{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":435,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":435,"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":"081a53945d31","filters":{"venue":"GEOMATICA"}},"results":[{"id":"W2338354263","doi":"","title":"Toward better support for spatial decision making: defining the characteristics of spatial on-line analytical processing (solap)","year":2019,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":154,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Online analytical processing; Exploit; Data warehouse; Computer science; Spatial analysis; Line (geometry); Decision support system; Data mining; Data science; Geography; Cartography; Mathematics; Remote sensing","retraction":null,"screen_n_in":null,"score":{"opus":0.02906984507809188,"gpt":0.2903889626372823,"spread":0.2613191175591905,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000511753,0.0001486337,0.0002644238,0.00009050298,0.00009000809,0.0002409272,0.0009124479,0.0000469886,0.00008547348],"category_scores_gemma":[0.0001680386,0.0001015169,0.0000850344,0.000155179,0.00004330498,0.0002732065,0.0004037002,0.0001026656,0.000148645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001588788,"about_ca_system_score_gemma":0.00004846451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007730299,"about_ca_topic_score_gemma":0.000002046351,"domain_scores_codex":[0.9984824,0.00002329964,0.0004405639,0.0003248606,0.0004289964,0.0002998553],"domain_scores_gemma":[0.9987505,0.0003285528,0.0002151038,0.0005798267,0.00008522508,0.00004080694],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004754439,0.00008713395,0.001949361,0.0001389939,0.00002593662,0.000006467394,0.0002478349,0.00003346957,0.000009959131,0.01293594,0.000698656,0.9838187],"study_design_scores_gemma":[0.0004818131,0.0003890411,0.01351067,0.0001734888,0.00003739817,0.000004184174,0.00001979746,0.9776957,0.0001023853,0.003200792,0.004203648,0.0001810718],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03150706,0.00000426063,0.9656096,0.0009318023,0.0004079986,0.00035786,0.00003001604,0.00004582399,0.001105629],"genre_scores_gemma":[0.9133058,8.355618e-7,0.08559673,0.0008187372,0.0001440014,0.00001382434,0.00003334947,0.00001212602,0.00007464667],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9836376,"threshold_uncertainty_score":0.4139739,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2415624988","doi":"10.5623/cig2016-102","title":"Spatial Accuracy of UAV-Derived Orthoimagery and Topography: Comparing Photogrammetric Models Processed with Direct Geo-Referencing and Ground Control Points","year":2016,"lang":"en","type":"article","venue":"GEOMATICA","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":144,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"GNSS applications; Orthophoto; Remote sensing; Real Time Kinematic; Photogrammetry; Global Positioning System; Georeference; Geodesy; Satellite; Computer science; Mean squared error; Geography; Mathematics; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.02230267116353185,"gpt":0.1966323502776018,"spread":0.17432967911407,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002928406,0.0001677897,0.0003527074,0.0001020163,0.0001389616,0.00009170245,0.0000953046,0.00004665943,0.0001356],"category_scores_gemma":[0.0001154329,0.00009266003,0.0000320926,0.0002375782,0.0001466527,0.0004476762,0.000010118,0.00006607512,0.000004619836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001768849,"about_ca_system_score_gemma":0.00003087878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006373436,"about_ca_topic_score_gemma":0.006090556,"domain_scores_codex":[0.998904,0.00009164373,0.0002452754,0.0002574141,0.000213927,0.0002877421],"domain_scores_gemma":[0.998954,0.0005710687,0.0001411556,0.0001335995,0.00006960827,0.0001305614],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001845096,0.00001857696,0.8432533,0.0001804756,0.00007752402,0.0000100437,0.0003833589,0.00006231057,0.000605016,0.000008344832,0.000005371115,0.1552112],"study_design_scores_gemma":[0.001184643,0.0001743995,0.9813943,0.0001847448,0.00004679885,0.00002101344,0.0002120674,0.01567069,0.0002394723,0.0006576315,0.000009137963,0.0002051241],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936149,0.0004770434,0.004063493,0.00004971761,0.00002789297,0.0002369047,0.00004102398,0.00004764885,0.001441361],"genre_scores_gemma":[0.9988595,0.00008319686,0.0009664032,0.00003630642,0.00001829894,0.000002504412,0.00001584959,0.000004035066,0.00001391281],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1550061,"threshold_uncertainty_score":0.9634771,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2514818752","doi":"","title":"Defining global geospatial data infrastructure (ggdi): components, stakeholders and interfaces","year":2019,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":91,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Geospatial analysis; Spatial data infrastructure; Geography; Critical infrastructure; Volunteered geographic information; Data science; Computer science; Cartography; Environmental resource management; Spatial analysis; Remote sensing; Environmental science; Computer security","retraction":null,"screen_n_in":null,"score":{"opus":0.04419403438362487,"gpt":0.2966623852561303,"spread":0.2524683508725055,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005723966,0.0001179469,0.0002064268,0.0000454751,0.0003988633,0.0001723782,0.0004415517,0.0000775705,0.0002475619],"category_scores_gemma":[0.0001719269,0.0001060972,0.00001969762,0.0002114434,0.0002267711,0.0005427846,0.0004146956,0.00008474122,0.000237709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004083034,"about_ca_system_score_gemma":0.00005655759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002357523,"about_ca_topic_score_gemma":0.001536006,"domain_scores_codex":[0.9986817,0.00007671279,0.0002942373,0.0002028154,0.0004341703,0.0003103892],"domain_scores_gemma":[0.9992103,0.0001080483,0.0001600505,0.0003705463,0.00007049349,0.00008054075],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002825545,0.00002888351,0.7795047,0.000277046,0.0002708357,0.000002892583,0.06645037,0.0000936745,0.00002014799,0.1119458,0.01709877,0.02427857],"study_design_scores_gemma":[0.001310743,0.00008010729,0.6681213,0.0002621533,0.00006877487,0.00001428757,0.158173,0.003298834,0.00000500333,0.008021177,0.1600195,0.0006251212],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9411516,0.0002742769,0.0002083702,0.0007439002,0.0006449139,0.0003754738,0.0001621319,0.0001040176,0.0563353],"genre_scores_gemma":[0.9985664,0.0000384803,0.001041176,0.0001313894,0.00004706386,0.00000449969,0.00005478468,0.000004254342,0.0001119145],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1429207,"threshold_uncertainty_score":0.4326518,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2237424363","doi":"10.5623/cig2014-405","title":"Evaluation Of Uav Photogrammetric Accuracy For Mapping And Earthworks Computations","year":2014,"lang":"en","type":"article","venue":"GEOMATICA","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":83,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Photogrammetry; GNSS applications; Remote sensing; Stockpile; Scale (ratio); Aerial survey; Aerial photography; Computer science; Geography; Geodesy; Environmental science; Global Positioning System; Cartography","retraction":null,"screen_n_in":null,"score":{"opus":0.06194611094541619,"gpt":0.2687300136032815,"spread":0.2067839026578653,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001537778,0.00005150463,0.00009816836,0.00005339246,0.0001089069,0.0000318768,0.0000496375,0.00002851707,0.0002260594],"category_scores_gemma":[0.0007883994,0.00004043599,0.00002608497,0.0002003649,0.00002931952,0.00007462052,0.000003287076,0.00002977978,0.00001767581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001215156,"about_ca_system_score_gemma":0.0000150578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002115251,"about_ca_topic_score_gemma":0.0002924428,"domain_scores_codex":[0.9992899,0.000127306,0.0001483276,0.00009443364,0.0002261409,0.0001138398],"domain_scores_gemma":[0.9990024,0.0006834773,0.00006346344,0.00007153477,0.0001363639,0.00004275636],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003008045,0.00000746229,0.03411096,0.00004712381,0.000014038,3.646969e-8,0.0003628143,0.002369115,0.00002884071,0.00005043767,0.0001221634,0.962884],"study_design_scores_gemma":[0.0002461894,0.00004554077,0.4315308,0.00002228205,0.00002860043,0.000001506486,0.0001970438,0.563823,0.00002372892,0.003388603,0.0006366646,0.0000560784],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9806414,0.0003248374,0.01507126,0.00006849626,0.00008435807,0.0002909209,0.00002258204,0.00002247146,0.003473726],"genre_scores_gemma":[0.9925168,0.000006363526,0.00731873,0.00003337477,0.00002552726,0.000003341523,0.00007338235,0.000001277978,0.00002118355],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9628279,"threshold_uncertainty_score":0.2475192,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2262288151","doi":"","title":"Citizens as Sensors for Natural Hazards: A VGI integration Workflow","year":2010,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Seismology and Earthquake Studies","field":"Computer Science","cited_by":75,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Volunteered geographic information; Workflow; Natural hazard; Natural (archaeology); Geography; Geomatics; Citizen science; Cartography; Computer science; Environmental planning; Database; Archaeology; Meteorology","retraction":null,"screen_n_in":null,"score":{"opus":0.008390190358535728,"gpt":0.2456700978023346,"spread":0.2372799074437989,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002039826,0.0001091176,0.0001417764,0.00005762988,0.0002294861,0.00007627473,0.0003010406,0.00007952393,0.00003373077],"category_scores_gemma":[0.0004527759,0.00008730848,0.00007412818,0.0001361982,0.00008434519,0.0001597266,0.0000771885,0.0001898501,0.0002242213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005717093,"about_ca_system_score_gemma":0.00003542544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001213797,"about_ca_topic_score_gemma":0.0000481149,"domain_scores_codex":[0.9992318,0.00002556896,0.0001507093,0.0002210729,0.0001118444,0.0002589999],"domain_scores_gemma":[0.9992245,0.0002577123,0.00004771703,0.0003292612,0.00009445237,0.00004631721],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004736524,0.00009275191,0.0004184975,0.00004440749,0.0001463716,0.00003297246,0.007638718,0.00004302849,0.002906089,0.402458,0.02356515,0.5626066],"study_design_scores_gemma":[0.001665045,0.0004437158,0.03726421,0.0001038951,0.00006363378,0.0003660639,0.0005408704,0.381411,0.01003603,0.5249941,0.04216992,0.0009414376],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7963564,0.00008119558,0.183483,0.011222,0.002933897,0.0003823478,0.000003797244,0.0003280895,0.005209157],"genre_scores_gemma":[0.8870196,0.000002636643,0.1108802,0.0008858162,0.0001359165,0.00003895644,0.000004021273,0.000005171901,0.001027679],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5616652,"threshold_uncertainty_score":0.3560337,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2185052039","doi":"","title":"SPATIAL DATA UNCERTAINTY IN THE VGI WORLD: GOING FROM CONSUMER TO PRODUCER","year":2019,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":70,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"Université Laval","funders":"","keywords":"Volunteered geographic information; Geography; Spatial analysis; Cartography; Remote sensing","retraction":null,"screen_n_in":null,"score":{"opus":0.0421253478080758,"gpt":0.3194284407909464,"spread":0.2773030929828706,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001761654,0.00008527188,0.0001648272,0.0001195591,0.0002515735,0.0001242792,0.0007417498,0.00003248722,0.0003342109],"category_scores_gemma":[0.0003972046,0.00005950234,0.00002316318,0.0006055881,0.00009265981,0.0002552255,0.0002155149,0.00009571779,0.003181244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003290173,"about_ca_system_score_gemma":0.00007467208,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02859393,"about_ca_topic_score_gemma":0.07966313,"domain_scores_codex":[0.9984961,0.0001896031,0.0003082906,0.0002038743,0.0005111734,0.0002910114],"domain_scores_gemma":[0.9986541,0.0004335257,0.00008967119,0.0007133773,0.00006788023,0.00004148711],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003214701,0.00008521893,0.4823952,0.00007619554,0.0001217596,0.000004304476,0.4119129,0.0001191207,0.00002321313,0.01810019,0.06534177,0.02178803],"study_design_scores_gemma":[0.000351354,0.00001439087,0.1334209,0.0001333631,0.00001905303,4.185684e-7,0.05324259,0.0008073025,0.00000267512,0.001878773,0.809899,0.0002302392],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7862403,0.00007246775,0.0001402437,0.01422598,0.0009370495,0.001850293,0.0000851127,0.00007703067,0.1963716],"genre_scores_gemma":[0.9974837,0.000005355097,0.0003243636,0.0008695871,0.0001573726,0.00004179722,0.00003088381,0.000004135773,0.001082747],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7445572,"threshold_uncertainty_score":0.9975949,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2472692956","doi":"","title":"CSRS-PPP: AN INTERNET SERVICE FOR GPS USER ACCESS TO THE CANADIAN SPATIAL REFERENCE FRAME","year":2019,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":69,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Global Positioning System; Geography; Frame (networking); Cartography; Computer science; The Internet; Service (business); Reference frame; Telecommunications; Remote sensing; Geodesy; World Wide Web; Business","retraction":null,"screen_n_in":null,"score":{"opus":0.05700903661699402,"gpt":0.3326943155669138,"spread":0.2756852789499198,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008543205,0.0001050505,0.000156684,0.0001141928,0.0006331644,0.0004932166,0.0008929928,0.00009975675,0.0005466632],"category_scores_gemma":[0.0001813701,0.00007787891,0.00003574228,0.0003677743,0.0000520609,0.0004928052,0.0001077584,0.00009292995,0.001359394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009567422,"about_ca_system_score_gemma":0.0002427616,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7613296,"about_ca_topic_score_gemma":0.9861463,"domain_scores_codex":[0.9986978,0.00008188438,0.0002589998,0.0001594411,0.0003620906,0.0004397797],"domain_scores_gemma":[0.9987993,0.000137164,0.00009876656,0.0003423904,0.000406643,0.0002157868],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005305587,0.00006879224,0.1269337,0.0003593419,0.0002292977,0.000001562834,0.5797143,0.0003050418,0.000009509156,0.2042512,0.07656162,0.01151248],"study_design_scores_gemma":[0.0001883396,0.00005791031,0.07715829,0.00005815173,0.00001499664,7.445451e-7,0.01817977,0.0008617329,0.00001114381,0.001618778,0.9016256,0.0002245815],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7614566,0.00001793163,0.001761681,0.04576331,0.001774889,0.003769755,0.0001209332,0.0001605463,0.1851743],"genre_scores_gemma":[0.9924499,0.000001119827,0.0003224511,0.004939972,0.000166704,0.0001773802,0.00001683431,0.000007986478,0.001917586],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8250639,"threshold_uncertainty_score":0.9994181,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3023196182","doi":"10.1139/geomat-2019-0015","title":"Assessing the state of the art in Discrete Global Grid Systems: OGC criteria and present functionality","year":2020,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"Wilfrid Laurier University; University of Waterloo","funders":"","keywords":"Geospatial analysis; Computer science; Implementation; Software; Grid; Scalability; Geographic information system; Software engineering; Database; Spatial database; Documentation; Spatial analysis; Data science; Systems engineering; Engineering; Geography; Operating system; Remote sensing","retraction":null,"screen_n_in":null,"score":{"opus":0.03006076086355432,"gpt":0.2915705207448065,"spread":0.2615097598812522,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005883127,0.00008746903,0.0001604528,0.000007318458,0.00009348786,0.000372015,0.0005319469,0.00001886139,0.000002601158],"category_scores_gemma":[0.00008750299,0.00004858997,0.00003785202,0.0003014577,0.00006455884,0.0001929958,0.0003603066,0.00007555191,0.000008658104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002023413,"about_ca_system_score_gemma":0.00005303432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001051204,"about_ca_topic_score_gemma":0.000004632289,"domain_scores_codex":[0.998647,0.0003942035,0.0003208218,0.000194871,0.0002809738,0.0001621248],"domain_scores_gemma":[0.9992769,0.0001588378,0.0001368332,0.0003354276,0.00004131852,0.00005066453],"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":[0.0001155591,0.0006230132,0.2469644,0.007390576,0.0007643851,0.0001367681,0.0282492,0.2463141,0.001326654,0.210863,0.2245553,0.03269695],"study_design_scores_gemma":[0.0002188925,0.00002716666,0.1668538,0.0002111424,0.000008188948,0.00002841923,0.0001612845,0.8214825,0.00001433326,0.002869711,0.008010237,0.0001142701],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3796527,0.0004522458,0.6006009,0.01381466,0.001381516,0.0005848766,0.00008619916,0.00009305514,0.003333793],"genre_scores_gemma":[0.9993217,0.000001075924,0.0004024195,0.0001427751,0.00008668414,0.000007053553,0.0000029985,0.000002165956,0.00003311555],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.619669,"threshold_uncertainty_score":0.3587349,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2417164357","doi":"10.5623/cig2016-101","title":"The Canadian Geodetic Vertical Datum of 2013 (CGVD2013)","year":2016,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Geophysics and Gravity Measurements","field":"Earth and Planetary Sciences","cited_by":45,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true},"ca_institutions":"Geological Survey of Canada; Natural Resources Canada","funders":"","keywords":"Geodetic datum; GNSS applications; Geoid; Levelling; Geodesy; North American Datum of 1927; Satellite system; Satellite; Global Positioning System; Geology; Remote sensing; Computer science; Aerospace engineering; Telecommunications; Geophysics; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01561661077008292,"gpt":0.1895789169880542,"spread":0.1739623062179713,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002573359,0.00006548131,0.00008567123,0.00002370458,0.0002214164,0.00003416204,0.0002313288,0.00003214785,0.0009808256],"category_scores_gemma":[0.00008131227,0.00003140665,0.00003352748,0.00006916694,0.0001302196,0.00006045241,0.000007021835,0.00004023479,0.001606596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000466796,"about_ca_system_score_gemma":0.0001150892,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1908145,"about_ca_topic_score_gemma":0.6428456,"domain_scores_codex":[0.9991423,0.0000379851,0.0001464012,0.00009857245,0.0002618401,0.0003128677],"domain_scores_gemma":[0.9993533,0.0001339081,0.00002289112,0.0002550969,0.00004817928,0.0001865534],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004612739,0.00005410567,0.656024,0.00005514938,0.000149064,0.00001571992,0.0002814817,0.00007269435,0.0009289378,0.01034796,0.04803184,0.2839929],"study_design_scores_gemma":[0.0001848746,0.00006295623,0.9517003,0.00002982425,0.00001525839,0.000002238668,0.00001865703,0.001056913,0.0002166236,0.02148591,0.02512182,0.0001046087],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9703206,0.0001902915,0.00006904614,0.009052601,0.0005320608,0.0002082186,0.0001042296,0.00001493423,0.01950797],"genre_scores_gemma":[0.9993705,0.00001647144,0.00008937139,0.00008324496,0.00003138281,7.118246e-7,0.000006774529,0.000001621554,0.0003998768],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4520311,"threshold_uncertainty_score":0.9999324,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2980556879","doi":"","title":"AN INTERDISCIPLINARY FRAME FOR UNDERSTANDING VOLUNTEERED GEOGRAPHIC INFORMATION","year":2019,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":45,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Volunteered geographic information; Geography; Frame (networking); Cartography; Geographic information system; Geospatial analysis; Computer science; Telecommunications","retraction":null,"screen_n_in":null,"score":{"opus":0.02587636057368359,"gpt":0.3275921506909581,"spread":0.3017157901172745,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001041287,0.0001139195,0.000192261,0.000318853,0.0009463062,0.0002277086,0.0002598843,0.0001143264,0.0001952608],"category_scores_gemma":[0.00008518148,0.0001086874,0.00009445476,0.0003484459,0.0001463814,0.001955123,0.0000774381,0.0000779929,0.0003899396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001087806,"about_ca_system_score_gemma":0.00005182706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000234565,"about_ca_topic_score_gemma":0.0003124286,"domain_scores_codex":[0.9986526,0.00005479955,0.0004206831,0.000108359,0.0003898286,0.0003737781],"domain_scores_gemma":[0.9990793,0.0001722016,0.0002011328,0.000250091,0.000203374,0.00009389129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004265525,0.00004211673,0.02874746,0.0003075266,0.0001086507,1.960617e-7,0.1864121,0.0000872068,0.00001824463,0.7796845,0.00295893,0.001590481],"study_design_scores_gemma":[0.001317183,0.0003739693,0.02187682,0.0001993993,0.00005062572,0.000002877066,0.6942874,0.008383287,0.000005586171,0.2182301,0.05466978,0.0006028775],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5860385,0.00005506993,0.1418449,0.003950597,0.002646353,0.004355527,0.0000961785,0.0007904798,0.2602223],"genre_scores_gemma":[0.9983593,0.000005942316,0.001017129,0.0001808701,0.00007954232,0.00009669608,0.0000547768,0.0000067989,0.0001989414],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5614543,"threshold_uncertainty_score":0.7278318,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W155443542","doi":"","title":"RAY-TRACING OPTIONS TO MITIGATE THE NEUTRAL ATMOSPHERE DELAY IN GPS","year":2019,"lang":"en","type":"article","venue":"GEOMATICA","topic":"GNSS positioning and interference","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Atmosphere (unit); Global Positioning System; Ray tracing (physics); Tracing; Satellite; Remote sensing; Geography; Geodesy; Path (computing); Computer science; Environmental science; Meteorology; Physics; Telecommunications; Astronomy; Optics","retraction":null,"screen_n_in":null,"score":{"opus":0.005580665810047319,"gpt":0.200218863349675,"spread":0.1946381975396277,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00007628114,0.00007896169,0.00008666727,0.00001055509,0.00003779759,0.00004770002,0.0001323409,0.00003341114,0.0003141159],"category_scores_gemma":[0.00001038103,0.00006252763,0.00002908348,0.0001242885,0.00001068522,0.0000747104,0.00001918084,0.0001328442,0.002383101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002957569,"about_ca_system_score_gemma":0.000006316182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003436605,"about_ca_topic_score_gemma":0.00005233457,"domain_scores_codex":[0.9994981,0.00001615876,0.0001412547,0.00008640486,0.00005528288,0.0002027624],"domain_scores_gemma":[0.9996913,0.00004597611,0.000008830119,0.0001974104,0.00001242042,0.00004407286],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003424153,0.0000147619,0.0006294644,0.00005225367,0.00001720763,0.000002818578,0.001841162,0.9889101,0.002221805,0.00275548,0.002242844,0.001308713],"study_design_scores_gemma":[0.000530687,0.0001709765,0.06543966,0.0009396318,0.0000285502,0.00004510424,0.001114595,0.9204904,0.004573798,0.001892208,0.004200078,0.0005743471],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9680517,0.00005885587,0.001952553,0.0002637002,0.0001927695,0.0001517782,0.000002896883,0.0001122005,0.02921353],"genre_scores_gemma":[0.9980147,0.000003223744,0.001217995,0.00008112307,0.00002441664,0.00002774784,0.00000253944,0.0000130148,0.0006152243],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0684197,"threshold_uncertainty_score":0.9983937,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2523252104","doi":"","title":"GOOD GOVERNANCE OF CANADA’S OFFSHORE AND COASTAL ZONE: TOWARDS AN UNDERSTANDING OF THE MARINE BOUNDARY ISSUES","year":2019,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Law, logistics, and international trade","field":"Business, Management and Accounting","cited_by":41,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true},"ca_institutions":"University of New Brunswick","funders":"","keywords":"Maritime boundary; Submarine pipeline; Geography; Corporate governance; Continental shelf; Boundary (topology); Territorial waters; Oceanography; Exclusive economic zone; Geology; Political science; International law; Business; Law","retraction":null,"screen_n_in":null,"score":{"opus":0.01872681761043182,"gpt":0.2156059025559013,"spread":0.1968790849454695,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001158613,0.00007805928,0.0001511002,0.00001782902,0.00005999801,0.00005008603,0.0001898857,0.00002320478,0.0003063335],"category_scores_gemma":[0.00006489259,0.00005811993,0.00002599777,0.00006538816,0.0001421843,0.0002529203,0.0001749479,0.00004710878,0.00000215963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003801495,"about_ca_system_score_gemma":0.0001072959,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1242909,"about_ca_topic_score_gemma":0.2041194,"domain_scores_codex":[0.9992614,0.000005407282,0.0001979136,0.0001036827,0.0003125593,0.000119085],"domain_scores_gemma":[0.9995574,0.00002338642,0.0001873783,0.0001613291,0.00006243312,0.000008073568],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00002486285,0.0000528513,0.08840567,0.0005491159,0.00005067384,0.000001896154,0.0001086407,0.0000475481,0.0001555607,0.9054977,0.004484643,0.000620842],"study_design_scores_gemma":[0.0009165082,0.00005152988,0.855705,0.0002956068,0.00008125049,0.000005315145,0.002132945,0.0111073,0.0005026291,0.0696063,0.05927562,0.0003200267],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8086381,0.00007195523,0.0003486679,0.003780157,0.0006436942,0.0002213572,0.00005980941,0.00001786902,0.1862184],"genre_scores_gemma":[0.9979263,0.00000984706,0.0001300482,0.0002506234,0.0001384332,8.860965e-7,0.00001126083,0.000008214894,0.001524373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8358914,"threshold_uncertainty_score":0.8815405,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2185226792","doi":"","title":"Community Mapping The Recovery (and Discovery) of our Common Ground 1","year":2003,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":41,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Common ground; Social connectedness; Indigenous; Geography; Cartography; Empowerment; Participatory planning; Citizen journalism; Sustainable community; Community organization; Sociology; Environmental planning; Sustainable development; Computer science; Political science; Public relations; Ecology; World Wide Web","retraction":null,"screen_n_in":null,"score":{"opus":0.05706818114198062,"gpt":0.2862784992444699,"spread":0.2292103181024893,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002247107,0.0000616287,0.0001532332,0.00005043759,0.001211185,0.00008900738,0.000168642,0.00003771099,0.000007306045],"category_scores_gemma":[0.0004251096,0.00004345203,0.00004402337,0.0002512588,0.0002183261,0.0003097373,0.00005917853,0.0001184804,0.00001178071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001799235,"about_ca_system_score_gemma":0.00002897778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005115135,"about_ca_topic_score_gemma":0.00212591,"domain_scores_codex":[0.9987374,0.0005621545,0.000267287,0.00004022301,0.0002302884,0.0001626805],"domain_scores_gemma":[0.9992131,0.0003196415,0.0001599715,0.0002199269,0.00006374072,0.00002362993],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.000007276532,0.0000860803,0.06968462,0.0002954512,0.0001935863,5.990633e-7,0.3407027,0.00001066896,0.00003523756,0.5820842,0.003991935,0.002907612],"study_design_scores_gemma":[0.0002552481,0.00004033778,0.1303865,0.0001333719,0.00002585558,0.000004289564,0.7725918,0.00001173942,0.00002605969,0.05511708,0.04123951,0.0001682486],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.846437,0.0001271613,0.0003338524,0.001620677,0.0002104888,0.0002464938,0.000004463544,0.00002327339,0.1509966],"genre_scores_gemma":[0.9987497,0.00005522393,0.0001649375,0.000110117,0.00001850522,0.0000126779,8.682436e-7,0.000002673509,0.0008852456],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5269672,"threshold_uncertainty_score":0.9315576,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2214956521","doi":"10.5623/cig2014-402","title":"The Use of Unmanned Aerial Vehicles For Disaster Management","year":2014,"lang":"en","type":"article","venue":"GEOMATICA","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Work (physics); Business; Port (circuit theory); Computer security; Investment (military); Diversity (politics); Emergency management; Risk analysis (engineering); Aeronautics; Transport engineering; Engineering; Computer science; Political science","retraction":null,"screen_n_in":null,"score":{"opus":0.01413271807185843,"gpt":0.1952530027164373,"spread":0.1811202846445789,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005168316,0.00003646358,0.00004448332,0.00001143001,0.00004603344,0.00002606151,0.00005714264,0.00001417099,0.000005941044],"category_scores_gemma":[0.000009413928,0.00002618016,0.0000186415,0.00003639273,0.00001442683,0.00003341044,0.00001124226,0.000009674805,0.000009612088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004755307,"about_ca_system_score_gemma":6.24006e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001010649,"about_ca_topic_score_gemma":0.000002936765,"domain_scores_codex":[0.9997395,0.000004780608,0.0001063242,0.00003767717,0.00003871643,0.00007304046],"domain_scores_gemma":[0.9997212,0.00008001156,0.00001517658,0.0001581756,0.00001389403,0.00001154477],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004216791,0.00005901622,0.00008675767,0.0004791233,0.0001659349,8.066262e-8,0.0005974796,0.5308244,0.001201213,0.2393227,0.0315357,0.1956854],"study_design_scores_gemma":[0.0002102559,0.0000130531,0.0005973715,0.00001096013,0.000020549,1.166877e-7,0.00002851588,0.864035,0.000466197,0.002255327,0.1323095,0.00005324611],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09138176,0.00001302041,0.9057948,0.0001970383,0.0001292724,0.0004539132,0.000008704758,0.0000817414,0.001939756],"genre_scores_gemma":[0.9126512,0.00003213152,0.0865653,0.00003195999,0.00007849054,0.0002080887,0.00001930564,0.00002080946,0.0003927029],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8212695,"threshold_uncertainty_score":0.1067596,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2515368120","doi":"","title":"Crustal motion and deformation monitoring of the canadian landmass","year":2019,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Geological Modeling and Analysis","field":"Earth and Planetary Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Geology; Geodesy; Seismology; Motion (physics); Deformation monitoring; Deformation (meteorology); Geography; Remote sensing; Computer science; Computer vision","retraction":null,"screen_n_in":null,"score":{"opus":0.01089437921200832,"gpt":0.1783472713994814,"spread":0.1674528921874731,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009980257,0.00002712781,0.00004914808,0.00002360429,0.00007336571,0.00001561793,0.000048595,0.00002482203,0.0002655859],"category_scores_gemma":[0.00001921906,0.00001525464,0.00001736638,0.00006419756,0.0000126454,0.0000483357,0.000003321335,0.0000334834,0.00007589671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001829595,"about_ca_system_score_gemma":0.00001102857,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08212501,"about_ca_topic_score_gemma":0.0760263,"domain_scores_codex":[0.9997076,0.00001654625,0.0000712316,0.000043835,0.00008031091,0.00008050776],"domain_scores_gemma":[0.9998411,0.00001508277,0.00002561059,0.0000648339,0.00001434988,0.00003903085],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[4.733066e-7,6.325608e-7,0.9828941,0.000008047688,0.000002602316,6.715228e-8,0.00007112817,0.008869189,0.000003916912,0.00002047789,0.000003185206,0.0081262],"study_design_scores_gemma":[0.00003275943,0.000007942484,0.8616562,0.000007799969,0.000005703458,0.000001044421,0.00009544743,0.137592,0.00002431262,0.000507134,0.00004824078,0.00002148085],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957737,0.00003488425,0.00006222547,0.0002824266,0.00007552051,0.00004040846,0.00000562699,0.00000439865,0.003720856],"genre_scores_gemma":[0.9996736,0.000002999423,0.000221229,0.00001657799,0.00001437409,1.161303e-7,0.000006122904,3.292911e-7,0.00006466363],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1287228,"threshold_uncertainty_score":0.9408338,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2527252489","doi":"","title":"A gravimetric geoid model as a vertical datum in canada","year":2019,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Geophysics and Gravity Measurements","field":"Earth and Planetary Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Geodetic datum; Geoid; Geodesy; North American Datum of 1927; Geology; Geography; Division (mathematics); Geophysics; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.01112659030016779,"gpt":0.1813104325072623,"spread":0.1701838422070945,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001406418,0.00009271645,0.0001531207,0.00006677436,0.00003135603,0.00002563754,0.0001820165,0.00002582889,0.001167208],"category_scores_gemma":[0.00004054185,0.00007927183,0.00002447749,0.0003174912,0.00001040948,0.00008086903,0.00001234532,0.0001089092,0.001554744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001999091,"about_ca_system_score_gemma":0.000560285,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9171316,"about_ca_topic_score_gemma":0.8922864,"domain_scores_codex":[0.9988692,0.00002547022,0.0001651291,0.0001788433,0.0004269663,0.0003343519],"domain_scores_gemma":[0.9995756,0.00005149359,0.0000180216,0.0002127209,0.00001926148,0.000122935],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002041208,0.0000313025,0.9744776,0.00003916241,0.00001446596,0.00002290115,0.00007299217,0.01650317,0.00006588524,0.0003142304,0.000771708,0.007666133],"study_design_scores_gemma":[0.0002485834,0.00003412026,0.6008499,0.00001433063,0.000005711715,0.000002593251,0.00004468194,0.3908773,0.00004133282,0.007549832,0.000207685,0.0001238767],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9854613,0.00004275297,0.00002615995,0.0001573769,0.0001588394,0.0001508969,0.00002381256,0.000006952043,0.01397194],"genre_scores_gemma":[0.9990927,0.000002294809,0.0002360503,0.0003540948,0.00001073524,8.229725e-7,0.00003834322,0.000002188724,0.0002627653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3743741,"threshold_uncertainty_score":0.9997458,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2166857440","doi":"10.5623/cig2013-036","title":"Using Video Acquired from an Unmanned Aerial Vehicle (UAV) to Measure Fracture Orientation in an Open-Pit Mine","year":2013,"lang":"en","type":"article","venue":"GEOMATICA","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":40,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"Carleton University","funders":"","keywords":"Point cloud; Computer science; Computer vision; Artificial intelligence; Orientation (vector space); Measure (data warehouse); Software; Remote sensing; Computer graphics (images); Geology","retraction":null,"screen_n_in":null,"score":{"opus":0.04985569083224869,"gpt":0.2814039533063346,"spread":0.2315482624740859,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002850618,0.0001450081,0.0002055066,0.00004200856,0.0001631247,0.000405062,0.0003791005,0.00009456778,0.005367273],"category_scores_gemma":[0.00007313285,0.0001139981,0.00001885701,0.0002427287,0.00002332165,0.001357291,0.00002185096,0.00006692009,0.0005202521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009338245,"about_ca_system_score_gemma":0.00003153898,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03789907,"about_ca_topic_score_gemma":0.02959117,"domain_scores_codex":[0.9986432,0.0002415417,0.000250887,0.0003192395,0.0002454738,0.0002996534],"domain_scores_gemma":[0.9993086,0.00006072615,0.00005911835,0.0002710092,0.00006314886,0.0002373836],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000588308,0.0002747315,0.8243077,0.00003767007,0.00004466754,0.00004220012,0.01725909,0.01975262,0.04840979,0.00001788738,0.002627732,0.08663763],"study_design_scores_gemma":[0.0005865009,0.0002386669,0.9623685,0.00004570254,0.000009791332,0.000001712504,0.001297691,0.03368249,0.0004147948,0.0008501778,0.0002635838,0.0002403707],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982295,0.00003560177,0.0001080819,0.0004149153,0.0002383417,0.0004651876,0.00006309902,0.00004529416,0.000399987],"genre_scores_gemma":[0.9931507,6.715387e-7,0.005275184,0.0008073767,0.0001676236,0.000005698094,0.0005260827,0.000005989043,0.00006067548],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1380609,"threshold_uncertainty_score":0.9955419,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W91894089","doi":"","title":"Data structures and application issues in 3-D geographic information systems","year":2019,"lang":"en","type":"article","venue":"GEOMATICA","topic":"3D Modeling in Geospatial Applications","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Geography; Geographic information system; Cartography; Information system; Geospatial analysis; Computer science; Data science; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.007551511883809334,"gpt":0.2241384067967183,"spread":0.2165868949129089,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001239208,0.00008165318,0.0001090405,0.0001106762,0.00002166194,0.00006226974,0.000210316,0.00005776842,0.00000836357],"category_scores_gemma":[0.00001194462,0.00008191299,0.000006295671,0.000141031,0.00001445189,0.0003990844,0.00006390804,0.00007500122,0.0001351001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001261806,"about_ca_system_score_gemma":0.000004837797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002483302,"about_ca_topic_score_gemma":0.00003914259,"domain_scores_codex":[0.9994218,0.000007588581,0.0002371784,0.0001073138,0.000107125,0.0001190206],"domain_scores_gemma":[0.999303,0.00002883664,0.00003028134,0.0005888676,0.00002101029,0.00002796704],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005638792,0.00002619861,0.03444596,0.001745544,0.00006184747,3.040951e-7,0.001342643,0.8590513,0.001501181,0.05994222,0.001637174,0.04024],"study_design_scores_gemma":[0.0001147296,0.000004602827,0.023711,0.00002348788,0.000005726317,0.000002321923,0.00008103223,0.9641448,0.00001759452,0.001981689,0.009811494,0.0001015681],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8543075,0.0009563772,0.1397881,0.0001677169,0.0002053305,0.001285305,0.0001425047,0.0004479125,0.002699187],"genre_scores_gemma":[0.9952522,0.00008249187,0.004222942,0.00001604526,0.00002425456,0.00007575376,0.000310798,0.00000950194,0.000006007386],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1409447,"threshold_uncertainty_score":0.3340315,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2137539224","doi":"","title":"USING THE CASE STUDY METHODOLOGY FOR CADASTRAL REFORM","year":2019,"lang":"en","type":"article","venue":"GEOMATICA","topic":"3D Modeling in Geospatial Applications","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Cadastre; Geography; Cartography; Regional science","retraction":null,"screen_n_in":null,"score":{"opus":0.1315375828445305,"gpt":0.3522707594425546,"spread":0.2207331765980242,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003406325,0.00008483913,0.000127248,0.0000259407,0.00008669727,0.00001667818,0.0001305509,0.00003911488,0.00003019996],"category_scores_gemma":[0.00002090214,0.00006096189,0.0000363326,0.00007514779,0.00001455834,0.00003598256,0.00002901941,0.00008199935,0.00003352795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006147272,"about_ca_system_score_gemma":0.00001194052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006612504,"about_ca_topic_score_gemma":0.0002370836,"domain_scores_codex":[0.9994431,0.00002737183,0.0001833819,0.0001052298,0.00005290233,0.0001880723],"domain_scores_gemma":[0.9993486,0.0001968628,0.00002225681,0.0003732562,0.00003181418,0.00002723546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001154928,0.0001424794,0.0007023805,0.0002526565,0.0002885326,0.00005266845,0.007943385,0.9632846,0.006700704,0.008713926,0.0002973509,0.01160973],"study_design_scores_gemma":[0.0002480614,0.00005443982,0.0001027319,0.000005422202,0.00005954713,0.0003096937,0.004530998,0.9919502,0.000297109,0.002120051,0.0002098865,0.0001118728],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6546658,0.00001153849,0.3439483,0.00005152116,0.000139461,0.0007224088,0.000006102531,0.00009073459,0.0003641809],"genre_scores_gemma":[0.8335715,3.195942e-7,0.1661698,0.00002080658,0.00005299244,0.0001283776,0.000002011502,0.00002016158,0.00003403434],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1789057,"threshold_uncertainty_score":0.2485954,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2464190297","doi":"","title":"Multiscale characterization of boundaries and landscape ecological patterns","year":2019,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Wildlife-Road Interactions and Conservation","field":"Environmental Science","cited_by":34,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Geography; Ecology; Cartography; Environmental resource management; Environmental science; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.004053927975539822,"gpt":0.1883876080166544,"spread":0.1843336800411145,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0000495343,0.00004266986,0.00007106085,0.00001140094,0.00004934253,0.00003252165,0.00003965016,0.00002807891,0.00583251],"category_scores_gemma":[0.0000130055,0.00003469391,0.00001323552,0.00003979809,0.00005460041,0.0001547912,0.00004983914,0.00002836887,0.0002696631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009240774,"about_ca_system_score_gemma":0.00000305534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005578346,"about_ca_topic_score_gemma":0.00002824282,"domain_scores_codex":[0.999634,0.00001537549,0.0001148473,0.00009147523,0.00007524608,0.00006901546],"domain_scores_gemma":[0.9998109,0.0000230862,0.00005381417,0.00008735555,0.000004527171,0.00002033699],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000005575821,0.00004169577,0.9691138,0.0000119839,0.000003499013,2.611345e-7,0.0002112204,0.000005589176,0.02751117,0.0001148654,0.0001454567,0.002834935],"study_design_scores_gemma":[0.0001082633,0.00004606066,0.9898172,0.000009371041,0.00000398552,0.000003066253,0.00005201462,0.004727142,0.0005726537,0.00008414823,0.004532059,0.00004404244],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997073,0.000001114292,0.000332334,0.0003583537,0.00007190119,0.000105557,0.000008734924,0.00001211514,0.00203689],"genre_scores_gemma":[0.9990215,0.000004205462,0.0002523492,0.000135452,0.000008003162,0.000006788155,0.00002013901,0.000002718102,0.0005487956],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02693852,"threshold_uncertainty_score":0.9950763,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2415363387","doi":"","title":"Potential of VGI as a Resource for SDIS in The North/South Context","year":2019,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Volunteered geographic information; Pace; Geography; The Internet; Context (archaeology); Resource (disambiguation); World Wide Web; Computer science; Line (geometry); Cartography","retraction":null,"screen_n_in":null,"score":{"opus":0.01207230616471227,"gpt":0.2570078620977201,"spread":0.2449355559330079,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009520652,0.00005691166,0.0001542408,0.00007398764,0.0001866841,0.00003158146,0.0002464053,0.00004086227,0.00007882404],"category_scores_gemma":[0.0002340946,0.00004008269,0.00007898883,0.0002634379,0.0001303096,0.00008412652,0.0000286692,0.00004454751,0.0001543628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001132287,"about_ca_system_score_gemma":0.00004018655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001323734,"about_ca_topic_score_gemma":0.001806725,"domain_scores_codex":[0.9989904,0.00008995154,0.0002948997,0.00007307153,0.0003509784,0.0002006755],"domain_scores_gemma":[0.9993429,0.0002137329,0.0001533131,0.0001715309,0.00009789639,0.00002061302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004598796,0.00005177047,0.09357571,0.0001952396,0.0000626728,9.762385e-7,0.8055156,0.00004859843,0.000007181043,0.09449846,0.003728108,0.002269702],"study_design_scores_gemma":[0.000994485,0.0001190594,0.1415943,0.00008068472,0.000027981,0.000001847327,0.7216772,0.0001713243,0.000005302698,0.00353451,0.131625,0.0001682505],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9238318,0.00003431507,0.00008758686,0.001469704,0.0001067944,0.0008926462,0.00001439295,0.00001628317,0.0735465],"genre_scores_gemma":[0.9986919,0.000002116653,0.00006463814,0.000280502,0.00004363232,0.00005768531,0.000003706551,0.000002919569,0.0008528685],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1278969,"threshold_uncertainty_score":0.2001098,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2768108767","doi":"10.5623/cig2017-203","title":"Web Mercator and Raster Tile Maps: Two Cornerstones of Online Map Service Providers","year":2017,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":29,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"University of New Brunswick","funders":"","keywords":"Mercator projection; Raster graphics; Tile; World Wide Web; Computer science; Web service; Geography; Cartography; Computer graphics (images)","retraction":null,"screen_n_in":null,"score":{"opus":0.02883004838944447,"gpt":0.3152582198874643,"spread":0.2864281714980198,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004422019,0.00008937938,0.0002082019,0.00007039892,0.0007590908,0.0001155588,0.0002749473,0.00005003446,0.00006075659],"category_scores_gemma":[0.0001516777,0.00007675326,0.0000345851,0.00007946843,0.0004177247,0.0004245175,0.0001312624,0.00004954572,0.00006682301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000981329,"about_ca_system_score_gemma":0.00007463501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003219262,"about_ca_topic_score_gemma":0.008843451,"domain_scores_codex":[0.9990461,0.00004853366,0.0002875608,0.0001059272,0.0003007576,0.0002111427],"domain_scores_gemma":[0.999043,0.00007778837,0.0003306778,0.0003065645,0.0001681571,0.00007376321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00008932412,0.0003233392,0.4179493,0.003420922,0.0006480507,0.000007052663,0.4612376,0.00001211755,0.0007595256,0.05104927,0.05035755,0.01414594],"study_design_scores_gemma":[0.004104332,0.0001422665,0.2555847,0.000902138,0.0002282828,0.000009687221,0.3858841,0.001549919,0.0001617794,0.00881704,0.3416372,0.0009784801],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9334119,0.0001543034,0.00001847104,0.01338957,0.0004518917,0.0005711255,0.0000722867,0.00006631017,0.05186413],"genre_scores_gemma":[0.9980658,0.00002831464,0.0006722284,0.0002415817,0.00008485202,0.00001945024,0.000006182147,0.000005474626,0.0008760932],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2912797,"threshold_uncertainty_score":0.5838389,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2901528478","doi":"10.1139/geomat-2018-0017","title":"A GIS-based multi-criteria decision analysis approach for public school site selection in Surabaya, Indonesia","year":2018,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Soil and Land Suitability Analysis","field":"Environmental Science","cited_by":27,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Analytic hierarchy process; Multiple-criteria decision analysis; Site selection; Geographic information system; Government (linguistics); Geography; Environmental planning; Population; Transport engineering; Environmental resource management; Computer science; Cartography; Operations research; Engineering; Political science; Environmental science; Sociology","retraction":null,"screen_n_in":null,"score":{"opus":0.02221629577066642,"gpt":0.2691633047410553,"spread":0.2469470089703889,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008839073,0.0001412694,0.0002945944,0.000288526,0.0001892449,0.000102708,0.0001966448,0.0001013339,0.002372135],"category_scores_gemma":[0.0003373261,0.0001162542,0.0001946315,0.002207146,0.0001237737,0.0002307945,0.00005701507,0.00007739295,0.0002142063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001584308,"about_ca_system_score_gemma":0.00001948065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001073611,"about_ca_topic_score_gemma":0.006380865,"domain_scores_codex":[0.9984626,0.0001173912,0.0003554798,0.0004323392,0.0002834023,0.0003487733],"domain_scores_gemma":[0.9993145,0.0001544035,0.00007531568,0.0002787863,0.00003318474,0.0001438389],"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":[0.00005428694,0.0003240551,0.990164,0.00001253254,0.00006515093,4.117312e-7,0.0001847133,0.002059069,0.0006074548,0.000003446097,0.00022979,0.006295105],"study_design_scores_gemma":[0.000413971,0.00003611752,0.4716,0.000002280628,0.00009348884,4.36675e-7,0.00004034523,0.5274437,0.00006812968,0.00008145689,0.0001251951,0.00009486685],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.755422,0.000005472647,0.2438552,0.0001300095,0.00001482561,0.0002205454,0.000008126461,0.0000322153,0.0003115836],"genre_scores_gemma":[0.9480764,7.660023e-7,0.0515071,0.0001326804,0.00003215547,0.0001042396,0.00006340429,0.000008740826,0.00007449458],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5253847,"threshold_uncertainty_score":0.9985398,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1840999097","doi":"10.5623/cig2015-306","title":"Contextual Douglas-Peucker SIMPLIFICATION","year":2015,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":26,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"University of New Brunswick","funders":"","keywords":"Representation (politics); Computer science; Scale (ratio); Artificial intelligence; Algorithm; Geography; Cartography","retraction":null,"screen_n_in":null,"score":{"opus":0.08855643296715725,"gpt":0.3393504833756819,"spread":0.2507940504085246,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001100585,0.00006834638,0.0001201254,0.00007228094,0.0003636305,0.00008117036,0.000161616,0.00005918661,0.0001332664],"category_scores_gemma":[0.0005470531,0.00006180041,0.00003711677,0.0002702469,0.0002056307,0.0002813458,0.00003356992,0.00004804524,0.001775562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005438226,"about_ca_system_score_gemma":0.00009624411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008997011,"about_ca_topic_score_gemma":0.0004637346,"domain_scores_codex":[0.9988633,0.00008530931,0.0002660921,0.00008600537,0.0004615743,0.0002377019],"domain_scores_gemma":[0.9991576,0.00009021282,0.0001114167,0.0001735481,0.0003344991,0.0001327345],"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":[0.000009848388,0.00003979748,0.02047548,0.00002144565,0.00004959542,0.000001203414,0.1959068,0.00001117512,0.000005052585,0.6853213,0.09406751,0.004090843],"study_design_scores_gemma":[0.0004158166,0.00002592959,0.01106655,0.00001676915,0.00001298893,0.00000189727,0.1177048,0.00009983811,0.000007351789,0.01536665,0.855116,0.0001654853],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1176037,0.000142533,0.001344486,0.005960111,0.001206347,0.0005733064,0.000006888439,0.0003302812,0.8728324],"genre_scores_gemma":[0.9964105,0.000007808532,0.0004198731,0.0002478863,0.0002311414,0.00004276134,0.000006129515,0.000004286353,0.00262959],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8788068,"threshold_uncertainty_score":0.9990017,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2886752202","doi":"10.1139/geomat-2018-0007","title":"A cyclic self-learning Chinese word segmentation for the geoscience domain","year":2018,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Topic Modeling","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Computer science; Context (archaeology); Domain (mathematical analysis); Benchmark (surveying); Natural language processing; Text segmentation; Segmentation; Word (group theory); Artificial intelligence; Information retrieval; Geography; Archaeology; Linguistics; Cartography","retraction":null,"screen_n_in":null,"score":{"opus":0.0110331818280587,"gpt":0.2655054943658863,"spread":0.2544723125378276,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005614239,0.00008776268,0.00008151996,0.00004077261,0.0004809031,0.0001885178,0.0007214846,0.00002524081,0.00001594179],"category_scores_gemma":[0.0001492893,0.0000564825,0.00003949444,0.0002944607,0.0000662681,0.0002815804,0.0001716054,0.00006785554,0.0000791624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002657211,"about_ca_system_score_gemma":0.00003404927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001395644,"about_ca_topic_score_gemma":0.000009602623,"domain_scores_codex":[0.9990466,0.00004618235,0.000172219,0.0002540699,0.0002216554,0.000259315],"domain_scores_gemma":[0.9990669,0.0003344077,0.00007907131,0.0004166014,0.00005740506,0.00004557493],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002747827,0.0002204879,0.005668269,0.0001728877,0.0001168554,0.000007493196,0.07661025,0.01333194,0.008645955,0.1092255,0.0008004805,0.7851724],"study_design_scores_gemma":[0.0001847698,0.0000505325,0.002847862,0.00001082422,0.000004791795,0.000005975278,0.0001292524,0.9751033,0.0001045533,0.01874437,0.002721793,0.00009196232],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1509255,0.0000213815,0.8465463,0.00136279,0.000268736,0.000269066,3.161291e-7,0.0001706699,0.0004352246],"genre_scores_gemma":[0.6076499,0.000001830665,0.3917061,0.0002851172,0.0001537524,0.00005573342,3.834748e-7,0.000004403486,0.0001427184],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9617714,"threshold_uncertainty_score":0.3698766,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2511451891","doi":"","title":"Ionosphere modelling using carrier smoothed ionosphere observations from a regional GPS network","year":2002,"lang":"en","type":"article","venue":"GEOMATICA","topic":"GNSS positioning and interference","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Ionosphere; Geodesy; Global Positioning System; Humanities; Geography; Physics; Philosophy; Telecommunications; Computer science; Geophysics","retraction":null,"screen_n_in":null,"score":{"opus":0.07139891798544813,"gpt":0.2064504428185148,"spread":0.1350515248330666,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00004178158,0.0001684582,0.0001776789,0.00001418397,0.000189562,0.00008074054,0.0001552794,0.0001024463,0.001188979],"category_scores_gemma":[0.000009917845,0.0001782703,0.00007077565,0.0001729493,0.00003411864,0.0001762653,0.00002103338,0.0001712369,0.0001423046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006439527,"about_ca_system_score_gemma":0.000009249921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000184796,"about_ca_topic_score_gemma":0.00001925207,"domain_scores_codex":[0.9990684,0.00002275592,0.0002789405,0.0001779546,0.0001475919,0.0003042979],"domain_scores_gemma":[0.9994566,0.00007787213,0.00004007504,0.0002852377,0.0000498728,0.00009031225],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001528337,0.00001403012,0.0002842587,0.00001401622,0.0000465571,0.000001563208,0.0004902731,0.9861296,0.0001959729,0.001025806,0.01155928,0.0002371484],"study_design_scores_gemma":[0.0001350389,0.000009617726,0.0004914899,0.0002314406,0.00003226571,0.000004640305,0.00007848538,0.9912769,0.00005560814,0.005168401,0.002310798,0.0002052759],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6441794,0.001214284,0.3445601,0.0001566361,0.0003704268,0.0001281238,0.00003098142,0.0004354251,0.008924637],"genre_scores_gemma":[0.9473411,0.00004497122,0.05171478,0.0001179902,0.0003028177,0.00001693945,0.0000317043,0.00004007671,0.0003896231],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3031617,"threshold_uncertainty_score":0.9997241,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2198162374","doi":"10.5623/cig2015-203","title":"Examining Urban Expansion In The Greater Toronto Area Using Landsat Imagery From 1974–2014","year":2015,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true},"ca_institutions":"University of Waterloo","funders":"Tianjin University; U.S. Geological Survey; University of Waterloo","keywords":"Urban expansion; Geography; Remote sensing; Physical geography; Satellite imagery; Cartography; Environmental science; Urban planning; Engineering; Civil engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.04532492707520583,"gpt":0.2284683183335288,"spread":0.183143391258323,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003641403,0.0001009687,0.0001300321,0.000009356764,0.00006123069,0.00006272149,0.0002170371,0.00004429751,0.001325864],"category_scores_gemma":[0.00001110568,0.00005779362,0.00001993923,0.00005067073,0.00001031532,0.0003373989,0.0001101674,0.00004221621,0.0005234534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001058527,"about_ca_system_score_gemma":0.000005417526,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01249839,"about_ca_topic_score_gemma":0.005656512,"domain_scores_codex":[0.9991145,0.00008177826,0.0001736886,0.0001822608,0.0002367541,0.0002110136],"domain_scores_gemma":[0.9995292,0.00005785243,0.00004920832,0.0002965679,0.00000308298,0.0000640511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002554187,0.00004770246,0.9748762,0.0000148751,0.000009258572,0.00004293951,0.01715147,0.0004393112,0.001336349,0.000001701687,0.005224614,0.0008300627],"study_design_scores_gemma":[0.001119258,0.0001012853,0.9170427,0.0002071814,0.00005596543,0.00002976389,0.01085466,0.06445484,0.0004953612,0.0007188727,0.004450533,0.0004695468],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9913689,0.00008464266,0.00006044402,0.00007871603,0.00009504185,0.0001040807,0.000004580575,0.00002038888,0.008183199],"genre_scores_gemma":[0.9990765,0.000003811395,0.0005049433,0.0002769841,0.00008780919,0.000008778309,0.00001164675,0.000007714794,0.00002180875],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06401553,"threshold_uncertainty_score":0.9995871,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2224019690","doi":"10.5623/cig2011-006","title":"Encouraging Transdisciplinary Participation Using an Open Source Cybercartographic Toolkit: The Atlas of the Lake Huron Treaty Relationship Process","year":2011,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":22,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"Carleton University","funders":"","keywords":"Atlas (anatomy); Outreach; Process (computing); Obstacle; Computer science; Data science; Software; Set (abstract data type); Knowledge management; Open source software; Management science; Process management; Political science; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.1301435098984828,"gpt":0.3563716935528361,"spread":0.2262281836543533,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001771173,0.0001162342,0.0001768442,0.0000822328,0.002177567,0.0001070678,0.0007523051,0.00007247541,0.00008589905],"category_scores_gemma":[0.000241266,0.00007089176,0.00008240121,0.0008795852,0.0005329499,0.000829756,0.0001101965,0.0001236666,0.000007738759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001967487,"about_ca_system_score_gemma":0.0001070642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001616285,"about_ca_topic_score_gemma":0.01315398,"domain_scores_codex":[0.9981772,0.0004396641,0.0004823928,0.0001441498,0.00046912,0.0002874601],"domain_scores_gemma":[0.9987671,0.0002453935,0.0003455097,0.000383288,0.0002007667,0.00005790305],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00001278955,0.00008934103,0.2176842,0.00004740789,0.00003789201,2.208267e-7,0.770757,0.0004488681,0.000009154782,0.01040121,0.00002302682,0.0004888286],"study_design_scores_gemma":[0.0003429498,0.00007132058,0.7373177,0.0001941794,0.0001870246,0.000003147446,0.2393908,0.001843514,0.00009184882,0.01960675,0.0007096324,0.0002411228],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9608668,0.00002334035,0.0005996683,0.0005698715,0.0001301125,0.0009193616,0.000006190747,0.00005041126,0.03683426],"genre_scores_gemma":[0.9994085,0.000003248904,0.0002100927,0.00003471245,0.00004279557,0.00009578338,0.000003004769,0.000009416694,0.0001924426],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5313662,"threshold_uncertainty_score":0.9991215,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2139045525","doi":"10.5623/cig2012-023","title":"Recent Developments in Precise Point Positioning","year":2012,"lang":"en","type":"article","venue":"GEOMATICA","topic":"GNSS positioning and interference","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false},"ca_institutions":"Natural Resources Canada; York University","funders":"Natural Resources Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Precise Point Positioning; Convergence (economics); Ambiguity resolution; Computer science; Ambiguity; Integer (computer science); Kinematics; Point (geometry); Constant (computer programming); Algorithm; Mathematical optimization; Global Positioning System; Mathematics; Telecommunications; GNSS applications; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.01186952527329912,"gpt":0.2141330462744236,"spread":0.2022635210011245,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001057367,0.0000707792,0.00007432843,0.00005763378,0.00002802092,0.00002091371,0.00005807797,0.00003207161,0.0001568949],"category_scores_gemma":[0.00002226936,0.00007242407,0.00001169516,0.0000949771,0.000007285012,0.0001677647,0.00001677327,0.00007870858,0.0004044746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008228173,"about_ca_system_score_gemma":0.000005652654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003162636,"about_ca_topic_score_gemma":0.000001904698,"domain_scores_codex":[0.9994611,0.0000124668,0.0001577449,0.00005340991,0.00007402155,0.0002412244],"domain_scores_gemma":[0.9998109,0.00001903773,0.00001066755,0.00008644442,0.00001364375,0.00005934707],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00007677218,0.001547748,0.104693,0.00093973,0.000400826,0.00003116362,0.06869916,0.02827805,0.05156832,0.02759308,0.06104759,0.6551245],"study_design_scores_gemma":[0.001829451,0.0001170278,0.7734573,0.002574607,0.000046818,0.0001713849,0.0009589515,0.05070491,0.1159214,0.003989902,0.04847044,0.001757844],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8274311,0.0005138877,0.003148032,0.00009889382,0.0004540553,0.0001156132,0.000002247385,0.0002277118,0.1680084],"genre_scores_gemma":[0.9943594,0.00005543339,0.00540332,0.00004438061,0.00002427334,0.00002486588,0.000009444337,0.00001082096,0.00006806065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6687642,"threshold_uncertainty_score":0.5198838,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4401465305","doi":"10.1016/j.geomat.2024.100003","title":"Assessment of flood susceptibility in Sylhet using analytical hierarchy process and geospatial technique","year":2024,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Geospatial analysis; Flood myth; Hierarchy; Analytic hierarchy process; Process (computing); Computer science; Geography; Data science; Data mining; Remote sensing; Engineering; Operations research; Archaeology; Political science; Programming language","retraction":null,"screen_n_in":null,"score":{"opus":0.01020169240789791,"gpt":0.3149083677857901,"spread":0.3047066753778922,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006084867,0.0001220181,0.0001938233,0.00009054122,0.00003715234,0.00004121587,0.0001308898,0.00005276067,0.0006616456],"category_scores_gemma":[0.00001886847,0.0001032149,0.00003610113,0.0003554891,0.0001666306,0.0001880107,0.0002368032,0.0001365722,0.000008983113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001315266,"about_ca_system_score_gemma":0.00003283728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004370625,"about_ca_topic_score_gemma":0.0002905502,"domain_scores_codex":[0.9987559,0.00005779105,0.0003093837,0.0003268097,0.0003219179,0.0002281682],"domain_scores_gemma":[0.9996451,0.00004880754,0.00003628683,0.0002046213,0.000005331407,0.00005987092],"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":[0.00002876456,0.001196685,0.9247226,0.002373775,0.0001338169,0.0001396835,0.001640202,0.01210375,0.02177838,0.009784512,0.0005211956,0.02557669],"study_design_scores_gemma":[0.0002087812,0.0001205411,0.2739421,0.0001511255,0.00005456941,0.000005675312,0.0001949351,0.717567,0.0005726482,0.006846846,0.0001567762,0.0001791025],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9680095,0.0000257575,0.02550687,0.0001740472,0.00004764833,0.0005934009,0.000005512677,0.00004587571,0.005591403],"genre_scores_gemma":[0.9834281,0.00001265593,0.01642936,0.00001916577,0.00001169519,0.00004144092,0.000003857955,0.00000978941,0.00004392821],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7054632,"threshold_uncertainty_score":0.7244555,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4403144134","doi":"10.1016/j.geomat.2024.100029","title":"Evaluating monsoon season heavy metal contamination in groundwater of Uttar Dinajpur District using pollution indices and Principal Component analysis","year":2024,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":20,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Uttar pradesh; Environmental science; Pollution; Principal component analysis; Monsoon; Groundwater; Contamination; Hydrology (agriculture); Water resource management; Geography; Geology; Socioeconomics; Biology; Mathematics; Ecology; Statistics; Meteorology","retraction":null,"screen_n_in":null,"score":{"opus":0.05511706663908961,"gpt":0.3438167398759757,"spread":0.2886996732368861,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009798422,0.0001019861,0.0002003395,0.0001540706,0.000074423,0.00005775946,0.00006634844,0.00004426832,0.0002500084],"category_scores_gemma":[0.0000211758,0.00008670941,0.00006155307,0.0005451296,0.00009529282,0.0002763988,0.000100326,0.0000748286,0.00001910272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002651845,"about_ca_system_score_gemma":0.00001097683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001821136,"about_ca_topic_score_gemma":0.000284259,"domain_scores_codex":[0.9986334,0.0002391056,0.0003481477,0.0002250849,0.0003820861,0.0001721714],"domain_scores_gemma":[0.9996845,0.00005811517,0.00009149447,0.0001116876,0.000005268296,0.0000489636],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001472982,0.001086745,0.7458012,0.0009742461,0.001102205,0.00004247086,0.02525636,0.08448621,0.08892836,0.004023929,0.0000291297,0.0481219],"study_design_scores_gemma":[0.000149391,0.00006543633,0.6105387,0.00004595615,0.0002485544,0.000003240195,0.000257794,0.3870802,0.001231557,0.000238549,0.00004972991,0.00009092768],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942005,0.00009198019,0.005040916,0.0002508952,0.0000493964,0.0001940117,0.00001659919,0.0000202491,0.0001353978],"genre_scores_gemma":[0.9977596,0.000006437149,0.002115145,0.00001726554,0.00001023466,0.000009695534,0.0000358785,0.000004832153,0.00004088793],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.302594,"threshold_uncertainty_score":0.3535907,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4407242224","doi":"10.1016/j.geomat.2025.100049","title":"LW-UAV–YOLOv10: A lightweight model for small UAV detection on infrared data based on YOLOv10","year":2025,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Infrared Target Detection Methodologies","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Infrared; Computer science; Remote sensing; Geography; Physics; Optics","retraction":null,"screen_n_in":null,"score":{"opus":0.07131939130334962,"gpt":0.2877349126026619,"spread":0.2164155212993123,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006928327,0.0003355691,0.000377143,0.0004719566,0.0001948879,0.00008209064,0.0006025224,0.0003024028,0.00006829262],"category_scores_gemma":[0.001471148,0.0003239547,0.0001135966,0.000394147,0.00004100805,0.0001565614,0.0001086447,0.0003384126,0.0001122103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000177487,"about_ca_system_score_gemma":0.00006456064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004111711,"about_ca_topic_score_gemma":0.00001515415,"domain_scores_codex":[0.9982442,0.0001216511,0.000464144,0.000489948,0.0001998513,0.0004801936],"domain_scores_gemma":[0.9971493,0.00116849,0.00007151389,0.001456761,0.00008098061,0.0000729176],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004305078,0.0001244399,0.0000211874,0.0006983365,0.0001937622,0.00000621346,0.0001922607,0.9248646,0.01302973,0.001172977,0.01547366,0.04379227],"study_design_scores_gemma":[0.0006700833,0.0001406902,0.0001295473,0.0001016403,0.00005813405,0.000001260378,0.00002778143,0.8897578,0.09470265,0.0090941,0.005033686,0.0002826824],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01931274,0.00004506338,0.9632264,0.0002628705,0.001523345,0.0008327216,0.0002239118,0.001345209,0.01322777],"genre_scores_gemma":[0.3007646,0.00002738258,0.6924021,0.001286283,0.0002835667,0.0007515759,0.0002980216,0.0001597262,0.004026699],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2814519,"threshold_uncertainty_score":0.9999213,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2314386248","doi":"10.5623/cig2011-045","title":"Soil landscapes of canada: Building a National Framework for Environmental Information","year":2011,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true},"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Landform; Soil map; Digital soil mapping; Soil series; Soil functions; Soil survey; Geography; Soil classification; Geographic information system; Variety (cybernetics); Environmental science; Soil science; Soil water; Cartography; Soil fertility; Mathematics; Soil biodiversity; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.01039958023925394,"gpt":0.1967775331138589,"spread":0.186377952874605,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001167041,0.00005450282,0.00006803928,0.00001532759,0.00006797132,0.000005804103,0.00008435624,0.00002696061,0.0008762837],"category_scores_gemma":[0.0001317879,0.00005210926,0.00001811267,0.00003782576,0.00002815861,0.0001183311,0.0000484825,0.00002933638,0.0000201009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008207068,"about_ca_system_score_gemma":0.0000333036,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01110421,"about_ca_topic_score_gemma":0.007530611,"domain_scores_codex":[0.9993935,0.000005357927,0.0001705331,0.00006048729,0.0002368335,0.0001332937],"domain_scores_gemma":[0.9997179,0.00008441633,0.00008883786,0.00006371326,0.000004827287,0.00004033803],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002622537,0.0006150146,0.1406865,0.0006166809,0.0003274234,0.000007617914,0.02143656,0.0113864,0.006169476,0.53017,0.08425065,0.2040715],"study_design_scores_gemma":[0.001033278,0.0001758964,0.5567195,0.0001013182,0.00005339192,0.00001356839,0.00156686,0.07696877,0.008058415,0.313511,0.04116764,0.000630374],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6934768,0.00001706451,0.2457008,0.0001696231,0.0002344898,0.0004178172,0.0003058066,0.00002529362,0.05965227],"genre_scores_gemma":[0.9190121,0.000001598242,0.08075276,0.0001415019,0.00001191123,0.00002090796,0.00001693879,0.000003331992,0.00003891],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.416033,"threshold_uncertainty_score":0.995481,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2967215329","doi":"","title":"The Way Forward: Advances in Maintaining Right-of-Way of Transmission Lines","year":2019,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Right of way; Transmission (telecommunications); Geography; Telecommunications; Cartography; Computer science; Engineering; Transport engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.004481662449997478,"gpt":0.2282681652229198,"spread":0.2237865027729223,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002258736,0.00005179898,0.0001009272,0.00001504854,0.00004981261,0.000004820895,0.0001300821,0.0000255824,0.0002042448],"category_scores_gemma":[0.00001682695,0.00003143979,0.00003361439,0.000139032,0.00009430467,0.00005830633,0.00002448043,0.00004744005,0.00009471213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001427093,"about_ca_system_score_gemma":0.000004182306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005954143,"about_ca_topic_score_gemma":0.00003683189,"domain_scores_codex":[0.9994026,0.00002583943,0.0002089173,0.00009829584,0.0001441954,0.0001201637],"domain_scores_gemma":[0.9995406,0.0001509812,0.00007250287,0.0002069197,0.000004499587,0.00002447679],"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":[0.00004081263,0.0001201675,0.01430969,0.00008591014,0.00001066643,0.000001032807,0.003164649,0.008527031,0.06875129,0.004756671,0.0002879227,0.8999441],"study_design_scores_gemma":[0.001425732,0.0003383088,0.1826947,0.0006436845,0.00004439855,0.00001479057,0.003196956,0.1367483,0.136651,0.07378422,0.4638883,0.0005695574],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9371328,0.0001646653,0.003609867,0.0005398643,0.00003986652,0.0002146375,0.000001158065,0.00001146012,0.05828565],"genre_scores_gemma":[0.9938971,0.00008515426,0.00559704,0.00001238899,0.000005790187,0.000001324863,0.000001118353,0.000004425642,0.0003956882],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8993746,"threshold_uncertainty_score":0.2236338,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1604308338","doi":"","title":"On the correct determination of transformation parameters of a horizontal geodetic datum","year":2019,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Geophysics and Gravity Measurements","field":"Earth and Planetary Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"York University; University of New Brunswick","funders":"","keywords":"Geodetic datum; Geodesy; Transformation (genetics); North American Datum of 1927; Geography; Geology; Cartography","retraction":null,"screen_n_in":null,"score":{"opus":0.01416236182709665,"gpt":0.1934703632831377,"spread":0.179308001456041,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002345404,0.0000541744,0.000101629,0.00003211379,0.00002647874,0.000008936986,0.0001076763,0.00002076024,0.0003918651],"category_scores_gemma":[0.00003609073,0.00003476262,0.00004296541,0.00008638501,0.0000277086,0.00007602511,0.000002034849,0.00004309663,0.0001449145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001505996,"about_ca_system_score_gemma":0.00001280694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003396969,"about_ca_topic_score_gemma":0.00009174347,"domain_scores_codex":[0.9993744,0.00004344346,0.0001641298,0.00006397428,0.0002625892,0.00009145863],"domain_scores_gemma":[0.9995567,0.0001543517,0.00009317398,0.0001409685,0.0000365738,0.0000182263],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004926731,0.0004553953,0.149143,0.001116362,0.0001665955,0.000002658804,0.01058446,0.003801402,0.01489809,0.009089357,0.0007250718,0.809525],"study_design_scores_gemma":[0.001102052,0.002421316,0.6730663,0.0003315991,0.00009726044,0.000005693266,0.001335046,0.2481339,0.03293082,0.04008898,0.0001317916,0.0003551846],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934218,0.00000547465,0.0004194443,0.00008424769,0.0001567258,0.0002339344,0.00003420279,0.000003898082,0.005640274],"genre_scores_gemma":[0.9996365,0.000001434583,0.0002645078,0.00003749496,0.000003291091,7.640785e-7,0.00003558445,0.000001070485,0.00001934748],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8091698,"threshold_uncertainty_score":0.4290648,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2335751979","doi":"10.5623/cig2012-007","title":"<i>PlotGoogleMaps</i>: The R-Based Web-Mapping Tool for Thematic Spatial Data","year":2012,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":18,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"Science and Engineering Research Board","keywords":"Computer science; Thematic map; Web mapping; World Wide Web; Software; Data mapping; Web application; Web page; Information retrieval; Web modeling; Database; Cartography; Geography; Programming language","retraction":null,"screen_n_in":null,"score":{"opus":0.09536345064276563,"gpt":0.3277436977090112,"spread":0.2323802470662455,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003895329,0.000125423,0.00020852,0.00007213624,0.0013747,0.0001294105,0.0007660405,0.00006301749,0.0001349664],"category_scores_gemma":[0.001346072,0.00008379177,0.00008212564,0.0002948218,0.0002509658,0.0005333701,0.0001576172,0.00007132002,0.0002573598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002830399,"about_ca_system_score_gemma":0.0001202132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003802255,"about_ca_topic_score_gemma":0.000414562,"domain_scores_codex":[0.9982003,0.0001478584,0.0004453746,0.0001268365,0.0005161241,0.0005634927],"domain_scores_gemma":[0.9977216,0.001106049,0.0002356534,0.0007291305,0.0001348524,0.00007276217],"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":[0.00004504927,0.0005016568,0.0590485,0.002106394,0.0007518589,9.673901e-7,0.3388598,0.00005420269,0.0001397209,0.3638225,0.19513,0.03953934],"study_design_scores_gemma":[0.0007767933,0.00002529399,0.005826173,0.0001784958,0.0001117541,0.000002037468,0.04561164,0.006971131,0.00002400341,0.003200732,0.9368728,0.0003991272],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2029666,0.001706166,0.3860667,0.06691191,0.007652839,0.01700218,0.0008535404,0.00182962,0.3150105],"genre_scores_gemma":[0.9942801,0.000006911812,0.003791635,0.000651177,0.0005870773,0.0002618808,0.00003820105,0.00001150198,0.0003715082],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7913135,"threshold_uncertainty_score":0.9999254,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2334801791","doi":"10.5623/cig2011-023","title":"A Scalable GeoWeb Tool for Argumentation Mapping","year":2011,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Public participation GIS; Geospatial analysis; Computer science; Volunteered geographic information; World Wide Web; Deliberation; Geographic information system; Participatory GIS; Scalability; Discoverability; Data science; Crowdsourcing; Metadata; Citizen journalism; GIS and public health; Database; Geography; Remote sensing","retraction":null,"screen_n_in":null,"score":{"opus":0.05995961726030451,"gpt":0.286992956001542,"spread":0.2270333387412374,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008165293,0.00006132346,0.0001062788,0.00008729516,0.0006334172,0.00004900157,0.0001119276,0.0000436797,0.0003209097],"category_scores_gemma":[0.0001839597,0.00005875427,0.00005504195,0.0002104702,0.00009044854,0.0003168705,0.00002208038,0.0000245282,0.0002605137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003126252,"about_ca_system_score_gemma":0.0000353169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006369846,"about_ca_topic_score_gemma":0.0001620078,"domain_scores_codex":[0.9991476,0.00003194464,0.0002604776,0.00008332371,0.0002124243,0.000264256],"domain_scores_gemma":[0.9995151,0.00008091003,0.0001128487,0.0001036867,0.0001501573,0.0000373302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001896583,0.00008277402,0.03701758,0.0002770229,0.0001509471,9.050231e-7,0.5120744,0.000002732711,0.00005898495,0.4239919,0.01447243,0.01185136],"study_design_scores_gemma":[0.001823165,0.0001435138,0.1255534,0.0002367146,0.00008892294,0.000003747052,0.2903024,0.0007644016,0.0003628021,0.1277725,0.4521096,0.0008388475],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3525393,0.00006747875,0.03009029,0.001080467,0.0009002613,0.002244239,0.00001645377,0.000355465,0.612706],"genre_scores_gemma":[0.9811444,0.00001168386,0.01550171,0.000200471,0.0000934794,0.0002871184,0.00000538869,0.000005648962,0.002750097],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6286051,"threshold_uncertainty_score":0.4871797,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4402187667","doi":"10.1016/j.geomat.2024.100023","title":"A comparative analysis of PlanetScope 4-band and 8-band imageries for land use land cover classification","year":2024,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true},"ca_institutions":"University of Prince Edward Island","funders":"Department of Energy, Environment and Climate Action; Natural Resources Canada; Natural Sciences and Engineering Research Council of Canada; Princeton Environmental Institute, Princeton University","keywords":"Land cover; Remote sensing; Support vector machine; Cohen's kappa; Environmental science; Satellite imagery; Agricultural land; Random forest; Land use; Cartography; Computer science; Geography; Artificial intelligence; Machine learning; Ecology","retraction":null,"screen_n_in":null,"score":{"opus":0.03778723101058647,"gpt":0.2737110143003825,"spread":0.2359237832897961,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000121347,0.0001248111,0.0003129175,0.0002253939,0.00003911943,0.0001837795,0.0000453657,0.00005793177,0.00002310301],"category_scores_gemma":[0.00005620721,0.0001108892,0.00005339102,0.0003353776,0.00008658335,0.0002240198,0.000005424171,0.0000600444,0.00001431891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002624736,"about_ca_system_score_gemma":0.00001502175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001950112,"about_ca_topic_score_gemma":0.00004240337,"domain_scores_codex":[0.9993051,0.00002235201,0.0002612412,0.0001757591,0.00010616,0.0001294119],"domain_scores_gemma":[0.9991965,0.000462272,0.0000419353,0.0001997198,0.00005791526,0.00004162254],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004555241,0.0002123454,0.06659061,0.007043647,0.01272527,0.00003634023,0.01831653,0.1083294,0.7273811,0.003350153,0.04034044,0.01521861],"study_design_scores_gemma":[0.0002134495,0.00002984918,0.102823,0.00008356537,0.0007449473,0.000004742006,0.00005106768,0.8824222,0.008845545,0.000138221,0.004485832,0.0001576025],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9466242,0.0005259067,0.04997142,0.0001094268,0.0001129842,0.0003519616,0.0002577963,0.0001780939,0.001868237],"genre_scores_gemma":[0.9961815,0.00006175082,0.00325377,0.000007245508,0.00002488945,0.00001207451,0.0002402461,0.00001531115,0.0002031581],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7740928,"threshold_uncertainty_score":0.4521928,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2527482605","doi":"","title":"AIRBORNE KINEMATIC POSITIONING USING PRECISE POINT POSITIONING METHODOLOGY","year":2019,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Precise Point Positioning; Kinematics; Geodesy; Geography; Remote sensing; Point (geometry); Computer science; Global Positioning System; GNSS applications; Cartography; Mathematics; Physics; Geometry; Telecommunications","retraction":null,"screen_n_in":null,"score":{"opus":0.02076080774955685,"gpt":0.2496749336075192,"spread":0.2289141258579624,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002679789,0.0001403667,0.0002360305,0.0001013132,0.00008023828,0.00004288443,0.0001140524,0.00008979656,0.0005189963],"category_scores_gemma":[0.00008051145,0.0001436808,0.00006521779,0.0001817577,0.0000164193,0.0001966435,0.00003329165,0.0001325296,0.0003771119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008434329,"about_ca_system_score_gemma":0.000007924763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003208125,"about_ca_topic_score_gemma":0.000001820493,"domain_scores_codex":[0.999047,0.00008685049,0.0003160963,0.0001402154,0.0001400703,0.0002697532],"domain_scores_gemma":[0.9993865,0.0001728556,0.00004849562,0.0002899907,0.0000458688,0.00005623436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002382355,0.0000318446,0.0002236679,0.0005812367,0.0001103982,0.00001303757,0.001594782,0.4334646,0.5561856,0.004577192,0.0002618656,0.002931993],"study_design_scores_gemma":[0.000474019,0.00006237337,0.002682011,0.0004020283,0.0000878519,0.0001208138,0.0001625455,0.9383672,0.04967387,0.007581097,0.00004323925,0.0003429806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8898562,0.00009014091,0.1014013,0.0001000292,0.0004151314,0.0002842772,0.00000382398,0.0003063358,0.007542735],"genre_scores_gemma":[0.8890869,0.000002938034,0.1106383,0.00005628745,0.000097987,0.000008245622,0.00002746175,0.00003283799,0.0000490493],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5065117,"threshold_uncertainty_score":0.5859131,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2514400434","doi":"","title":"GPS monitoring of crustal strain in southwest british columbia with the western canada deformation array","year":2019,"lang":"en","type":"article","venue":"GEOMATICA","topic":"earthquake and tectonic studies","field":"Earth and Planetary Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Global Positioning System; Geography; Geology; Geodesy; Seismology; Deformation (meteorology); Strain (injury); Archaeology; Cartography; Remote sensing; Oceanography; Telecommunications","retraction":null,"screen_n_in":null,"score":{"opus":0.006637923804118049,"gpt":0.169153328895874,"spread":0.1625154050917559,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001314008,0.00004880155,0.0001190572,0.0000106439,0.00006997823,0.00006564301,0.00009758959,0.00001833263,0.0004026787],"category_scores_gemma":[0.00001024871,0.000042836,0.00001302147,0.0001062263,0.00003612024,0.00009404465,0.000004677778,0.00007189714,0.00002167004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004971056,"about_ca_system_score_gemma":0.0001093048,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9450272,"about_ca_topic_score_gemma":0.998565,"domain_scores_codex":[0.9993657,0.00002577456,0.000143275,0.00008075892,0.000209586,0.0001748795],"domain_scores_gemma":[0.9996966,0.00009176425,0.0000617018,0.000104017,0.00002007352,0.0000258306],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000002553931,0.000002698665,0.9906602,0.00002515989,0.000009738265,0.000004245945,0.0005070695,0.0003353189,0.000004087503,3.534986e-7,0.0000666139,0.008381963],"study_design_scores_gemma":[0.0001739297,0.00004740438,0.9963226,0.00009498748,0.000004745868,0.00001157462,0.002943365,0.00008179751,0.00001216401,0.00001866386,0.0002267916,0.00006199066],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968335,0.0001325226,0.000006872057,0.00008963441,0.00008671843,0.0001514433,0.0000768184,0.000007557512,0.002614921],"genre_scores_gemma":[0.9995872,0.000009342019,0.00009683923,0.00003073099,0.00002089556,0.000001193713,0.00001397788,0.000001654769,0.000238177],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0535378,"threshold_uncertainty_score":0.4409049,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2262162781","doi":"10.5623/cig2015-305","title":"Exploring the decision tree method FOR MODELLING URBAN LAND USE CHANGE","year":2015,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"","keywords":"Geospatial analysis; Land use; Decision tree; Land use, land-use change and forestry; Change detection; Process (computing); Cohen's kappa; Computer science; Land cover; Geography; Data mining; Machine learning; Remote sensing; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.2600511667339954,"gpt":0.2876552891315791,"spread":0.02760412239758364,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005151865,0.00007668803,0.000101908,0.00001293487,0.0001138275,0.0000639279,0.0001802287,0.00002110221,0.00004665762],"category_scores_gemma":[0.00002670676,0.00004241526,0.0000363053,0.00008069826,0.000004676382,0.0005260459,0.00009422923,0.00003040305,0.0002571043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002920911,"about_ca_system_score_gemma":0.000002282814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008805821,"about_ca_topic_score_gemma":0.0008764664,"domain_scores_codex":[0.9993218,0.00003081073,0.0001323422,0.0001442468,0.0001796196,0.0001911619],"domain_scores_gemma":[0.9993873,0.0002511765,0.00003832575,0.0002331896,0.000006556223,0.00008341511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004581551,0.0003265979,0.2017368,0.0002949524,0.0001449154,0.00002090279,0.0569586,0.3391541,0.0001898652,0.0007883393,0.01769531,0.3822315],"study_design_scores_gemma":[0.0003350249,0.00004512395,0.004611839,0.00004120656,0.00002664993,0.000003658778,0.0002129899,0.9690951,0.0001018182,0.002828939,0.02257942,0.0001182344],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8917612,0.00003140752,0.1068741,0.0002574931,0.0001673001,0.0003055348,0.000005170811,0.00003096961,0.0005668434],"genre_scores_gemma":[0.9355911,0.00002030099,0.06366199,0.0002153021,0.000188006,0.0002439309,0.000005072736,0.00001492146,0.00005940102],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.629941,"threshold_uncertainty_score":0.3304642,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4402629527","doi":"10.1016/j.geomat.2024.100026","title":"Investigating the potential of blockchain technology for geospatial data sharing: Opportunities, challenges, and solutions","year":2024,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Blockchain; Geospatial analysis; Data sharing; Data science; Computer science; Computer security; Geography; Cartography; Medicine","retraction":null,"screen_n_in":null,"score":{"opus":0.1048076310344174,"gpt":0.282276440937279,"spread":0.1774688099028616,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007527647,0.00009893213,0.0001367062,0.0001526263,0.0002637565,0.00005773719,0.001808988,0.0001345911,0.000002795864],"category_scores_gemma":[0.0001308133,0.00007758178,0.0000244717,0.0002395054,0.0003707921,0.00008190207,0.001871108,0.0001738512,0.000001875695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008329904,"about_ca_system_score_gemma":0.000088132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001704148,"about_ca_topic_score_gemma":0.00003353862,"domain_scores_codex":[0.9989414,0.00001886338,0.0002643207,0.0004321182,0.0001048279,0.0002384627],"domain_scores_gemma":[0.9982533,0.0001512723,0.00006970319,0.001435032,0.00005225557,0.00003846363],"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":[2.092153e-7,0.00001620135,0.000002836413,0.0000804442,0.00002668023,0.000001313915,0.0003397753,0.000005082475,0.0001873628,0.8467714,0.0003627359,0.152206],"study_design_scores_gemma":[0.00006290036,0.00003008073,0.00005446397,0.00004128423,0.00002072851,0.00004241642,0.0003191494,0.5926813,0.00008693924,0.4014014,0.005190522,0.00006881681],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02109125,0.01843132,0.8570458,0.1014067,0.00019488,0.0006828047,0.0001071955,0.0007266353,0.0003134729],"genre_scores_gemma":[0.933415,0.0004768074,0.06572133,0.00009085022,0.00005644972,0.0001757273,0.00001992727,0.00001070403,0.00003323708],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9123237,"threshold_uncertainty_score":0.336158,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4401465751","doi":"10.1016/j.geomat.2024.100013","title":"Morphometric analysis in the sub basins of the Kali River using Geographic Information System, Karnataka, India","year":2024,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Groundwater and Watershed Analysis","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Drainage density; Hydrology (agriculture); Drainage basin; Structural basin; Erosion; Watershed; Drainage; Flood myth; Geology; Floodplain; Environmental science; Geomorphology; Geography; Cartography; Geotechnical engineering; Ecology","retraction":null,"screen_n_in":null,"score":{"opus":0.006328138793819242,"gpt":0.1911871717794063,"spread":0.1848590329855871,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007152597,0.00009921212,0.0001671891,0.0006234804,0.0001005868,0.0001211255,0.0003791393,0.00004373643,0.0002287938],"category_scores_gemma":[0.00002173852,0.00005141825,0.000220148,0.006933165,0.0001371041,0.0003928187,0.000115429,0.000101877,0.0001401516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000100383,"about_ca_system_score_gemma":0.000006688617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002094769,"about_ca_topic_score_gemma":0.0001041649,"domain_scores_codex":[0.9987316,0.0001404137,0.0003450166,0.0001222982,0.0004753777,0.0001853672],"domain_scores_gemma":[0.9994504,0.00008277694,0.00008164105,0.0003525885,0.000007342447,0.00002521136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000001993086,0.00002800291,0.9839455,0.0001229803,0.0003128194,0.000006730536,0.005377129,0.008282143,0.0003379461,0.0005522071,0.0001057536,0.0009267945],"study_design_scores_gemma":[0.00005656635,0.000006638364,0.9080696,0.00004459111,0.0006109558,0.000006137652,0.0009058664,0.0895697,0.0002573809,0.0002438943,0.000139002,0.0000896662],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962825,0.00003107577,0.001971082,0.0001241632,0.00005244118,0.0001457945,0.00002051931,0.00001696702,0.001355523],"genre_scores_gemma":[0.9997314,0.000004216326,0.0001555361,0.00006870973,0.000006729652,0.000007964723,0.000009972446,0.000003698778,0.00001175808],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08128756,"threshold_uncertainty_score":0.3331156,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1992426331","doi":"10.5623/cig2013-052","title":"Pedestrian Navigation Services: Challenges and Current Trends","year":2013,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Popularity; Pedestrian; Computer science; Transport engineering; Human–computer interaction; Simulation; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01168479172666241,"gpt":0.2124120167425415,"spread":0.2007272250158791,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003039346,0.00008625828,0.00008798911,0.00007273486,0.00003302363,0.00003514646,0.00007220672,0.00005657091,0.0001072829],"category_scores_gemma":[0.000004471964,0.00007648645,0.00001468611,0.00007643344,0.00002139823,0.0001366007,0.00002071538,0.00006152153,0.0001270097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001134427,"about_ca_system_score_gemma":0.000001591995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008011052,"about_ca_topic_score_gemma":0.000006231807,"domain_scores_codex":[0.9995885,0.000006179205,0.0001200725,0.00008167113,0.00007043343,0.0001331481],"domain_scores_gemma":[0.9997853,0.00001459451,0.00001478231,0.0001323603,0.00001977317,0.00003318521],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[3.522429e-7,0.000009259277,0.0001331409,0.0005858226,0.00001144783,5.137732e-7,0.001061997,0.0001504274,0.00008906071,0.003611633,0.0004084205,0.9939379],"study_design_scores_gemma":[0.002254792,0.0002152053,0.1394944,0.001257753,0.0001261748,0.0000598212,0.008666229,0.6311381,0.01005798,0.09433146,0.1104966,0.001901468],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9419696,0.02208182,0.004005649,0.001051363,0.0005660669,0.0003179957,0.00000939626,0.002973848,0.02702421],"genre_scores_gemma":[0.9978596,0.001586258,0.0003930696,0.000008830384,0.00003361432,0.00006069639,0.00001686058,0.00001241267,0.0000286648],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9920365,"threshold_uncertainty_score":0.3119027,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W8678021","doi":"","title":"A new canadian geoid model in support of levelling by GPS","year":2019,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Geophysics and Gravity Measurements","field":"Earth and Planetary Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Geoid; Geomatics; Levelling; Global Positioning System; Geodesy; Geography; Remote sensing; Geology; Cartography; Computer science; Geophysics; Telecommunications","retraction":null,"screen_n_in":null,"score":{"opus":0.01621717629082492,"gpt":0.1889842903479635,"spread":0.1727671140571386,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001622629,0.00006555327,0.0001262474,0.00006171512,0.00002027891,0.00001392418,0.0001300885,0.00003385869,0.001779793],"category_scores_gemma":[0.000006905418,0.0000608185,0.00002450338,0.0001081996,0.000007959371,0.0000720537,0.000003247934,0.0000568591,0.0006872999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000409229,"about_ca_system_score_gemma":0.0002414433,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3391241,"about_ca_topic_score_gemma":0.2382254,"domain_scores_codex":[0.9992889,0.00001063962,0.0001540596,0.0001125282,0.0001849294,0.000248969],"domain_scores_gemma":[0.9996402,0.00001450844,0.00003489235,0.0001337255,0.00001547494,0.00016117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001422449,0.00002912904,0.9186064,0.00009670445,0.00002622854,0.000006564592,0.001114115,0.03416888,0.0008053189,0.0004365549,0.02006479,0.02463107],"study_design_scores_gemma":[0.001391576,0.0002666416,0.588183,0.00009188418,0.00002801698,0.000004755928,0.0002542204,0.3569306,0.001056958,0.0360419,0.01506637,0.0006840363],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9684735,0.0000466307,0.0002031618,0.0002634208,0.00009002462,0.0001555226,0.0001390325,0.000005314242,0.03062339],"genre_scores_gemma":[0.9970984,0.000002929159,0.001168848,0.0002053821,0.000008181412,1.93643e-7,0.00007611205,0.000001835565,0.001438116],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3304234,"threshold_uncertainty_score":0.9991327,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2885404276","doi":"10.1139/geomat-2018-0008","title":"The rHEALPix Discrete Global Grid System: considerations for Canada","year":2018,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true},"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Geospatial analysis; Grid; Computer science; Key (lock); Geographic information system; Grid cell; Geospatial PDF; Data science; Database; Geography; Remote sensing; Computer security","retraction":null,"screen_n_in":null,"score":{"opus":0.01282472640708965,"gpt":0.2411471220187541,"spread":0.2283223956116645,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003341789,0.0001016798,0.0001315556,0.000007257274,0.0009864414,0.0003832477,0.0005276086,0.00002753502,0.000002839285],"category_scores_gemma":[0.0001673836,0.00006860801,0.0000414571,0.0001448064,0.00006176953,0.00007413965,0.0001023897,0.00003428806,0.00003766724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001277133,"about_ca_system_score_gemma":0.0005911377,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03490134,"about_ca_topic_score_gemma":0.1483753,"domain_scores_codex":[0.9988658,0.00007386056,0.0002871572,0.0002055427,0.0002258379,0.0003417973],"domain_scores_gemma":[0.9985928,0.0004961822,0.0001001246,0.0005391898,0.0001757979,0.00009592804],"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":[0.000002283359,0.000005226758,0.00009832435,0.0000526499,0.00003337614,0.000004328771,0.0001320317,0.0001259807,0.000002665242,0.710705,0.2881747,0.0006634491],"study_design_scores_gemma":[0.000597078,0.0001777464,0.002117649,0.0001765716,0.00002648857,0.000260299,0.0003111465,0.6702206,0.00006046975,0.02677151,0.2988557,0.0004247357],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002644708,0.00009857034,0.9726297,0.006773332,0.004092933,0.0005327667,0.0001798354,0.0002273909,0.01282076],"genre_scores_gemma":[0.9904448,3.291664e-7,0.008693142,0.0002411946,0.0004245477,0.00003824068,0.000007445026,0.000003653237,0.0001466009],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9878001,"threshold_uncertainty_score":0.9715253,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2322046715","doi":"10.5623/cig2012-055","title":"Impact of the Quality of Spatial 3D City Models on Sensor Networks Placement Optimization","year":2012,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"Université Laval","funders":"","keywords":"Software deployment; Terrain; Computer science; Wireless sensor network; Data mining; Spatial analysis; Optimization problem; Real-time computing; Algorithm; Geography; Remote sensing; Cartography; Computer network","retraction":null,"screen_n_in":null,"score":{"opus":0.05912805582302097,"gpt":0.3460437009991641,"spread":0.2869156451761432,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001559769,0.00007361198,0.0001887231,0.00004016751,0.0002443458,0.00001042348,0.0001265335,0.00006132659,0.0001450996],"category_scores_gemma":[0.0002135667,0.00004772175,0.0001222424,0.0002096705,0.0001680703,0.0001726954,0.00004840328,0.00005114879,0.000003068329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005962496,"about_ca_system_score_gemma":0.0000409472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005267827,"about_ca_topic_score_gemma":0.0001324919,"domain_scores_codex":[0.998513,0.0002569752,0.0004474702,0.00005168052,0.0005061828,0.0002247273],"domain_scores_gemma":[0.9989359,0.0001827417,0.0004445508,0.0002047901,0.0001855806,0.00004641175],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00002080922,0.00007804181,0.07763983,0.00002607354,0.00006787444,6.296294e-9,0.01941909,0.8961901,0.000002111954,0.006177876,0.0001329765,0.0002451944],"study_design_scores_gemma":[0.0008809981,0.0001505879,0.5930085,0.0001609503,0.00006938042,4.211144e-7,0.0160128,0.3885992,0.00003986588,0.0006512895,0.0001103608,0.0003156954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8294675,0.00003049205,0.1342059,0.0001706732,0.0003944579,0.0007209537,0.00002478095,0.0000306648,0.03495456],"genre_scores_gemma":[0.9989536,0.00001072496,0.0008686466,0.00001997469,0.00007633492,0.0000107731,0.000002380667,0.000002836526,0.00005466387],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5153686,"threshold_uncertainty_score":0.7963415,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2276168327","doi":"10.5623/cig2012-006","title":"Towards a Framework for Designing Spatial and Non-Spatial Visualizations for Communicating Climate Change Risks","year":2012,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Climate Change Communication and Perception","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false},"ca_institutions":"Mount Allison University","funders":"Mount Allison University","keywords":"Flooding (psychology); Risk perception; Vulnerability (computing); Climate change; Perception; Limiting; Computer science; Coastal flood; Risk analysis (engineering); Environmental resource management; Psychology; Computer security; Sea level rise; Business; Engineering; Environmental science","retraction":null,"screen_n_in":null,"score":{"opus":0.5719927761233653,"gpt":0.5168958418885945,"spread":0.0550969342347708,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001476958,0.0001169074,0.0001875277,0.00006535269,0.001709697,0.0001252586,0.000266939,0.0001617325,0.0001590441],"category_scores_gemma":[0.0009050853,0.0001228131,0.00006856811,0.0001293383,0.0001564245,0.0002630481,0.0001446767,0.00009996695,0.00001576028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005902488,"about_ca_system_score_gemma":0.00002720645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002286611,"about_ca_topic_score_gemma":0.002189724,"domain_scores_codex":[0.998769,0.0002058905,0.0002667035,0.0001268445,0.0001519404,0.0004796077],"domain_scores_gemma":[0.998189,0.001023749,0.0001754132,0.0003299506,0.0001290996,0.0001527741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00007348153,0.0002915455,0.02043785,0.0003820928,0.000039172,5.588162e-8,0.3755592,0.000001814211,0.0002664393,0.1530479,0.0002941331,0.4496063],"study_design_scores_gemma":[0.006257777,0.001045023,0.3027607,0.003031033,0.0009761729,0.000007549052,0.2048214,0.1466958,0.0006668316,0.1222575,0.2079409,0.003539415],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03799899,0.0004343008,0.9482977,0.004683709,0.000418727,0.002640249,0.0001577804,0.0001830734,0.005185508],"genre_scores_gemma":[0.8987056,0.001679475,0.0972359,0.0004253714,0.0007348877,0.001055502,0.0001286681,0.00002444185,0.00001018026],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8607066,"threshold_uncertainty_score":0.9995899,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2210088548","doi":"10.5623/cig2013-004","title":"The Case Study Method in Examining Land Registration Usage","year":2013,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Land Rights and Reforms","field":"Agricultural and Biological Sciences","cited_by":15,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Land registration; Land administration; Grassroots; Context (archaeology); Land titling; Agency (philosophy); Business; Land tenure; Politics; Political science; Law; Geography; Sociology","retraction":null,"screen_n_in":null,"score":{"opus":0.03454711225086791,"gpt":0.2596585957804048,"spread":0.2251114835295369,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003856434,0.00005047201,0.00006634765,0.000003245258,0.0002614374,0.0001078271,0.00008165815,0.00002763012,0.0001179694],"category_scores_gemma":[0.00001793987,0.00000627901,0.00001354759,0.00009219371,0.00001708253,0.00007601097,0.00002195282,0.00005648318,0.00003164545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005414604,"about_ca_system_score_gemma":0.000002197168,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.007674989,"about_ca_topic_score_gemma":0.01803013,"domain_scores_codex":[0.9994898,0.00007622754,0.0001398554,0.00009344364,0.00007049289,0.0001301879],"domain_scores_gemma":[0.9996712,0.0002059447,0.00003754874,0.00004179534,0.00001370561,0.00002986637],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000005160016,0.0002181118,0.0577722,0.00000586615,0.00001703792,0.000427258,0.001680262,0.00000718191,0.002367843,0.0001944541,0.0004283743,0.9368762],"study_design_scores_gemma":[0.0003401283,0.0005465337,0.9630281,0.00001749817,0.0000112061,0.0004888761,0.01808307,0.002373914,0.00008386608,0.006176608,0.008648499,0.0002016654],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972881,0.00001023102,0.000006821774,0.001067527,0.00004095092,0.000276718,6.733494e-7,0.00001482393,0.001294169],"genre_scores_gemma":[0.9981199,0.000006156534,0.00014559,0.00002671758,0.00006627458,0.00002731447,0.000002107661,2.477838e-7,0.001605692],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9366746,"threshold_uncertainty_score":0.9998882,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2484116175","doi":"","title":"EXTRACTION OF ROAD NETWORKS USING PAN-SHARPENED MULTISPECTRAL AND PANCHROMATIC QUICKBIRD IMAGES","year":2005,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"University of New Brunswick; Université du Québec à Montréal; York University","funders":"","keywords":"Panchromatic film; Cartography; Humanities; Geography; Multispectral image; Forestry; Remote sensing; Art","retraction":null,"screen_n_in":null,"score":{"opus":0.01259309500213291,"gpt":0.2441195354685923,"spread":0.2315264404664594,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001469641,0.0001484986,0.0002196197,0.00008322873,0.00005152721,0.00004749342,0.00006496094,0.0000843538,0.00002815246],"category_scores_gemma":[0.00005976812,0.0001550747,0.00003945596,0.0001276691,0.00006122835,0.0003101568,0.0000157139,0.0001152184,0.0000207743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007993983,"about_ca_system_score_gemma":0.000009343448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000326369,"about_ca_topic_score_gemma":0.00001338071,"domain_scores_codex":[0.999086,0.00003553383,0.0003696812,0.0001462425,0.0001301476,0.0002324179],"domain_scores_gemma":[0.9994781,0.00007912292,0.00009500873,0.0002563978,0.0000371142,0.00005426431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00000754026,0.00004330793,0.0001938602,0.0002648593,0.00005723893,0.000004694949,0.0003552361,0.08749605,0.7382635,0.00004068856,0.0002469701,0.173026],"study_design_scores_gemma":[0.0002150457,0.00001146322,0.04894288,0.0001047754,0.00003936709,0.00004903125,0.00004562166,0.9269626,0.02337816,0.0000683249,0.00003822324,0.0001445343],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8753462,0.0006214643,0.1229003,0.00006702308,0.0001282778,0.0001977077,0.000002518317,0.0002379488,0.0004985238],"genre_scores_gemma":[0.9241235,0.00009649096,0.07558372,0.000007849074,0.0001208299,0.000002425876,0.000005914485,0.00003530726,0.00002394369],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8394665,"threshold_uncertainty_score":0.6323763,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}