,0.0007083713,0.0001304177,0.0001806393],"category_scores_gemma":[0.0003255489,0.0004249753,0.00003338844,0.0002085311,0.0004802005,0.00578316,0.003177603,0.0003899134,0.00002559361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003794261,"about_ca_system_score_gemma":0.00001214813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000502421,"about_ca_topic_score_gemma":0.00308594,"domain_scores_codex":[0.997227,0.00005479146,0.0005701949,0.001468769,0.0002853752,0.0003939338],"domain_scores_gemma":[0.997411,0.0003446066,0.0002863305,0.00188544,0.0000136801,0.00005897053],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007716978,0.0006423245,0.002148056,0.001852072,0.001079275,0.004022542,0.0008167116,0.0001422014,0.0003783169,0.5927856,0.09101976,0.3043415],"study_design_scores_gemma":[0.0003459807,0.00006361815,0.00005735572,0.0003134533,0.000308695,0.00001609988,0.001726267,0.001197498,0.0001324544,0.0005604245,0.9947752,0.0005029415],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.006676232,0.03194604,0.005672891,0.00412784,0.001996414,0.004936518,0.2787642,0.001806359,0.6640735],"genre_scores_gemma":[0.02703552,0.6977572,0.007030969,0.001333801,0.0001159832,0.0001764042,0.05007716,0.0001463533,0.2163266],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9037554,"threshold_uncertainty_score":0.9998202,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2884667593","doi":"10.4018/978-1-5225-3142-5.ch011","title":"Big Data in Massive Parallel Processing","year":2018,"lang":"en","type":"book-chapter","venue":"Advances in data mining and database management book series","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Big data; Computer science; Massively parallel; Cloud computing; Data processing; Domain (mathematical analysis); Field (mathematics); Distributed computing; Data science; Parallel computing; Database; Operating system","authors":[{"name":"Vijayalakshmi Saravanan","is_ca":false},{"name":"Anpalagan Alagan","is_ca":true},{"name":"Isaac Woungang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.050763890243285,"gpt":0.2797774737697361,"spread":0.2290135835264511,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.001067153,0.000585433,0.0005686555,0.0006025751,0.0002202883,0.0004338328,0.005748957,0.0001108943,0.00002556649],"category_scores_gemma":[0.00005233088,0.0005720523,0.00002453574,0.000203472,0.0003549965,0.00210822,0.02625266,0.0003199749,0.00002659052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005817131,"about_ca_system_score_gemma":0.00005138334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001998914,"about_ca_topic_score_gemma":0.0006722162,"domain_scores_codex":[0.9956196,0.00005316659,0.0007299562,0.002466134,0.000555157,0.0005760043],"domain_scores_gemma":[0.9933352,0.000114268,0.0004186551,0.006000139,0.00003193882,0.00009975342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007006055,0.00006923224,0.00009749478,0.00147798,0.00009169133,0.001251471,0.0006157116,0.0002400919,2.572108e-7,0.04357566,0.0240846,0.9284257],"study_design_scores_gemma":[0.0005644149,0.00005510247,0.00002523993,0.00281221,0.00005069397,0.00001501758,0.0003907855,0.0303687,5.20979e-7,0.002364416,0.9626608,0.0006921295],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.0001054281,0.1053278,0.1229017,0.002423896,0.002202494,0.00193745,0.001945549,0.0006650519,0.7624906],"genre_scores_gemma":[0.0004206376,0.06967186,0.474694,0.001717137,0.001240642,0.00008051828,0.01036266,0.0001908299,0.4416217],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9385762,"threshold_uncertainty_score":0.9996731,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2483332504","doi":"10.4018/978-1-4666-4309-3.ch013","title":"From Data-Centered to Activity-Centered Geospatial Visualizations","year":2013,"lang":"en","type":"book-chapter","venue":"Advances in data mining and database management book series","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Geospatial analysis; Computer science; Visualization; Popularity; Geovisualization; Data science; Data visualization; Human–computer interaction; Focus (optics); Information visualization; World Wide Web; Data mining; Geography; Cartography","authors":[{"name":"Olga Buchel","is_ca":true},{"name":"Kamran Sedig","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06919051318874063,"gpt":0.3541098565831341,"spread":0.2849193433943935,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006988558,0.0003853159,0.0004955077,0.0003347355,0.0005982349,0.0003698007,0.001934363,0.0001232128,0.002395292],"category_scores_gemma":[0.000210168,0.0004275685,0.00003603691,0.0001388154,0.0004245481,0.005990415,0.00318572,0.0001851512,0.0001237476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000926453,"about_ca_system_score_gemma":0.00009070876,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005508378,"about_ca_topic_score_gemma":0.1386907,"domain_scores_codex":[0.9968714,0.0001458222,0.0005171289,0.001516366,0.0005552612,0.0003940205],"domain_scores_gemma":[0.9961293,0.000245884,0.0002794166,0.003082545,0.00006492107,0.0001978862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00035741,0.0004206613,0.0006007078,0.0007312256,0.0008861275,0.0001354999,0.008982106,0.00008611747,0.000006672224,0.1055015,0.1458398,0.7364521],"study_design_scores_gemma":[0.0002968693,0.0000253374,0.00003950098,0.0006105956,0.0002279701,1.836932e-7,0.002919259,0.0007066466,0.000001408712,0.0007381589,0.9939805,0.0004536294],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001112013,0.01949262,0.06934506,0.006365958,0.002305103,0.005439389,0.1194467,0.0006822243,0.775811],"genre_scores_gemma":[0.006007701,0.1226286,0.03044091,0.002111998,0.001797673,0.0002532942,0.2634005,0.000185361,0.573174],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.8481406,"threshold_uncertainty_score":0.9998176,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4229521098","doi":"10.4018/978-1-4666-6078-6.ch003","title":"A Measure Optimized Cost-Sensitive Learning Framework for Imbalanced Data Classification","year":2014,"lang":"en","type":"book-chapter","venue":"Advances in data mining and database management book series","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Machine learning; Computer science; Particle swarm optimization; Artificial intelligence; Classifier (UML); Benchmark (surveying); Measure (data warehouse); Artificial neural network; Data mining; Feature (linguistics); Support vector machine","authors":[{"name":"Peng Cao","is_ca":true},{"name":"Osmar R. Zai͏̈ane","is_ca":true},{"name":"Dazhe Zhao","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0668525753557907,"gpt":0.3211394183207882,"spread":0.2542868429649975,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001745857,0.0006112109,0.0007300305,0.0003879841,0.0003276508,0.000417708,0.004549048,0.0002441512,0.0000126569],"category_scores_gemma":[0.0006585938,0.0006502437,0.00003901691,0.0001402521,0.000317848,0.007649741,0.006447247,0.0005143259,0.00001339913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008530464,"about_ca_system_score_gemma":0.00006399063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003137062,"about_ca_topic_score_gemma":0.00003840714,"domain_scores_codex":[0.9954846,0.0001151103,0.0007916145,0.002588339,0.0005264531,0.0004939216],"domain_scores_gemma":[0.9907568,0.0007482021,0.0008479372,0.00739491,0.0001387007,0.0001134129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001586425,0.00001904824,0.00001252365,0.0004185093,0.00008318884,0.00002378412,0.00008543955,0.00001799907,0.000007835463,0.7156931,0.01255256,0.2709274],"study_design_scores_gemma":[0.000651129,0.00007002091,0.00001658099,0.001730968,0.00009970155,0.00001169205,0.0001780273,0.0389972,0.00003191044,0.006314344,0.9511527,0.0007456991],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[1.642524e-7,0.003462452,0.9522832,0.0007070117,0.0003033394,0.00153023,0.005118372,0.00047971,0.03611554],"genre_scores_gemma":[0.00005161819,0.03721225,0.8774215,0.0004591305,0.0001458076,0.0002670927,0.05771785,0.00007828543,0.02664647],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9386002,"threshold_uncertainty_score":0.9995949,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4252056038","doi":"10.4018/978-1-4666-5019-0.ch006","title":"Social Network Integration in Document Summarization","year":2013,"lang":"en","type":"book-chapter","venue":"Advances in data mining and database management book series","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal","funders":"","keywords":"Automatic summarization; Computer science; Social media; Multi-document summarization; Event (particle physics); Information retrieval; Social network (sociolinguistics); Context (archaeology); World Wide Web; Microblogging; Data science","authors":[{"name":"Atefeh Farzindar","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01999497349308524,"gpt":0.2860572642265334,"spread":0.2660622907334482,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003196996,0.0003413978,0.0004073956,0.0002190823,0.0001257381,0.0001436848,0.0004412901,0.00005542948,0.0005373928],"category_scores_gemma":[0.000003071,0.0003578605,0.00003333388,0.00009666497,0.0001077235,0.002973859,0.001372783,0.0001993527,0.00001029644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004369532,"about_ca_system_score_gemma":0.00001121063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007229014,"about_ca_topic_score_gemma":0.0008079401,"domain_scores_codex":[0.9982869,0.00003622158,0.0005190841,0.0006895416,0.0001993812,0.0002688469],"domain_scores_gemma":[0.9988443,0.00005243254,0.0002838337,0.0007654637,0.00002231607,0.00003166031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002759563,0.00001735977,0.0007023969,0.00007321517,0.00006722325,0.000009291274,0.00007649048,0.00005853656,3.470809e-7,0.6547133,0.0363313,0.307923],"study_design_scores_gemma":[0.0002441499,0.0000185281,0.00006039961,0.000827305,0.0001024179,2.657404e-7,0.0002321082,0.0008852446,0.000002214346,0.05316906,0.9440411,0.0004172204],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00005129362,0.00841539,0.03081317,0.0002965564,0.0002041949,0.001234211,0.000769542,0.0001273515,0.9580883],"genre_scores_gemma":[0.009527203,0.065722,0.1484168,0.0005181544,0.002761439,0.0006876218,0.1869543,0.0002725975,0.5851399],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9077098,"threshold_uncertainty_score":0.9998873,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2520535771","doi":"10.4018/978-1-5225-0714-7.ch012","title":"How Age-Friendly Are Cities?","year":2016,"lang":"en","type":"book-chapter","venue":"Advances in data mining and database management book series","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Index (typography); Composite index; Geography; Czech; Regional science; Composite indicator; Business; Computer science","authors":[{"name":"Lucie Vidovićová","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04688998688949519,"gpt":0.3229005404997101,"spread":0.2760105536102149,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000731473,0.0004021549,0.0005424909,0.0002353178,0.0005940386,0.0003653794,0.001032434,0.000153399,0.0002954366],"category_scores_gemma":[0.0001922523,0.0003620271,0.00004113381,0.00005228331,0.0009098965,0.006084142,0.001636645,0.0001949997,0.00001686685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009830375,"about_ca_system_score_gemma":0.00007607038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001199447,"about_ca_topic_score_gemma":0.01668978,"domain_scores_codex":[0.9973744,0.00006534611,0.0004002391,0.0009316832,0.0005429587,0.0006853442],"domain_scores_gemma":[0.9977747,0.0002802628,0.0003367027,0.001371846,0.00003401104,0.0002024881],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004217689,0.000007999995,0.0003156756,0.001016911,0.00004299303,0.0004667263,0.0004531178,9.482344e-8,2.294911e-8,0.8703495,0.05202287,0.07528195],"study_design_scores_gemma":[0.000278896,0.00002001607,0.00005284644,0.002270221,0.0000503144,0.000001872573,0.007368225,7.446559e-7,2.217703e-7,0.004469466,0.9850236,0.0004635312],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000006131771,0.03445975,0.0002300282,0.008252845,0.0008986062,0.0005222131,0.005165306,0.0001224278,0.9503427],"genre_scores_gemma":[0.00003827592,0.2688279,0.003763052,0.001433166,0.0003820975,0.00003207134,0.001216669,0.00004066715,0.7242661],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9330008,"threshold_uncertainty_score":0.9998832,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2488625897","doi":"10.4018/978-1-5225-0463-4.ch009","title":"Automated Identification of Child Abuse in Chat Rooms by Using Data Mining","year":2016,"lang":"en","type":"book-chapter","venue":"Advances in data mining and database management book series","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure; Concordia University","funders":"","keywords":"Preprocessor; Identification (biology); Computer science; Data pre-processing; Domain (mathematical analysis); Data mining; Data science; Feature extraction; Scalability; Social media; Machine learning; Artificial intelligence; World Wide Web; Database","authors":[{"name":"Mohammad Reza Keyvanpour","is_ca":false},{"name":"Mohammadreza Ebrahimi","is_ca":true},{"name":"Necmiye Genc Nayebi","is_ca":true},{"name":"Olga Ormandjieva","is_ca":true},{"name":"Ching Y. Suen","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03144693544285009,"gpt":0.2802886728559151,"spread":0.248841737413065,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009600089,0.0003459243,0.0004013888,0.0004869477,0.0001325726,0.0001949317,0.002563986,0.0001029852,0.00001185537],"category_scores_gemma":[0.00005883225,0.0003418155,0.00001711343,0.0001553117,0.0001682163,0.01224376,0.00354947,0.0001464905,0.000004127626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004931907,"about_ca_system_score_gemma":0.0000203642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000261648,"about_ca_topic_score_gemma":0.0003050921,"domain_scores_codex":[0.9971533,0.00004831041,0.0007633158,0.001379403,0.0003709373,0.0002846684],"domain_scores_gemma":[0.9954158,0.0001136781,0.0005977835,0.003794507,0.0000264695,0.0000517474],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003605864,0.0002312222,0.0009162803,0.003606112,0.0004286997,0.0004573793,0.002627933,0.0002700725,0.0005722881,0.05702466,0.03370172,0.899803],"study_design_scores_gemma":[0.0009121393,0.00005946095,0.00006796802,0.005664516,0.0001017452,0.0000346461,0.0002536889,0.08201925,0.0002118645,0.0004465904,0.9093439,0.0008842137],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.004204188,0.2352568,0.4888372,0.002547351,0.009189454,0.005690269,0.05239641,0.003160659,0.1987176],"genre_scores_gemma":[0.01244923,0.4435278,0.3575862,0.001276004,0.0008269624,0.000133624,0.07350799,0.0004757365,0.1102165],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8989188,"threshold_uncertainty_score":0.9999034,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2505195002","doi":"10.4018/978-1-60960-475-2.ch012","title":"Making Query Coding in SQL Easier by Implementing the SQL Divide Keyword","year":2011,"lang":"en","type":"book-chapter","venue":"Advances in data mining and database management book series","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Query by Example; Computer science; SQL; Sargable; Query optimization; Data definition language; Relational algebra; SQL/PSM; Stored procedure; Null (SQL); Programming language; Codd's theorem; Relational database; Theoretical computer science; Database; Relational model; Information retrieval; Web search query; Relational calculus","authors":[{"name":"Eric Draken","is_ca":true},{"name":"Shang Gao","is_ca":true},{"name":"Reda Alhajj","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05640107424140321,"gpt":0.2973257292373583,"spread":0.2409246549959551,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.001558749,0.0007033775,0.0006764171,0.0003804213,0.0004572253,0.0002663397,0.002333,0.000102011,0.00007893398],"category_scores_gemma":[0.00007926049,0.0006036502,0.00005153955,0.0001821411,0.0003444962,0.0114664,0.01051593,0.0004468368,0.00001155532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007673346,"about_ca_system_score_gemma":0.00004212884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009121741,"about_ca_topic_score_gemma":0.002583624,"domain_scores_codex":[0.9957252,0.00009676216,0.001055924,0.001749997,0.00051547,0.0008566789],"domain_scores_gemma":[0.9954645,0.0002927221,0.000641059,0.003482313,0.00003333108,0.00008607998],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000557275,0.00002607267,0.0005273815,0.0007837932,0.00008954804,0.0004349353,0.00069938,0.000007204274,0.00000464733,0.7949815,0.01505404,0.1873358],"study_design_scores_gemma":[0.0003751407,0.00003148789,0.00002378939,0.002666022,0.00004258147,0.00002876613,0.000547361,0.0002540375,0.00001247682,0.002454156,0.9928467,0.0007174424],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00003752194,0.09816639,0.4490646,0.0007489382,0.00139529,0.001979351,0.007036413,0.0003792384,0.4411923],"genre_scores_gemma":[0.001689982,0.2931343,0.4032259,0.003032894,0.0007445051,0.0005889687,0.01641195,0.0004032105,0.2807683],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9777927,"threshold_uncertainty_score":0.9996415,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3092448126","doi":"10.4018/978-1-7998-3053-5.ch025","title":"Descriptive Data Analytics on Dinesafe Data for Food Assessment and Evaluation Using R Programming Language","year":2020,"lang":"en","type":"book-chapter","venue":"Advances in data mining and database management book series","topic":"Data Analysis with R","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Lakehead University","funders":"","keywords":"Christian ministry; Data science; Analytics; Agency (philosophy); Computer science; Descriptive statistics; Work (physics); Visualization; Data visualization; World Wide Web; Engineering; Data mining; Political science; Sociology","authors":[{"name":"Ajinkya Kunjir","is_ca":true},{"name":"Vikas Trikha","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1763928216549824,"gpt":0.3831092513069133,"spread":0.2067164296519309,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.002016241,0.0005314251,0.0006158761,0.0003851763,0.0002425776,0.0006815092,0.00503437,0.00007546264,0.000009753175],"category_scores_gemma":[0.0002321642,0.0005252861,0.00002215553,0.0001837526,0.0001894185,0.01388267,0.02111447,0.0002300071,0.000001639284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009802277,"about_ca_system_score_gemma":0.0001198176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001393714,"about_ca_topic_score_gemma":0.0008384312,"domain_scores_codex":[0.9952805,0.000079201,0.0006487501,0.002827754,0.0007950324,0.000368752],"domain_scores_gemma":[0.9905735,0.0002561347,0.0005189668,0.008457843,0.00006949526,0.0001240867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00014512,0.0001001022,0.0001347785,0.001647321,0.001017259,0.0002247046,0.0003997835,0.0001487197,0.000005450317,0.1482571,0.01172073,0.8361989],"study_design_scores_gemma":[0.000649463,0.0001705806,0.00001292827,0.0009128412,0.0008681475,0.000008361448,0.0008269715,0.411355,0.000001701163,0.0005712449,0.5840574,0.0005653616],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00004665619,0.0309876,0.8468235,0.001093597,0.0006387721,0.003866429,0.1000437,0.000253443,0.0162463],"genre_scores_gemma":[0.0002733162,0.0109132,0.8113505,0.0003523525,0.0001718018,0.0000504765,0.174655,0.0000666819,0.002166656],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8356336,"threshold_uncertainty_score":0.9999096,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2885194465","doi":"10.4018/978-1-5225-3142-5.ch014","title":"Resource Provisioning and Scheduling of Big Data Processing Jobs","year":2018,"lang":"en","type":"book-chapter","venue":"Advances in data mining and database management book series","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Cloud computing; Provisioning; Big data; Computer science; Scheduling (production processes); Data processing; Resource (disambiguation); Distributed computing; Data science; Database; Operating system; Engineering; Computer network","authors":[{"name":"Rajni Aron","is_ca":false},{"name":"Deepak Aggarwal","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04735395957259508,"gpt":0.2769045705384887,"spread":0.2295506109658936,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.001354608,0.0004843643,0.0005572129,0.0004592271,0.0003221825,0.0003580029,0.003510073,0.00009520719,0.000007899922],"category_scores_gemma":[0.00008139422,0.0004621141,0.00002133392,0.0001569375,0.0004935138,0.001600831,0.02615771,0.0002562969,0.000002965808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002196957,"about_ca_system_score_gemma":0.00004074033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009804262,"about_ca_topic_score_gemma":0.00007187919,"domain_scores_codex":[0.9962805,0.00004707217,0.0007256647,0.002008103,0.0005282456,0.0004104313],"domain_scores_gemma":[0.9946927,0.0001536164,0.0005749457,0.004434689,0.00004492093,0.0000990702],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004949685,0.00003071093,0.00007482048,0.00244536,0.00009094195,0.0001534343,0.0006043357,0.0001131165,0.000001617061,0.02488831,0.003465906,0.968082],"study_design_scores_gemma":[0.000405781,0.00008523819,0.000013118,0.005323471,0.00009714193,0.00002431041,0.0006397371,0.04499622,0.000004707148,0.0007885491,0.9470769,0.0005448944],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.000953935,0.239316,0.1766187,0.001510221,0.001322445,0.002212471,0.001760513,0.0007748028,0.5755309],"genre_scores_gemma":[0.001523108,0.03810403,0.8183063,0.0006982979,0.0009328208,0.00002577055,0.004169481,0.000180391,0.1360599],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.967537,"threshold_uncertainty_score":0.999783,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3131108132","doi":"10.4018/978-1-7998-4963-6.ch015","title":"A Preliminary Framework to Fight Tax Evasion in the Home Renovation Market","year":2021,"lang":"en","type":"book-chapter","venue":"Advances in data mining and database management book series","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Evasion (ethics); Transactional leadership; Tax evasion; Analytics; Anomaly detection; Field (mathematics); Predictive analytics; Government (linguistics); Business; Computer security; Computer science; Data science; Economics; Artificial intelligence; Public economics","authors":[{"name":"Cataldo Zuccaro","is_ca":true},{"name":"Michel Plaisent","is_ca":true},{"name":"Prosper Bernard","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03107681028964373,"gpt":0.2874005376708139,"spread":0.2563237273811702,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001121632,0.0003623713,0.0003399968,0.00047242,0.000135621,0.0003079603,0.002895362,0.0001226636,0.0000678141],"category_scores_gemma":[0.0001627896,0.0003212774,0.00002069692,0.0003361375,0.000105161,0.005647731,0.004937413,0.0003469119,0.00001003189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006120038,"about_ca_system_score_gemma":0.00003465183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004855734,"about_ca_topic_score_gemma":0.0001239082,"domain_scores_codex":[0.99721,0.00009160173,0.0005631575,0.001338243,0.0004978916,0.0002991265],"domain_scores_gemma":[0.994904,0.0003428195,0.0002643278,0.004398379,0.00004361758,0.00004682878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001059977,0.00005093018,0.00004912714,0.0005128319,0.0000236888,0.0004305641,0.0004816286,0.00000467929,0.000003398634,0.6697649,0.1676985,0.1608738],"study_design_scores_gemma":[0.0001365357,0.00008268179,0.0002327385,0.002621054,0.00001889475,0.0000192317,0.0002293648,0.0004560592,0.00001559308,0.007963777,0.9878178,0.0004062211],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00001387038,0.02848049,0.6293206,0.008223723,0.0008190348,0.002627854,0.004914978,0.0004287147,0.3251707],"genre_scores_gemma":[0.00006951487,0.06382532,0.8215248,0.003973309,0.0001158356,0.0003179415,0.01137738,0.00005058368,0.0987453],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8201194,"threshold_uncertainty_score":0.9999239,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2511113538","doi":"10.4018/978-1-5225-0613-3.ch010","title":"A Dynamic and Scalable Decision Tree Based Mining of Educational Data","year":2016,"lang":"en","type":"book-chapter","venue":"Advances in data mining and database management book series","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Laurentian University","funders":"","keywords":"Data science; Computer science; Scalability; Big data; Field (mathematics); Data mining; Data stream mining; Process (computing); The Internet; Decision tree; Globe; World Wide Web; Database","authors":[{"name":"Dineshkumar B. Vaghela","is_ca":false},{"name":"Priyanka Sharma","is_ca":false},{"name":"Kalpdrum Passi","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02427566962768486,"gpt":0.2914051498074734,"spread":0.2671294801797885,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005951441,0.0003495149,0.0003997457,0.000354246,0.0001630483,0.0001690368,0.002956936,0.00007199389,0.00006541776],"category_scores_gemma":[0.00008780988,0.0003166578,0.00001637561,0.0001078213,0.0003298981,0.00680711,0.007743735,0.0001051918,0.000007350985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002572591,"about_ca_system_score_gemma":0.00008782322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007203202,"about_ca_topic_score_gemma":0.0002966964,"domain_scores_codex":[0.9972211,0.00001964143,0.00056079,0.001567675,0.0003615076,0.0002693178],"domain_scores_gemma":[0.9942961,0.0005711133,0.0003504194,0.004648848,0.00003825575,0.0000952325],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002946295,0.00004061685,0.0000874895,0.0002828085,0.00004329711,0.00001739329,0.00003992363,0.00000345677,0.000002795049,0.135951,0.01129785,0.852204],"study_design_scores_gemma":[0.0005948433,0.00005361432,0.00009930451,0.002484087,0.00007726022,0.00001361288,0.00008088177,0.04275427,0.000002950688,0.004431658,0.9489166,0.0004908767],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00008610537,0.06606994,0.5749385,0.004140581,0.0008591923,0.001420057,0.05228002,0.0001912256,0.3000143],"genre_scores_gemma":[0.00004868395,0.02617183,0.9016826,0.0001543722,0.00004460115,0.00003454492,0.0146649,0.00003612954,0.05716234],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9376188,"threshold_uncertainty_score":0.9999285,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2520584842","doi":"10.4018/978-1-5225-0714-7.ch008","title":"Constructing a Multidimensional Socioeconomic Index and the Validation of It with Early Child Developmental Outcomes","year":2016,"lang":"en","type":"book-chapter","venue":"Advances in data mining and database management book series","topic":"Early Childhood Education and Development","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Alberta","funders":"","keywords":"Socioeconomic status; Index (typography); Psychology; Developmental psychology; Child development; Early childhood; Principal (computer security); Geography; Demography; Population; Sociology; Computer science","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.01792247577107938,"gpt":0.2735282450871206,"spread":0.2556057693160413,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007396771,0.0002234006,0.0003218437,0.0001439709,0.0003898999,0.00007131664,0.0002941298,0.00005735728,0.0001529195],"category_scores_gemma":[0.00005672756,0.0001533201,0.00001653301,0.00002525462,0.001286702,0.002002657,0.0006650876,0.000111525,0.000005457322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006564,"about_ca_system_score_gemma":0.0001527429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008389389,"about_ca_topic_score_gemma":0.001888678,"domain_scores_codex":[0.9986062,0.00004917397,0.0003962429,0.0004742747,0.0002842576,0.0001898717],"domain_scores_gemma":[0.9989138,0.0003159447,0.0003438982,0.0003392313,0.00003179269,0.00005538602],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00030098,0.00002063249,0.06498678,0.0001824573,0.0003512656,0.0000122184,0.01276288,0.000001198379,1.288561e-7,0.8389097,0.001123814,0.08134788],"study_design_scores_gemma":[0.003502109,0.00003200147,0.004808234,0.002137526,0.0001333814,0.00001693648,0.03987803,0.000004399953,0.000008152634,0.002519449,0.946233,0.0007267704],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01154589,0.005620168,0.0003404245,0.007964658,0.0004898638,0.001547953,0.001326474,0.0000675134,0.9710971],"genre_scores_gemma":[0.08963384,0.1781352,0.1961919,0.003787538,0.0005482369,0.000228615,0.005681395,0.0002159873,0.5255773],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9451092,"threshold_uncertainty_score":0.6252214,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2489210490","doi":"10.4018/978-1-4666-6170-7.ch018","title":"GPS Travel Diaries in Rural Transportation Research","year":2014,"lang":"en","type":"book-chapter","venue":"Advances in data mining and database management book series","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of New Brunswick","funders":"","keywords":"Global Positioning System; TRIPS architecture; Transport engineering; License; Exploratory research; Geography; Geographic information system; Assisted GPS; Unit (ring theory); Sample (material); Business; Computer science; Engineering; Psychology; Telecommunications; Cartography","authors":[{"name":"Trevor Hanson","is_ca":true},{"name":"Eric Hildebrand","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06581219663468368,"gpt":0.3596982013595721,"spread":0.2938860047248885,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00219088,0.0002950286,0.0004332578,0.0004067664,0.000393486,0.0001558764,0.0009434622,0.0001534122,0.0002835247],"category_scores_gemma":[0.00005719286,0.0003084207,0.00003018057,0.000132714,0.001317156,0.004286934,0.0002194761,0.0003935552,0.00001029912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006597591,"about_ca_system_score_gemma":0.00006828996,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001284219,"about_ca_topic_score_gemma":0.1865195,"domain_scores_codex":[0.9972612,0.0001086701,0.0005744177,0.0008601797,0.0006802452,0.0005152638],"domain_scores_gemma":[0.9984638,0.0002583701,0.0001513411,0.0009836029,0.00004529777,0.00009760344],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004071005,0.00007007758,0.03130532,0.001433554,0.00005604208,0.0003402059,0.007393889,0.000004348871,0.000001258125,0.7894107,0.006148584,0.1634289],"study_design_scores_gemma":[0.0003959972,0.00003024337,0.004963072,0.001005241,0.00004347917,1.324759e-7,0.007370088,0.00001155681,0.000001870051,0.008236058,0.9775479,0.0003943369],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.003317571,0.03940832,0.0008015548,0.001158586,0.0006721379,0.001727876,0.004908363,0.0001357657,0.9478698],"genre_scores_gemma":[0.0396132,0.3013971,0.008742737,0.000325432,0.0006509971,0.0001784631,0.03092247,0.0001298023,0.6180398],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9713994,"threshold_uncertainty_score":0.9999368,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}