{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":1640,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":1640,"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":"ff9122f05404","filters":{"topic":"Robotics and Sensor-Based Localization"}},"results":[{"id":"W2151103935","doi":"10.1023/b:visi.0000029664.99615.94","title":"Distinctive Image Features from Scale-Invariant Keypoints","year":2004,"lang":"en","type":"article","venue":"International Journal of Computer Vision","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":55266,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Artificial intelligence; Pattern recognition (psychology); Clutter; Affine transformation; Computer science; Cognitive neuroscience of visual object recognition; Computer vision; Invariant (physics); Hough transform; 3D single-object recognition; Scale-invariant feature transform; Feature extraction; Mathematics; Image (mathematics); Radar","retraction":null,"screen_n_in":null,"score":{"opus":0.003827422997516845,"gpt":0.2291002685932968,"spread":0.22527284559578,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008167628,0.0001067855,0.0001385887,0.0001356301,0.0000242622,0.0001285687,0.0002545165,0.00005024378,0.00003269748],"category_scores_gemma":[0.00001331229,0.00009101976,0.00009546171,0.00005442045,0.00002153437,0.0002617332,0.00003730811,0.0001661477,0.00002329309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001433183,"about_ca_system_score_gemma":0.00002137487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002092007,"about_ca_topic_score_gemma":0.000006992638,"domain_scores_codex":[0.9990767,0.00001848706,0.0003195708,0.00008715503,0.0004092634,0.00008877558],"domain_scores_gemma":[0.9993607,0.00004976856,0.0001051411,0.00007765751,0.0003368948,0.00006979987],"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":[0.0001036831,0.0001110361,0.0001661205,0.000005486478,0.0001829931,0.0003264895,0.0003928655,0.9598663,0.01230162,0.0008449435,0.002414422,0.02328398],"study_design_scores_gemma":[0.007851262,0.0008053505,0.1704838,0.001639626,0.0001043219,0.0009514456,0.00007998564,0.7067423,0.06960829,0.03632257,0.004561108,0.0008498534],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1714287,0.00006331371,0.825494,0.0004795288,0.002178167,0.00003030651,0.00001281769,0.00002872376,0.0002844374],"genre_scores_gemma":[0.9408378,0.00004134146,0.05787215,0.0001340286,0.001069106,2.384608e-7,0.00002219767,0.00001701293,0.000006103325],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7694091,"threshold_uncertainty_score":0.3711678,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2145595389","doi":"10.1111/j.1477-9730.2006.00383.x","title":"Image‐based 3D Modelling: A Review","year":2006,"lang":"en","type":"review","venue":"The Photogrammetric Record","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":1004,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"National Research Council Canada","funders":"","keywords":"Photogrammetry; Computer science; Pipeline (software); Range (aeronautics); Image (mathematics); Image processing; Computer vision; Artificial intelligence; Computer graphics (images); Remote sensing; Geology; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.0593444128970113,"gpt":0.2874285770939984,"spread":0.2280841641969871,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005284696,0.0006552378,0.001750038,0.0006122364,0.0001006081,0.0001174603,0.0006223728,0.0002769681,0.0001087273],"category_scores_gemma":[0.00007239848,0.0004425018,0.0008405961,0.003907556,0.00004889256,0.00004352583,0.00003275189,0.0006346757,0.0002691485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001829804,"about_ca_system_score_gemma":0.00008983265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003660734,"about_ca_topic_score_gemma":0.00001332203,"domain_scores_codex":[0.9974636,0.0001918472,0.001056847,0.0003864499,0.0003746526,0.0005265909],"domain_scores_gemma":[0.9980935,0.0004285052,0.0002701496,0.0009941303,0.0001005191,0.0001132385],"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":[6.594163e-7,0.00002552943,1.079098e-7,0.03697674,0.00007068327,0.000007629356,0.000001272589,0.02258153,6.485508e-8,0.000007612582,0.01319782,0.9271303],"study_design_scores_gemma":[0.00006026688,0.00001540854,1.491066e-8,0.008679034,0.0007515834,0.000006607342,2.854595e-7,0.3272047,4.447984e-7,0.0000162406,0.662926,0.0003394468],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[3.862331e-8,0.6836623,0.3110591,0.000009602272,0.0003966741,0.001155701,0.00002553194,0.0002773466,0.00341367],"genre_scores_gemma":[0.000001117581,0.9893924,0.009201954,0.0001154867,0.0002278558,0.0002333856,0.0004297769,0.000214538,0.0001834733],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9267909,"threshold_uncertainty_score":0.9998026,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2898231767","doi":"10.1002/rob.21831","title":"RTAB‐Map as an open‐source lidar and visual simultaneous localization and mapping library for large‐scale and long‐term online operation","year":2018,"lang":"en","type":"article","venue":"Journal of Field Robotics","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":953,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Lidar; Scale (ratio); Open source; Term (time); Computer science; Computer vision; Artificial intelligence; Remote sensing; Geography; Cartography; Physics; Software; Operating system","retraction":null,"screen_n_in":null,"score":{"opus":0.01201653293020281,"gpt":0.2638744835157507,"spread":0.2518579505855478,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001123414,0.0001154797,0.0001892924,0.00008602235,0.0001341806,0.0002698053,0.00007625484,0.0001245601,0.00001409678],"category_scores_gemma":[0.00006113834,0.0001073983,0.00001652985,0.00006294592,0.00002460606,0.0004895164,0.00004749542,0.0001170906,4.826871e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009956268,"about_ca_system_score_gemma":0.00002087433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002212267,"about_ca_topic_score_gemma":0.00003485085,"domain_scores_codex":[0.999321,0.00002457027,0.0003138293,0.0001122651,0.0000933066,0.0001350387],"domain_scores_gemma":[0.9994986,0.0001181912,0.00008411291,0.00006706633,0.0001075143,0.0001245347],"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":[0.0002177904,0.0002255739,0.01589562,0.0004279885,0.00009993846,0.00004039538,0.003079446,0.9514461,0.002671024,0.0005247535,0.001062728,0.02430864],"study_design_scores_gemma":[0.0007433399,0.000922416,0.0005887555,0.0001170403,0.00003903284,0.00007560142,0.0002443652,0.9943756,0.001242166,0.0001320141,0.00137605,0.0001435975],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2729856,0.0002848789,0.7260012,0.0003561148,0.0001805069,0.0001437726,0.000004640571,0.00002168678,0.00002159137],"genre_scores_gemma":[0.9767691,0.0004957117,0.0214744,0.0005641605,0.0005057147,5.810182e-7,0.00003808601,0.00003758089,0.0001146388],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7045268,"threshold_uncertainty_score":0.4379575,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2004835121","doi":"10.1177/027836402761412467","title":"Mobile Robot Localization and Mapping with Uncertainty using Scale-Invariant Visual Landmarks","year":2002,"lang":"en","type":"article","venue":"The International Journal of Robotics Research","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":779,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Landmark; Computer vision; Artificial intelligence; Mobile robot; Computer science; Scale-invariant feature transform; Robot; Invariant (physics); Simultaneous localization and mapping; Mobile robot navigation; Feature extraction; Mathematics; Robot control","retraction":null,"screen_n_in":null,"score":{"opus":0.05264129411819038,"gpt":0.3149975304159522,"spread":0.2623562362977618,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008118189,0.0001077183,0.0001477998,0.000311027,0.0001412108,0.0002103862,0.0003145254,0.00006018802,0.00004471341],"category_scores_gemma":[0.00006485151,0.00007320246,0.00003615373,0.0002912027,0.0001241774,0.0001559216,0.00004820133,0.0003917322,0.000004378287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001974659,"about_ca_system_score_gemma":0.00003584523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003232018,"about_ca_topic_score_gemma":0.00002077157,"domain_scores_codex":[0.9982607,0.0001084735,0.000334109,0.00009740437,0.000975735,0.0002235649],"domain_scores_gemma":[0.9986544,0.0001824824,0.00008417922,0.0001054359,0.0008810935,0.00009236077],"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":[0.0000335902,0.00003780345,0.0007762663,0.00001610146,0.00009999295,0.00004052768,0.0006139327,0.9941008,0.001918668,0.0002442874,0.0002874942,0.001830522],"study_design_scores_gemma":[0.0004507271,0.0001350887,0.0001200319,0.0001485884,0.00001429642,0.0002420848,0.0004989224,0.9972678,0.0004549877,0.0001592583,0.0004187951,0.00008936058],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08705556,0.000626786,0.9108444,0.0004576919,0.0003283643,0.0001659335,0.000002903697,0.00002094255,0.000497441],"genre_scores_gemma":[0.9930243,0.0006527146,0.005868922,0.00004579083,0.0003046079,0.000001656791,0.000004338916,0.00002813803,0.00006951995],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9059688,"threshold_uncertainty_score":0.2985109,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2745007981","doi":"10.1017/9781316671528","title":"State Estimation for Robotics","year":2017,"lang":"en","type":"book","venue":"Cambridge University Press eBooks","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":735,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Artificial intelligence; Robotics; Kalman filter; Particle filter; Pose; Extended Kalman filter; Computer vision; Computer science; Robot; Context (archaeology); Outlier; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.01912102627894412,"gpt":0.2000162040877149,"spread":0.1808951778087708,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00005303443,0.0002582298,0.000282122,0.0001136856,0.0001989009,0.00008895416,0.0003067678,0.0002577528,3.500697e-7],"category_scores_gemma":[0.00001383245,0.0003376629,0.0001261539,0.000004390399,0.00007181879,0.00008223607,0.00005181963,0.0001914454,0.000005831706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000306042,"about_ca_system_score_gemma":0.00009902819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001258235,"about_ca_topic_score_gemma":0.000001667865,"domain_scores_codex":[0.9992577,0.00001167058,0.0001436796,0.0002249007,0.0001350265,0.0002270554],"domain_scores_gemma":[0.9991441,0.00005052764,0.000115137,0.000456951,0.0001356473,0.00009761928],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002117587,0.000004043887,2.860903e-7,0.0004610983,0.000106558,0.00002920678,0.00002190329,0.6692819,0.00001805881,0.12567,0.2021768,0.002208965],"study_design_scores_gemma":[0.0003534633,0.00002060357,0.000002429496,0.0001086631,0.0001280297,0.000001501965,0.000001873835,0.4988939,0.0001895181,0.00002178664,0.4999858,0.0002923829],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000007231267,0.00003718663,0.4361997,0.000003517853,0.0003480537,0.00036131,0.0002591491,0.0001899502,0.5625939],"genre_scores_gemma":[0.0002767249,0.000068938,0.003020807,0.000009436381,0.00008785837,0.000001117747,0.0005114035,0.00007891862,0.9959448],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4333509,"threshold_uncertainty_score":0.9999076,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2271206385","doi":"10.1561/2300000035","title":"A Review of Point Cloud Registration Algorithms for Mobile Robotics","year":2015,"lang":"en","type":"review","venue":"Foundations and Trends in Robotics","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":691,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; European Commission","keywords":"Robotics; Artificial intelligence; Computer science; Point cloud; Focus (optics); Point (geometry); Perspective (graphical); Image registration; Object (grammar); Computer vision; Mobile robot; Algorithm; Robot; Image (mathematics); Mathematics; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.08526266431262461,"gpt":0.3636447742066176,"spread":0.278382109893993,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004070872,0.0003407056,0.001202379,0.0003914588,0.00005103487,0.00004920188,0.0001367106,0.0002507139,0.00001527113],"category_scores_gemma":[0.00006924036,0.0003254222,0.0002186514,0.0007423329,0.00005979255,0.00009285338,0.00002533602,0.0002031986,0.000003422007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001663036,"about_ca_system_score_gemma":0.00009966712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007371979,"about_ca_topic_score_gemma":0.00002740074,"domain_scores_codex":[0.9982,0.00005730215,0.001089466,0.0002629119,0.0001689306,0.0002214105],"domain_scores_gemma":[0.9989067,0.0001336835,0.0002795532,0.0003848976,0.000209434,0.00008576363],"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":[7.185367e-7,0.00004671828,4.078228e-7,0.04751398,0.00006017601,0.000001059055,0.00002014709,0.2895502,2.894086e-8,0.004634439,0.003475352,0.6546968],"study_design_scores_gemma":[0.0002665902,0.0001119325,4.937954e-7,0.02805188,0.0007425446,0.00001627171,0.00001226601,0.1469328,1.528636e-7,0.0004253729,0.8230479,0.0003918333],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[3.574524e-8,0.8158052,0.1824692,0.00003052548,0.0004878937,0.0005899164,0.0001154868,0.00004610683,0.0004556086],"genre_scores_gemma":[0.000003856102,0.96149,0.03509966,0.00001514949,0.0001552095,0.0001354014,0.002850083,0.00007258028,0.0001780301],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8195725,"threshold_uncertainty_score":0.9999198,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2112103637","doi":"10.1145/1054972.1055012","title":"The bubble cursor","year":2005,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":589,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Cursor (databases); Computer science; Bubble; Fitts's law; Computer vision; Artificial intelligence; Target acquisition; Computer graphics (images); Movement (music); Acoustics; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.003699037095195828,"gpt":0.1713804744151503,"spread":0.1676814373199545,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002931869,0.0000299026,0.00002185336,0.000007151726,0.00004349959,0.00002396548,0.00003798512,0.00001452433,0.00006241745],"category_scores_gemma":[0.000004079916,0.00001911795,0.00001133698,0.00003719994,0.000006108849,0.00002503761,0.000002739293,0.00002480421,0.0001712667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001147682,"about_ca_system_score_gemma":0.000001854099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002587689,"about_ca_topic_score_gemma":0.00002888376,"domain_scores_codex":[0.9998013,0.000002422209,0.00005052872,0.0000273479,0.00004118282,0.00007724861],"domain_scores_gemma":[0.9998778,0.00001659415,0.000002537227,0.00007681928,0.000008981281,0.00001731914],"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":[4.275391e-7,0.000002598941,0.00004292112,0.000001698949,0.00000403872,1.536894e-7,0.00001973603,0.9429706,0.0003638545,0.01645087,0.02287521,0.01726783],"study_design_scores_gemma":[0.00004010171,0.000002408247,0.00008025796,8.474217e-7,0.00000116961,3.989338e-7,0.00001046756,0.7363227,0.002848514,0.00009770968,0.2605629,0.00003248912],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03899037,0.0008930776,0.5973687,0.003858131,0.0006722033,0.0001761491,0.000001322481,0.0008834359,0.3571566],"genre_scores_gemma":[0.9942509,0.00009469085,0.001739736,0.0001131244,0.0001191309,0.000001806258,0.00000164658,0.00001042752,0.003668527],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9552605,"threshold_uncertainty_score":0.2201344,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3015248322","doi":"10.1109/tits.2020.3023541","title":"Deep Learning for Image and Point Cloud Fusion in Autonomous Driving: A Review","year":2021,"lang":"en","type":"review","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":523,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Point cloud; Artificial intelligence; Computer science; Deep learning; Leverage (statistics); Lidar; Sensor fusion; Computer vision; Object detection; Cloud computing; Segmentation; Machine learning; Remote sensing; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.02925058794049247,"gpt":0.2819108817981284,"spread":0.2526602938576359,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003698095,0.0005221548,0.001546171,0.0004114848,0.0001131804,0.00008964441,0.0001158172,0.000342648,0.00004829122],"category_scores_gemma":[0.00000925575,0.0005271846,0.0004854296,0.0005162278,0.00002618763,0.0001156567,2.598483e-7,0.0005444154,0.00002256034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002624381,"about_ca_system_score_gemma":0.00006713778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002901091,"about_ca_topic_score_gemma":0.0001504267,"domain_scores_codex":[0.9972448,0.0001662294,0.001536596,0.0004999599,0.000241881,0.0003105721],"domain_scores_gemma":[0.9990006,0.0002696259,0.0002033943,0.0002638614,0.0001367691,0.0001257329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003214473,0.00005878598,6.890563e-7,0.06886685,0.0001349213,0.00002072953,0.0002719899,0.5624401,0.000004324172,0.00009309223,0.00006084921,0.3680445],"study_design_scores_gemma":[0.0003298605,0.0001226856,0.000001423906,0.113149,0.001263207,0.00004521347,0.0002372521,0.1942802,0.00007304654,0.000004624254,0.6895174,0.000976144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.000003301877,0.4959001,0.501938,0.000005321126,0.000795781,0.001198387,0.0000275012,0.0001116004,0.0000200128],"genre_scores_gemma":[0.001357808,0.9965518,0.0004681007,0.0000134311,0.00007268661,0.0007437227,0.000489921,0.0001509791,0.0001515804],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.6894565,"threshold_uncertainty_score":0.999718,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3003991701","doi":"10.1109/iros40897.2019.8967704","title":"SuMa++: Efficient LiDAR-based Semantic SLAM","year":2019,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":482,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval","funders":"","keywords":"Segmentation; Semantic mapping; Semantics (computer science); Convolutional neural network; Task (project management); Matching (statistics); Projection (relational algebra); Semantic matching","retraction":null,"screen_n_in":null,"score":{"opus":0.004790865206244858,"gpt":0.1788997548915594,"spread":0.1741088896853146,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00005392096,0.0000969173,0.0001027259,0.00006615395,0.0000199138,0.00003064537,0.00006384851,0.00005006498,0.0004468373],"category_scores_gemma":[0.000005944525,0.000087397,0.00004185641,0.0001335561,0.000007777257,0.0000172478,0.00000631762,0.00005728475,0.0008414694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003162902,"about_ca_system_score_gemma":0.00001045406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001032953,"about_ca_topic_score_gemma":0.000005265456,"domain_scores_codex":[0.9994458,0.000008242567,0.0001286851,0.0001127698,0.0001311013,0.0001733893],"domain_scores_gemma":[0.9996813,0.00002860797,0.000009663088,0.0002059653,0.00002858932,0.00004589848],"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":[0.000001720163,0.00001494705,0.0009068055,0.00005015095,0.000005934984,0.000001634167,0.00001783945,0.99365,0.003135311,0.00164069,0.0003252324,0.000249695],"study_design_scores_gemma":[0.0002680258,0.00002184117,0.00086358,0.00001715749,0.00000555425,5.48242e-7,0.00001388163,0.9869229,0.01035727,0.00001422654,0.00138415,0.0001308825],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7209309,0.00003878255,0.2535002,0.00007350316,0.0004887091,0.0001772031,0.000001396542,0.0003963652,0.02439292],"genre_scores_gemma":[0.9982784,0.000002347975,0.0008802484,0.000102051,0.00002695343,0.000001991415,0.00001399533,0.00002722777,0.0006668058],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2773474,"threshold_uncertainty_score":0.9999365,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2096680898","doi":"10.1109/robot.2001.932909","title":"Vision-based mobile robot localization and mapping using scale-invariant features","year":2002,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":476,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer vision; Artificial intelligence; Mobile robot; Computer science; Invariant (physics); Stereopsis; Robot; Mobile robot navigation; Feature (linguistics); Robot control; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.01335926690965794,"gpt":0.2129004041044833,"spread":0.1995411371948253,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006312592,0.0001407503,0.0001325424,0.0001245923,0.0001116089,0.00009252334,0.000046365,0.00009877,0.0001448638],"category_scores_gemma":[0.000009857077,0.000133371,0.00002910947,0.0002434415,0.00002724154,0.00010307,0.00001077892,0.00007255663,0.00001197531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000461644,"about_ca_system_score_gemma":0.000004353324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002782583,"about_ca_topic_score_gemma":0.00001529643,"domain_scores_codex":[0.9993026,0.00002107627,0.0001858425,0.0001690697,0.0001369796,0.0001843958],"domain_scores_gemma":[0.9996746,0.00003516814,0.00002110093,0.0001486391,0.00004196206,0.00007852131],"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":[0.000001135323,0.00001772112,0.0004222345,0.00005141883,0.000007017794,0.000003074972,0.00009301832,0.9902687,0.006560731,0.0001094109,0.0006061213,0.001859404],"study_design_scores_gemma":[0.0002507123,0.00002253102,0.0002831256,0.00005555968,0.00001099153,0.000005793944,0.00005318877,0.9951276,0.003418709,0.00002722107,0.0005647279,0.0001798065],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02095353,0.0004577966,0.976832,0.00004457121,0.0001404624,0.0001756803,0.00000229005,0.0002617109,0.001131914],"genre_scores_gemma":[0.9838272,0.00005998739,0.01570833,0.0001848347,0.00005773032,0.000004851579,0.00002129959,0.00003706415,0.00009875349],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9628736,"threshold_uncertainty_score":0.5438712,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2164638305","doi":"10.1023/a:1008987612352","title":"Using Real-Time Stereo Vision for Mobile Robot Navigation","year":2000,"lang":"en","type":"article","venue":"Autonomous Robots","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":408,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Occupancy grid mapping; Computer vision; Artificial intelligence; Stereopsis; Mobile robot; Grid; Robot; Stereo cameras; Set (abstract data type); Stereo camera","retraction":null,"screen_n_in":null,"score":{"opus":0.01467264046856596,"gpt":0.2617868465914921,"spread":0.2471142061229261,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009857052,0.000185277,0.0002063362,0.0000678589,0.0001260077,0.00007376466,0.00009893817,0.0001284215,0.0002206732],"category_scores_gemma":[0.000003503096,0.0002020247,0.0000795926,0.0001515604,0.00001978555,0.0001952023,0.000008591853,0.00006933817,0.0001546078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001580106,"about_ca_system_score_gemma":0.00002390956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004768569,"about_ca_topic_score_gemma":0.000003057896,"domain_scores_codex":[0.9990287,0.000020424,0.000309461,0.0002281267,0.0001172984,0.00029596],"domain_scores_gemma":[0.9995407,0.00004202607,0.00003682521,0.0002503749,0.00004979374,0.00008020826],"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":[0.000009389046,0.00002341208,0.00001384908,0.00003808974,0.00001459817,0.000002159894,0.0001028247,0.9263881,0.04636219,0.0000624461,0.0002462775,0.02673663],"study_design_scores_gemma":[0.0003666559,0.00009294298,0.000190307,0.00005572564,0.00002655822,0.000007792346,0.000009238474,0.9916248,0.005401073,0.0001350547,0.001841773,0.0002480621],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7379725,0.0001379435,0.2556232,0.00002902504,0.0003602583,0.0009623969,0.00002486379,0.0007863115,0.004103502],"genre_scores_gemma":[0.9553488,0.000077738,0.04244141,0.00003680364,0.0002174273,0.00005628871,0.0003142621,0.0001268216,0.001380438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2173763,"threshold_uncertainty_score":0.8238329,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2910054127","doi":"10.1109/lra.2019.2891991","title":"Deep Reinforcement Learning Robot for Search and Rescue Applications: Exploration in Unknown Cluttered Environments","year":2019,"lang":"en","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":378,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Canada Research Chairs","keywords":"Reinforcement learning; Task (project management); Computer science; Artificial intelligence; Urban search and rescue; Robot; Deep learning; Rescue robot; Search and rescue; Mobile robot; Identification (biology); Frontier; Human–computer interaction; Engineering; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.01267934446708015,"gpt":0.2174006178996612,"spread":0.2047212734325811,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001433401,0.0001202517,0.000128684,0.0001339911,0.00007160639,0.00007257419,0.00004166044,0.00006233763,0.00000357528],"category_scores_gemma":[0.000005245748,0.0001329402,0.00001874644,0.00009563858,0.00001975221,0.0002222882,0.00001085479,0.0000945374,0.00001032437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000710212,"about_ca_system_score_gemma":0.000004030889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007259315,"about_ca_topic_score_gemma":0.000008689943,"domain_scores_codex":[0.9992262,0.00002501775,0.0002622959,0.0001798699,0.0001299719,0.0001766999],"domain_scores_gemma":[0.9997634,0.00004225873,0.00002572291,0.0001117252,0.00001281795,0.00004408274],"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":[0.00000419235,0.000007231563,0.0003716696,0.000104573,0.000009954548,2.561723e-7,0.0002418169,0.9727636,0.02322116,0.0005765147,0.00001464164,0.002684394],"study_design_scores_gemma":[0.000573962,0.00003222442,0.001077843,0.00003413088,0.000008903164,8.203211e-7,0.00006223147,0.9962656,0.001442329,0.00003758189,0.0003159677,0.0001483993],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09092907,0.0000562585,0.9076746,0.0005091001,0.00008673487,0.0006675239,5.151452e-7,0.00005814627,0.00001805364],"genre_scores_gemma":[0.9909369,0.0002169531,0.008366577,0.0001829136,0.00004309153,0.00008114498,0.00009371545,0.000027833,0.00005091177],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9000078,"threshold_uncertainty_score":0.5421144,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2115499947","doi":"10.1109/tro.2013.2242375","title":"Appearance-Based Loop Closure Detection for Online Large-Scale and Long-Term Operation","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Robotics","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":375,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Term (time); Closure (psychology); Computer science; Scale (ratio); Loop (graph theory); Artificial intelligence; Computer vision; Control engineering; Engineering; Mathematics; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.01225182265873736,"gpt":0.2224844239471425,"spread":0.2102326012884051,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005574722,0.0001852737,0.0001639999,0.0001241333,0.0001901439,0.00008513538,0.00005419515,0.0001570696,0.00002639718],"category_scores_gemma":[0.000002385644,0.0001937266,0.00007371078,0.0001450298,0.00002659304,0.0001580781,3.730968e-7,0.0001690175,0.00002245869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006107429,"about_ca_system_score_gemma":0.00001407989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000864149,"about_ca_topic_score_gemma":0.0003487147,"domain_scores_codex":[0.9991678,0.00002041625,0.0002439688,0.000201412,0.0001258701,0.0002405137],"domain_scores_gemma":[0.9995546,0.00003727093,0.00002626749,0.0001863881,0.0001054372,0.00009006535],"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":[0.00001551028,0.0001231306,0.0001148312,0.0001234347,0.00002313922,4.468832e-7,0.00003596782,0.9838267,0.005225744,0.000009055178,0.00002295455,0.01047909],"study_design_scores_gemma":[0.0009434799,0.0001386703,0.001259828,0.00005070483,0.00005688013,0.000002750522,0.00002011737,0.9712365,0.02603964,0.00001825426,0.00001980264,0.0002133881],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1152974,0.00005748775,0.8831508,0.0001452082,0.0005542126,0.0005382462,0.00004095441,0.0002074787,0.000008196965],"genre_scores_gemma":[0.9864948,0.00008104718,0.01294593,0.0001241106,0.00008486299,0.00006286258,0.00004575419,0.00005947208,0.0001011641],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8711974,"threshold_uncertainty_score":0.7899941,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2953941229","doi":"10.1109/cvpr.2019.01214","title":"Monocular 3D Object Detection Leveraging Accurate Proposals and Shape Reconstruction","year":2019,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":328,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Computer vision; Artificial intelligence; Monocular; Benchmark (surveying); Point cloud; Minimum bounding box; Object (grammar); Object detection; Bounding overwatch; Projection (relational algebra); Key (lock); Set (abstract data type); Exploit; Convolutional neural network; Pinhole (optics); Pattern recognition (psychology); Image (mathematics); Algorithm","retraction":null,"screen_n_in":null,"score":{"opus":0.008285531654501792,"gpt":0.1890609395199843,"spread":0.1807754078654825,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006912212,0.00008941854,0.00009043628,0.00007046552,0.0000396843,0.00005640627,0.00002284884,0.0000587011,0.0001102336],"category_scores_gemma":[0.000007384067,0.00008504344,0.00001837903,0.00009695823,0.00000850167,0.0001824038,0.000007197065,0.00006866622,0.00004558355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003466143,"about_ca_system_score_gemma":0.000005287749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002461774,"about_ca_topic_score_gemma":0.00000944591,"domain_scores_codex":[0.999547,0.00001402541,0.000128037,0.0001311793,0.00006409151,0.0001156852],"domain_scores_gemma":[0.9998169,0.00001262326,0.0000163643,0.00009445586,0.00002806558,0.00003161237],"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":[0.000008142381,0.000004981571,0.002668194,0.0001002319,0.00003619447,0.000001605038,0.0001209493,0.4709119,0.1154217,0.0001289765,0.00002057527,0.4105766],"study_design_scores_gemma":[0.0001680811,0.00001988643,0.0007891154,0.00001976657,0.000007350099,0.0000211274,0.00005565899,0.9612391,0.03728701,0.00008811674,0.0001854867,0.0001193245],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8298817,0.00007857016,0.166181,0.00001462929,0.0003946515,0.000183729,4.685033e-7,0.0002373247,0.003027864],"genre_scores_gemma":[0.9965443,0.00007916366,0.00314193,0.00002004488,0.00003658915,0.000003271777,0.000003176258,0.00001974221,0.0001518079],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4903272,"threshold_uncertainty_score":0.346797,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4238681124","doi":"10.1177/027836402128964611","title":"Mobile Robot Localization and Mapping with Uncertainty using Scale-Invariant Visual Landmarks","year":2002,"lang":"en","type":"article","venue":"The International Journal of Robotics Research","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":312,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Landmark; Computer vision; Artificial intelligence; Mobile robot; Computer science; Scale-invariant feature transform; Robot; Invariant (physics); Simultaneous localization and mapping; Feature extraction; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.05264129411819038,"gpt":0.3149975304159522,"spread":0.2623562362977618,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008118189,0.0001077183,0.0001477998,0.000311027,0.0001412108,0.0002103862,0.0003145254,0.00006018802,0.00004471341],"category_scores_gemma":[0.00006485151,0.00007320246,0.00003615373,0.0002912027,0.0001241774,0.0001559216,0.00004820133,0.0003917322,0.000004378287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001974659,"about_ca_system_score_gemma":0.00003584523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003232018,"about_ca_topic_score_gemma":0.00002077157,"domain_scores_codex":[0.9982607,0.0001084735,0.000334109,0.00009740437,0.000975735,0.0002235649],"domain_scores_gemma":[0.9986544,0.0001824824,0.00008417922,0.0001054359,0.0008810935,0.00009236077],"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":[0.0000335902,0.00003780345,0.0007762663,0.00001610146,0.00009999295,0.00004052768,0.0006139327,0.9941008,0.001918668,0.0002442874,0.0002874942,0.001830522],"study_design_scores_gemma":[0.0004507271,0.0001350887,0.0001200319,0.0001485884,0.00001429642,0.0002420848,0.0004989224,0.9972678,0.0004549877,0.0001592583,0.0004187951,0.00008936058],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08705556,0.000626786,0.9108444,0.0004576919,0.0003283643,0.0001659335,0.000002903697,0.00002094255,0.000497441],"genre_scores_gemma":[0.9930243,0.0006527146,0.005868922,0.00004579083,0.0003046079,0.000001656791,0.000004338916,0.00002813803,0.00006951995],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9059688,"threshold_uncertainty_score":0.2985109,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2299529128","doi":"10.1007/s10514-017-9615-3","title":"Revisiting active perception","year":2017,"lang":"en","type":"article","venue":"Autonomous Robots","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":310,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; National Science Foundation","keywords":"Computer science; Perception; Multitude; Robotics; Artificial intelligence; Active perception; State (computer science); Cognitive science; Artificial general intelligence; Human–computer interaction; Data science; Robot; Epistemology; Psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.015810166991793,"gpt":0.2408627263983513,"spread":0.2250525594065583,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006069834,0.0001078752,0.0001194259,0.00003750897,0.0003036151,0.0001423741,0.0001489263,0.00006950943,0.00007910425],"category_scores_gemma":[0.00003506891,0.0001157274,0.00004436287,0.00002331273,0.00002557097,0.0002187681,0.00002416159,0.00009690419,0.0001725017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009859857,"about_ca_system_score_gemma":0.00001067264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003257981,"about_ca_topic_score_gemma":0.000005995509,"domain_scores_codex":[0.9994634,0.00001014902,0.0001331261,0.000134769,0.00007778689,0.0001807413],"domain_scores_gemma":[0.9994923,0.00001299391,0.00004985964,0.0003594712,0.00003354569,0.00005178833],"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":[0.00000311674,0.00000728204,0.0009111996,0.00003434427,0.00002275071,0.00000910076,0.0002770369,0.8229669,0.007656789,0.0008629654,0.0002843184,0.1669641],"study_design_scores_gemma":[0.0002561481,0.00001656719,0.1023324,0.00005706232,0.00002029527,0.000007200104,0.00007226101,0.8924987,0.002233284,0.0002009164,0.002022644,0.0002825024],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6229486,0.0001302051,0.2726746,0.0006870487,0.001425385,0.0003943947,0.00001198099,0.001055627,0.1006721],"genre_scores_gemma":[0.9970775,0.00004117177,0.002246342,0.00003995492,0.0002543526,0.000004978282,0.00001708999,0.00003103114,0.0002875289],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3741289,"threshold_uncertainty_score":0.4719227,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1979426194","doi":"10.1007/s10846-013-9822-x","title":"Robotic Urban Search and Rescue: A Survey from the Control Perspective","year":2013,"lang":"en","type":"article","venue":"Journal of Intelligent & Robotic Systems","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":268,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Urban search and rescue; Search and rescue; Rescue robot; Teleoperation; Robot; Terrain; Computer science; Robotics; Perspective (graphical); Task (project management); Workload; Artificial intelligence; Field (mathematics); Human–computer interaction; Simulation; Mobile robot; Engineering; Systems engineering; Geography; Cartography","retraction":null,"screen_n_in":null,"score":{"opus":0.02311327136300823,"gpt":0.2349557907784731,"spread":0.2118425194154649,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008801392,0.0002080025,0.000476787,0.0001186611,0.00009037795,0.000292988,0.0002646152,0.0001038786,0.00004587283],"category_scores_gemma":[0.0002687405,0.0001358629,0.0001099828,0.0002033459,0.00006840398,0.0001591733,0.00001980348,0.0003691483,0.00005561888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002388808,"about_ca_system_score_gemma":0.00004931025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005358216,"about_ca_topic_score_gemma":0.0001603536,"domain_scores_codex":[0.9979828,0.000406889,0.0007328526,0.0001504795,0.0004416634,0.0002852995],"domain_scores_gemma":[0.99796,0.0007369787,0.0001034562,0.0002518805,0.00076629,0.000181351],"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":[0.00001732773,0.00002571782,0.00871042,0.00002610445,0.0002781833,0.00001025941,0.0009777003,0.9865217,0.0003245014,0.0005179482,0.002439914,0.0001502675],"study_design_scores_gemma":[0.0003893246,0.0001338866,0.03409258,0.0002380563,0.00007872772,0.00007008012,0.003239824,0.9613437,0.0001206015,0.00007057964,0.00004941925,0.0001732175],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1684033,0.01349709,0.8141434,0.0005626662,0.002400856,0.0007735641,0.000009968953,0.00004726172,0.0001618907],"genre_scores_gemma":[0.9986973,0.0003658124,0.0002174469,0.00005486592,0.0005108318,0.000004995679,0.000003879341,0.00004141425,0.0001033967],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8302941,"threshold_uncertainty_score":0.8100056,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3090160518","doi":"10.1109/icra40945.2020.9196860","title":"RoNIN: Robust Neural Inertial Navigation in the Wild: Benchmark, Evaluations, & New Methods","year":2020,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":268,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"","keywords":"Inertial measurement unit; Benchmark (surveying); Computer science; Artificial intelligence; Inertial navigation system; Heading (navigation); Phone; Computer vision; Ground truth; Inertial frame of reference; Geography; Geodesy","retraction":null,"screen_n_in":null,"score":{"opus":0.07106588215320248,"gpt":0.3286866239415446,"spread":0.2576207417883421,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002849467,0.0001067358,0.0001024507,0.00003897472,0.00004053214,0.00006206436,0.0001258275,0.0000594529,0.0002024502],"category_scores_gemma":[0.0001211899,0.00008260264,0.00003600413,0.0003993352,0.00001068577,0.0001208017,0.00001190074,0.0001589634,0.00002717697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003261756,"about_ca_system_score_gemma":0.00002293114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008835948,"about_ca_topic_score_gemma":0.00006040726,"domain_scores_codex":[0.9991577,0.0001534428,0.0002365825,0.0001291621,0.0001826986,0.0001403879],"domain_scores_gemma":[0.999651,0.00009429639,0.00001986208,0.0001420656,0.00003080929,0.00006192394],"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":[0.000003542136,0.000005605364,0.0002344863,0.00001074495,0.000005091621,7.116442e-7,0.0006969944,0.975041,0.00147082,0.0007857866,0.005844688,0.0159005],"study_design_scores_gemma":[0.0002456181,0.00001892823,0.001118105,0.000007148406,0.0000140969,0.000001796422,0.00008547332,0.9934527,0.0004550624,0.0001457265,0.004348048,0.0001072839],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03166682,0.0001532429,0.9615062,0.004365491,0.0001876586,0.0002293845,0.000001229729,0.0001174458,0.001772454],"genre_scores_gemma":[0.881574,0.00002200838,0.1161745,0.001480864,0.0003701845,0.00001208391,0.0002242672,0.00002960391,0.000112529],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8499072,"threshold_uncertainty_score":0.3368438,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4230475428","doi":"10.1002/rob.20342","title":"Visual teach and repeat for long‐range rover autonomy","year":2010,"lang":"en","type":"article","venue":"Journal of Field Robotics","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":261,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Toronto","funders":"","keywords":"Global Positioning System; Computer science; Terrain; Artificial intelligence; Computer vision; Range (aeronautics); Visual odometry; Path (computing); Real-time computing; Geography; Engineering; Aerospace engineering; Robot; Cartography; Telecommunications","retraction":null,"screen_n_in":null,"score":{"opus":0.006166000830726257,"gpt":0.2331132792834897,"spread":0.2269472784527634,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000132247,0.00008103927,0.0001471853,0.00006327537,0.00003670728,0.00004202069,0.00006241426,0.0001170949,0.00001857781],"category_scores_gemma":[0.00008288828,0.00007099978,0.00006198332,0.00003743681,0.00001178144,0.00009254921,0.000008204851,0.0002723968,9.030787e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000155079,"about_ca_system_score_gemma":0.00002423622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001460585,"about_ca_topic_score_gemma":0.00001088425,"domain_scores_codex":[0.9994813,0.000005699181,0.0002535941,0.00005345294,0.00008971275,0.0001162704],"domain_scores_gemma":[0.9995747,0.0001151971,0.00006335032,0.00007813474,0.00009233767,0.00007634795],"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":[0.0000500553,0.00008618155,0.02367449,0.0001942136,0.0001273656,0.00004055768,0.0003641353,0.9387114,0.006238681,0.002676239,0.009192902,0.01864378],"study_design_scores_gemma":[0.00134237,0.0005321921,0.006485353,0.00006525374,0.0001381843,0.0001838114,0.00006034369,0.9735495,0.006584174,0.0006522338,0.01007576,0.0003308546],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1325949,0.0001701941,0.8643743,0.0007648797,0.001424566,0.0001036393,0.000001146683,0.0000266473,0.0005397464],"genre_scores_gemma":[0.970387,0.00006231128,0.02866926,0.0001416312,0.0005516264,6.675527e-7,0.000001578114,0.0000209186,0.0001649994],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8377921,"threshold_uncertainty_score":0.2895287,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2114084853","doi":"10.1109/icra.2012.6225005","title":"Continuous-time batch estimation using temporal basis functions","year":2012,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":256,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Simultaneous localization and mapping; Estimator; Basis (linear algebra); Rendering (computer graphics); Probabilistic logic; Mathematical optimization; Inertial measurement unit; Algorithm; Artificial intelligence; Mathematics; Robot; Statistics; Mobile robot","retraction":null,"screen_n_in":null,"score":{"opus":0.01392417486991174,"gpt":0.2146282597715549,"spread":0.2007040849016432,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008062225,0.00008485545,0.0000904346,0.00006053627,0.00006122071,0.00002933243,0.00002718986,0.00005584857,0.0005123522],"category_scores_gemma":[0.00001418347,0.00008332573,0.00003130597,0.0001269421,0.000009390928,0.0002229731,0.000005941558,0.00004560289,0.0002868517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005071881,"about_ca_system_score_gemma":0.000005914309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004683377,"about_ca_topic_score_gemma":0.000002942691,"domain_scores_codex":[0.9995207,0.00001171965,0.0001415609,0.00006017539,0.00008564471,0.0001802287],"domain_scores_gemma":[0.9997593,0.00001993551,0.00001512379,0.0001062886,0.00003018244,0.00006920678],"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":[0.000001294203,0.00002009795,0.006559163,0.00001268227,0.00001641745,2.48407e-7,0.0000565216,0.9835747,0.004392619,0.0003205766,0.002804285,0.002241368],"study_design_scores_gemma":[0.00009602395,0.00000640977,0.001067464,0.000006749234,0.00002041393,0.000003349286,0.00003189165,0.9952304,0.001961492,0.00001774795,0.001445414,0.0001126177],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1647707,0.00003901602,0.8280862,0.00002856297,0.0003265028,0.00007582932,0.000003090596,0.0002962954,0.006373832],"genre_scores_gemma":[0.9729319,0.000001782521,0.02607885,0.00003106856,0.000116345,0.000002261378,0.00005070665,0.00002475768,0.0007622807],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8081613,"threshold_uncertainty_score":0.5609897,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2106364358","doi":"10.1109/3dim.2005.81","title":"Unsupervised 3D Object Recognition and Reconstruction in Unordered Datasets","year":2005,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":246,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"RANSAC; Artificial intelligence; Computer vision; Computer science; Bundle adjustment; Perspective (graphical); Object (grammar); Scale-invariant feature transform; Invariant (physics); Cognitive neuroscience of visual object recognition; Constraint (computer-aided design); Translation (biology); Rotation (mathematics); Matching (statistics); Pattern recognition (psychology); Structure from motion; Image (mathematics); Motion (physics); Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.01684215282834634,"gpt":0.2009661604307633,"spread":0.184124007602417,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005662749,0.0000687806,0.00007069601,0.00009378753,0.00001898194,0.00002291918,0.00001992568,0.00005240212,0.0001500966],"category_scores_gemma":[0.00001147088,0.00007175461,0.000007863922,0.0001166391,0.00001061333,0.000164787,0.000004687497,0.00005524259,0.00003552512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003102915,"about_ca_system_score_gemma":0.000004421977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004602164,"about_ca_topic_score_gemma":0.0004236892,"domain_scores_codex":[0.9996023,0.00001397021,0.0001413747,0.0001005821,0.00004416691,0.00009765972],"domain_scores_gemma":[0.9998571,0.00001606385,0.000008169422,0.00007760349,0.00001170418,0.00002935832],"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":[0.00001260286,0.00002438312,0.001407213,0.00004941068,0.00001274159,0.000002643916,0.0001352741,0.2166062,0.00435164,0.00005949966,0.0008002729,0.7765381],"study_design_scores_gemma":[0.0006544666,0.00001567359,0.00193595,0.00003074424,0.000006927593,0.0000181728,0.00006795635,0.9917852,0.00374164,0.0002062318,0.001371374,0.0001656512],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9671136,0.0001486707,0.02759487,0.0001101651,0.0001634583,0.0001829745,0.00007034431,0.000215141,0.004400837],"genre_scores_gemma":[0.9864438,0.000295293,0.01250786,0.00007127683,0.00005523484,0.000004491815,0.0005879449,0.00001531094,0.0000187641],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7763724,"threshold_uncertainty_score":0.2926068,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2123537152","doi":"10.1109/ismar.2004.53","title":"Scene Modelling, Recognition and Tracking with Invariant Image Features","year":2005,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":243,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer vision; Artificial intelligence; Computer science; Initialization; Augmented reality; Tracking (education); Invariant (physics); Active appearance model; Virtual image; Tracking system; Video tracking; Computer graphics (images); Object (grammar); Image (mathematics); Mathematics; Kalman filter","retraction":null,"screen_n_in":null,"score":{"opus":0.0203124415215478,"gpt":0.1916801578773437,"spread":0.1713677163557959,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000373141,0.00007201459,0.00006049588,0.00003879555,0.00003178357,0.00005763603,0.00001790996,0.00003713501,0.0000369235],"category_scores_gemma":[0.000002312013,0.00005886539,0.000008358401,0.00005252626,0.00001070481,0.0001428006,0.000002729681,0.00005909639,0.00001036031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001341442,"about_ca_system_score_gemma":0.000003153498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002143158,"about_ca_topic_score_gemma":0.00006523135,"domain_scores_codex":[0.9996819,0.000005146123,0.00007398274,0.00008383812,0.00005959535,0.00009548484],"domain_scores_gemma":[0.9998605,0.00000948022,0.000008501056,0.00005561734,0.00002976259,0.00003615235],"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":[0.000005888889,0.000008117373,0.00002476451,0.0000192151,0.000009012521,0.000002763719,0.0001124467,0.9798605,0.002226741,0.0002041844,0.0002084468,0.0173179],"study_design_scores_gemma":[0.0002078936,0.00001586617,0.000103592,0.00002544091,0.000010482,0.00001153275,0.00002317401,0.9824648,0.01667044,0.0001650385,0.0001921151,0.0001095864],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07507452,0.0001146885,0.9185373,0.00009229225,0.00001974427,0.0000715846,0.00000233999,0.0001540426,0.005933473],"genre_scores_gemma":[0.9121331,0.0001233884,0.0874591,0.00008066156,0.00007067632,0.000001887085,0.0000255312,0.00002064449,0.00008502298],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8370585,"threshold_uncertainty_score":0.2400461,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2109064983","doi":"10.1109/im.2003.1240280","title":"Approximate K-D tree search for efficient ICP","year":2004,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":238,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"","keywords":"Tree (set theory); Mathematics; Depth-first search; Backtracking; Search tree; Algorithm; Outlier; Convergence (economics); Search algorithm; Combinatorics; Computer science; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.01716140711530028,"gpt":0.2296673267466452,"spread":0.2125059196313449,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005521665,0.0000588031,0.00005966398,0.00003969137,0.00003161336,0.00002060341,0.00004279742,0.00003169946,0.00001556097],"category_scores_gemma":[0.000003725153,0.0000519675,0.00002991155,0.00007956448,0.000008269676,0.00001355474,0.00000501624,0.00002958076,0.0000258821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004121337,"about_ca_system_score_gemma":0.000007643966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007461052,"about_ca_topic_score_gemma":0.000006210047,"domain_scores_codex":[0.9996045,0.000002234889,0.00008453941,0.00007612878,0.00007638345,0.0001562134],"domain_scores_gemma":[0.9998258,0.00001271971,0.000003363966,0.00009313331,0.00002578526,0.00003916409],"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":[0.000002224903,0.00001463998,0.000008458356,0.00003407428,0.000004923735,5.074565e-7,0.00005700593,0.9769238,0.002189508,0.01942303,0.0001169699,0.001224906],"study_design_scores_gemma":[0.0004117352,0.00002167791,0.00005172344,0.000006189105,0.000003414661,7.241725e-7,0.00002834567,0.9483266,0.05046422,0.0002083603,0.0003997201,0.00007724221],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06071126,0.00001938146,0.9311946,0.00008988487,0.00009985407,0.0001757374,0.000002591673,0.0001921048,0.007514601],"genre_scores_gemma":[0.9857929,0.000005384957,0.01393211,0.00003410019,0.00003935029,0.000009782162,0.00001528648,0.00002146503,0.0001496293],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9250816,"threshold_uncertainty_score":0.2119173,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2908599206","doi":"10.1109/iros.2018.8593693","title":"CalibNet: Geometrically Supervised Extrinsic Calibration using 3D Spatial Transformer Networks","year":2018,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":227,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Calibration; Point cloud; Artificial intelligence; Computer vision; Lidar; Intrinsics; Remote sensing; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.01637733304067644,"gpt":0.2119557552790482,"spread":0.1955784222383718,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007835526,0.0001598945,0.000157373,0.0001791507,0.00009473458,0.00007255158,0.00008037077,0.000148548,0.0005540695],"category_scores_gemma":[0.00001155625,0.0001505773,0.00005230209,0.0005920895,0.00004034105,0.0001795381,0.000005688645,0.0000984252,0.00001875207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006056162,"about_ca_system_score_gemma":0.00001853437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002360999,"about_ca_topic_score_gemma":0.0001588288,"domain_scores_codex":[0.9990472,0.00002195318,0.0002873367,0.0001680806,0.0001819548,0.0002934865],"domain_scores_gemma":[0.9996128,0.00003060357,0.0000161228,0.0001603161,0.00007571778,0.000104422],"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":[0.00001164979,0.00001729267,0.0004749181,0.00001410122,0.00002058345,0.000002336121,0.00006535731,0.9766228,0.00431749,0.0003581973,0.0002669467,0.01782829],"study_design_scores_gemma":[0.0003451415,0.00005849252,0.0004120835,0.000009543171,0.00002090434,0.000002940475,0.000009491367,0.9941452,0.004136264,0.00002711534,0.0006247753,0.0002080817],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05762019,0.00005957362,0.9389191,0.00002871942,0.0004586916,0.0001597622,0.000002474039,0.0002579719,0.002493473],"genre_scores_gemma":[0.991674,0.00003325182,0.007422377,0.0001580891,0.0005573902,0.00000257331,0.00004251566,0.00004963563,0.00006018284],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9340538,"threshold_uncertainty_score":0.6140363,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2103894593","doi":"10.1109/tpami.2009.146","title":"Designing Highly Reliable Fiducial Markers","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Pattern Analysis and Machine Intelligence","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":226,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Fiducial marker; Computer science; Artificial intelligence; Computer vision; Robustness (evolution); Augmented reality; Pose; Pattern recognition (psychology)","retraction":null,"screen_n_in":null,"score":{"opus":0.01239260680279877,"gpt":0.2288069678692139,"spread":0.2164143610664152,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001100823,0.0001756002,0.0002214906,0.0003420145,0.0001288337,0.00006608695,0.00009036795,0.00006777569,0.0001511968],"category_scores_gemma":[0.000002220418,0.0001691252,0.0001265007,0.0007430151,0.00002102784,0.0000837086,4.024787e-7,0.0001785084,0.00002005877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003433691,"about_ca_system_score_gemma":0.000006132807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002248013,"about_ca_topic_score_gemma":0.0002033291,"domain_scores_codex":[0.9991227,0.00002336492,0.0002734147,0.0002318662,0.0001525189,0.0001961047],"domain_scores_gemma":[0.9996002,0.00004081487,0.00002819749,0.0001958701,0.00004337737,0.00009153354],"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":[0.0000085991,0.00002932364,0.00008201311,0.000007196333,0.0001466653,0.000003942731,0.00005763148,0.765591,0.001143929,0.000009921677,0.00003290529,0.2328869],"study_design_scores_gemma":[0.00006719173,0.00009762507,0.0004725663,0.00002007208,0.0003934113,0.000002549796,0.00002963153,0.822796,0.175706,0.00008176491,0.0001039657,0.0002292054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004499784,0.00008346069,0.994531,0.0001151408,0.0001598418,0.00007184166,0.0000137398,0.0001298382,0.0003953589],"genre_scores_gemma":[0.9974399,0.000476349,0.001663809,0.0002333657,0.00002496526,0.000003903195,0.00001086596,0.00001531715,0.0001315443],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9929401,"threshold_uncertainty_score":0.6896724,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2128086777","doi":"10.1109/iros.2008.4651205","title":"Monocular visual odometry in urban environments using an omnidirectional camera","year":2008,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":219,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Epipolar geometry; Computer vision; Artificial intelligence; Omnidirectional camera; Bundle adjustment; Visual odometry; Computer science; Trajectory; Simultaneous localization and mapping; Monocular; Omnidirectional antenna; Motion estimation; Robot; Mobile robot; Photogrammetry; Image (mathematics)","retraction":null,"screen_n_in":null,"score":{"opus":0.02100645719784434,"gpt":0.2265678925578841,"spread":0.2055614353600397,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003864223,0.00008654445,0.00008756611,0.0001297321,0.00004629124,0.000008634417,0.00003397598,0.00005682691,0.0001019016],"category_scores_gemma":[0.000004384079,0.00009469401,0.00002203689,0.0001591278,0.00001759216,0.0001180103,0.000006584022,0.00006797513,0.00001773503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001024064,"about_ca_system_score_gemma":0.000006687337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001236382,"about_ca_topic_score_gemma":0.000008954312,"domain_scores_codex":[0.9994683,0.00001680884,0.0001366864,0.0001137825,0.0001265968,0.0001378571],"domain_scores_gemma":[0.9998435,0.00000869541,0.000009211721,0.0000800108,0.000004191944,0.00005440113],"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":[0.00000178198,0.00005690025,0.01768736,0.00000308336,0.000007900482,0.0000130074,0.00006819853,0.9661154,0.01570956,0.0000319653,0.0000516969,0.000253126],"study_design_scores_gemma":[0.0001990262,0.00001777979,0.01209485,0.000003572845,0.000002875704,0.00001041073,0.00002109486,0.9772937,0.009544533,0.000007481724,0.0006810834,0.0001235693],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7788848,0.00005945786,0.2201811,0.000002517955,0.00009921934,0.00004489129,7.638488e-7,0.00004478673,0.0006825083],"genre_scores_gemma":[0.9959516,0.0000402116,0.003713118,0.00003224201,0.00006046795,0.000001417361,0.00001816075,0.00002327899,0.0001595344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2170668,"threshold_uncertainty_score":0.386151,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2981556384","doi":"10.1109/iccv.2019.00045","title":"USIP: Unsupervised Stable Interest Point Detection From 3D Point Clouds","year":2019,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":204,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Nutrasource","funders":"","keywords":"Point cloud; Computer science; Detector; Artificial intelligence; Point (geometry); Ground truth; Computer vision; Feature (linguistics); Code (set theory); Lidar; Pattern recognition (psychology); Remote sensing; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.01197275015757723,"gpt":0.1885493413519998,"spread":0.1765765911944225,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00006701223,0.0001395382,0.0001495804,0.00006359111,0.00002901172,0.00006083752,0.00008169143,0.00009308817,0.001632706],"category_scores_gemma":[0.00001070783,0.0001316231,0.00004806798,0.0001276433,0.000007907674,0.0001451598,0.00002274187,0.0001154464,0.0006081819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009354601,"about_ca_system_score_gemma":0.000008151642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00041902,"about_ca_topic_score_gemma":0.0002974138,"domain_scores_codex":[0.9992939,0.00001931509,0.0002117431,0.0001770059,0.0001024879,0.0001955082],"domain_scores_gemma":[0.9995635,0.00003479761,0.00001712596,0.0002746522,0.00004230448,0.00006764306],"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":[0.00002986856,0.00003864553,0.001042353,0.00005724816,0.00006599773,0.000003990107,0.0002434994,0.7883702,0.2014973,0.0009062767,0.0007859482,0.006958711],"study_design_scores_gemma":[0.0004638522,0.00005186409,0.001187208,0.00002517792,0.00001196845,0.000001273803,0.0001399949,0.9246501,0.07099954,0.0003020052,0.001961875,0.0002051358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6943944,0.00003963635,0.2984902,0.00004321883,0.0007244446,0.0001512554,0.000007200843,0.0003188804,0.005830697],"genre_scores_gemma":[0.9972287,0.00002041101,0.002063951,0.000113592,0.00009053777,0.00000342092,0.00004599943,0.000042137,0.0003912921],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3028342,"threshold_uncertainty_score":0.9992799,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4401414715","doi":"10.1109/icra57147.2024.10610243","title":"ConceptGraphs: Open-Vocabulary 3D Scene Graphs for Perception and Planning","year":2024,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":182,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal; University of Toronto","funders":"Army Research Laboratory","keywords":"Computer science; Vocabulary; Perception; Artificial intelligence; Computer vision; Natural language processing; Linguistics; Psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.02218585672817179,"gpt":0.2714699540918887,"spread":0.2492840973637169,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007929909,0.00008963548,0.00009042524,0.00008817302,0.0000549078,0.0001928701,0.000055828,0.00005545525,0.00005204169],"category_scores_gemma":[0.000006123006,0.00008233538,0.00002650439,0.000122929,0.0000194558,0.00015285,0.00001467212,0.00005176548,0.000006176097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001406313,"about_ca_system_score_gemma":0.000006169246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001008706,"about_ca_topic_score_gemma":0.000002911798,"domain_scores_codex":[0.9995622,0.000006429683,0.0001134747,0.0001436225,0.00005191828,0.0001223691],"domain_scores_gemma":[0.9998221,0.00003651838,0.000004731608,0.00007292473,0.00002058995,0.0000430985],"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":[0.00004109295,0.0000338206,0.002000717,0.001127721,0.0002174054,0.00003221273,0.002664889,0.766612,0.02684455,0.0458326,0.04450576,0.1100873],"study_design_scores_gemma":[0.0001981176,0.00003706157,0.000518674,0.0000850411,0.00001874917,0.000004489929,0.0002440904,0.9929307,0.0003856111,0.00105913,0.004379077,0.0001392376],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.078172,0.001737988,0.9136837,0.0000894531,0.0006463402,0.0004327049,0.00001195845,0.0005069672,0.00471887],"genre_scores_gemma":[0.984575,0.0001616091,0.01477689,0.000105905,0.00006676203,0.00002123237,0.00005960326,0.00003312309,0.0001998754],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.906403,"threshold_uncertainty_score":0.3357539,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1990345222","doi":"10.1145/2366145.2366157","title":"Acquiring 3D indoor environments with variability and repetition","year":2012,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":182,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Kootenay Association for Science & Technology","funders":"Seventh Framework Programme; National Science Foundation","keywords":"Computer science; Robustness (evolution); Exploit; Scanner; Artificial intelligence; Mobile device; Computer vision","retraction":null,"screen_n_in":null,"score":{"opus":0.00977535615517298,"gpt":0.1928155461853541,"spread":0.1830401900301811,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001291965,0.0001064806,0.00008062372,0.00008279166,0.0001079832,0.00001663507,0.0000461772,0.00007836898,0.00002905803],"category_scores_gemma":[0.000007451539,0.0001006817,0.00002215409,0.0001483144,0.000051047,0.0001730106,0.000001429377,0.0001398759,0.000005437257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003335581,"about_ca_system_score_gemma":0.000002833508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003940295,"about_ca_topic_score_gemma":0.000005216684,"domain_scores_codex":[0.9994649,0.00002474935,0.0001126979,0.0001142373,0.0001198875,0.0001635667],"domain_scores_gemma":[0.9995582,0.00006232343,0.00001435909,0.0002774777,0.000008030614,0.00007959084],"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":[0.0001328273,0.0006614135,0.04693776,0.0002582727,0.000307725,0.000004251271,0.00129203,0.9050481,0.006031727,0.004078506,0.00003113455,0.03521625],"study_design_scores_gemma":[0.005950297,0.001431225,0.385701,0.00046824,0.00105998,0.0001587446,0.0005427765,0.5218111,0.05429739,0.005895366,0.01927907,0.003404749],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2245381,0.00002608678,0.774902,0.00004868507,0.000114819,0.0001009435,0.000007593622,0.00008597157,0.0001758107],"genre_scores_gemma":[0.9942404,0.0002160565,0.005404326,0.00005935613,0.00002305203,0.0000138276,0.000009336869,0.00002275044,0.00001089786],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7697023,"threshold_uncertainty_score":0.4105679,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2149646227","doi":"10.1109/irds.2002.1041393","title":"Global localization using distinctive visual features","year":2003,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":180,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia; Brampton Civic Hospital","funders":"","keywords":"RANSAC; Artificial intelligence; Computer vision; Computer science; Hough transform; Mobile robot; Robot; Matching (statistics); Frame (networking); Scale-invariant feature transform; Scale (ratio); Simultaneous localization and mapping; Invariant (physics); Polygon mesh; Pattern recognition (psychology); Feature extraction; Mathematics; Image (mathematics); Geography; Computer graphics (images); Cartography","retraction":null,"screen_n_in":null,"score":{"opus":0.008786586830524969,"gpt":0.2406555037158565,"spread":0.2318689168853315,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003240088,0.00008968868,0.00007230115,0.00002305035,0.00005309464,0.00003404409,0.00002495042,0.0000578009,0.00006753433],"category_scores_gemma":[0.00002881762,0.00008515608,0.00002266548,0.0002227813,0.00001398132,0.0000602326,0.000003674637,0.00002862569,0.000007445305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009923794,"about_ca_system_score_gemma":0.00001073308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000276765,"about_ca_topic_score_gemma":0.00003456894,"domain_scores_codex":[0.9995662,0.00001882517,0.00009800253,0.00009238032,0.00009466154,0.000129926],"domain_scores_gemma":[0.9998335,0.00000911306,0.00001040744,0.00006375169,0.00003939416,0.00004383853],"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":[0.000001576504,0.00001060527,0.004252455,0.000009189465,0.000009868562,0.000001681417,0.00002205533,0.9765651,0.0001436016,0.01823263,0.0004006797,0.000350539],"study_design_scores_gemma":[0.0001367006,0.00001134757,0.001466304,0.000006597861,0.00001129363,0.000007000452,0.00006437738,0.9949353,0.001963327,0.0005961442,0.0006735839,0.0001280027],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0398429,0.00006149146,0.9393896,0.000002847636,0.000231075,0.00006198834,0.000001949536,0.0001649564,0.02024315],"genre_scores_gemma":[0.9967427,0.000004611717,0.003087302,0.00004966209,0.00003183084,8.271637e-7,0.00001547348,0.00001409327,0.0000534936],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9568998,"threshold_uncertainty_score":0.3472564,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4387682177","doi":"10.1109/tro.2023.3323938","title":"Present and Future of SLAM in Extreme Environments: The DARPA SubT Challenge","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Robotics","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":178,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval","funders":"Defense Advanced Research Projects Agency; National Aeronautics and Space Administration","keywords":"Simultaneous localization and mapping; Robotics; Robot; Artificial intelligence; Competition (biology); Computer science; Search and rescue; Drone; Field (mathematics); Engineering; Mobile robot","retraction":null,"screen_n_in":null,"score":{"opus":0.03202102561179112,"gpt":0.2121457210149481,"spread":0.180124695403157,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007109412,0.000107975,0.0001146542,0.0001136528,0.00005097274,0.00001049561,0.00007190509,0.00007728288,0.00001873826],"category_scores_gemma":[6.131475e-7,0.00009128275,0.00003561325,0.0002330736,0.00003973834,0.0000445007,8.707574e-7,0.0001591715,0.00001292359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000295582,"about_ca_system_score_gemma":0.000004871978,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008285521,"about_ca_topic_score_gemma":0.00003347927,"domain_scores_codex":[0.9993779,0.00002535654,0.0001838704,0.0001118672,0.0001473296,0.000153686],"domain_scores_gemma":[0.999681,0.00005728256,0.00001713312,0.0002025679,0.00000732618,0.00003469968],"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":[0.00000429831,0.00004320759,0.00001620744,0.00003302463,0.00001880911,0.000003307983,0.0003463824,0.9927337,0.0004501234,0.0002242108,0.00007340337,0.006053278],"study_design_scores_gemma":[0.0003265779,0.00004868306,0.0008511576,0.00002504402,0.00002283226,0.000001614096,0.000331996,0.9937835,0.002713004,0.0001715373,0.001595986,0.0001280831],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01219638,0.000347067,0.9835091,0.002164315,0.0008027779,0.0003179676,0.00001943607,0.0001235273,0.0005193996],"genre_scores_gemma":[0.9955087,0.003512552,0.0006396178,0.0000179937,0.00008700136,0.0000122905,0.00000537402,0.00003282415,0.0001836343],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9833123,"threshold_uncertainty_score":0.3722402,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2139765204","doi":"10.1109/robot.1997.614387","title":"Stereo vision based mapping and navigation for mobile robots","year":2002,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":173,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Occupancy grid mapping; Computer vision; Artificial intelligence; Computer science; Mobile robot; Sonar; Stereopsis; Mobile robot navigation; Robot; Stereo cameras; Motion planning; Stereo camera; Plan (archaeology); Robot control; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.01628397983444002,"gpt":0.2136551870571928,"spread":0.1973712072227528,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004026132,0.0000645416,0.00006397969,0.00004179267,0.00004100679,0.00003519109,0.0000209414,0.00004232381,0.00005953414],"category_scores_gemma":[0.000004062007,0.00006208486,0.00001808604,0.00006561655,0.000006550571,0.00007051797,0.000003297077,0.00002538454,0.000008452743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001655495,"about_ca_system_score_gemma":9.045707e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002084929,"about_ca_topic_score_gemma":0.000001238596,"domain_scores_codex":[0.9996557,0.000005065982,0.0001056403,0.0000863421,0.00005337942,0.0000938691],"domain_scores_gemma":[0.9998264,0.0000335621,0.00001006662,0.00007307504,0.00002385935,0.00003298086],"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":[0.000001296176,0.00001073841,0.0001053087,0.00008931709,0.000004081865,4.171047e-7,0.00006473824,0.9759133,0.005418267,0.0002250456,0.001130081,0.01703736],"study_design_scores_gemma":[0.0002950194,0.00003813122,0.0001641392,0.0000299425,0.000003619709,6.17148e-7,0.00002250909,0.9941671,0.002673529,0.00004665772,0.002473866,0.00008480412],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08153593,0.000125394,0.9167385,0.00005393204,0.00009782206,0.0002589865,0.000002608257,0.0001570032,0.001029864],"genre_scores_gemma":[0.9842548,0.00001667876,0.0153892,0.00005884644,0.00003197845,0.00002030919,0.00003107477,0.00001795677,0.000179136],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9027189,"threshold_uncertainty_score":0.2531747,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4252405433","doi":"10.1145/2010324.1964947","title":"GlobFit","year":2011,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":166,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Kootenay Association for Science & Technology","funders":"Seventh Framework Programme; National Natural Science Foundation of China","keywords":"RANSAC; Robustness (evolution); Outlier; Computer science; Ground truth; Set (abstract data type); Algorithm; Geometric primitive; Object (grammar); Noise (video); Global optimization; Artificial intelligence; Image (mathematics)","retraction":null,"screen_n_in":null,"score":{"opus":0.03453351065816071,"gpt":0.205509405961013,"spread":0.1709758953028523,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003558763,0.00009551115,0.00007162328,0.0001288374,0.00007453507,0.00001087017,0.0001254855,0.00008141181,0.0001631898],"category_scores_gemma":[0.000004240656,0.00009919016,0.00006476312,0.0002987474,0.00002692216,0.00006107225,6.857713e-7,0.0001414287,0.0000581945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001390288,"about_ca_system_score_gemma":0.00000493468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001699392,"about_ca_topic_score_gemma":0.00003629802,"domain_scores_codex":[0.9995512,0.000008739406,0.0001153017,0.00009519209,0.00009546495,0.0001340942],"domain_scores_gemma":[0.9995569,0.0000219101,0.000008300593,0.0003287368,0.00002733,0.00005681168],"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":[0.00007391007,0.0006173893,0.001203381,0.0001702311,0.0004447935,0.00003911416,0.002257476,0.8630027,0.001991313,0.04687688,0.002087598,0.08123524],"study_design_scores_gemma":[0.00298761,0.0009391536,0.02137954,0.0002049171,0.0005135039,0.00006460573,0.00055609,0.7283259,0.1134203,0.09124199,0.03750512,0.002861192],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01517359,0.00004182016,0.9792632,0.00006243337,0.0004289639,0.00007827381,0.00001108213,0.0003932574,0.004547375],"genre_scores_gemma":[0.9947066,0.0002321236,0.004816125,0.0001421493,0.00001498392,0.000007436845,0.000004467146,0.00002687689,0.00004927152],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.979533,"threshold_uncertainty_score":0.4044857,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2133820918","doi":"10.3390/s150923286","title":"INS/GPS/LiDAR Integrated Navigation System for Urban and Indoor Environments Using Hybrid Scan Matching Algorithm","year":2015,"lang":"en","type":"article","venue":"Sensors","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":163,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Lidar; Global Positioning System; Ranging; Inertial navigation system; Computer science; Robustness (evolution); Navigation system; Remote sensing; GPS/INS; Matching (statistics); Iterative closest point; Assisted GPS; Computer vision; Real-time computing; Artificial intelligence; Geography; Point cloud; Inertial frame of reference; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.01547919684346408,"gpt":0.2130410298831363,"spread":0.1975618330396722,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000149626,0.000161506,0.000173096,0.0000833909,0.00007701667,0.00006059845,0.00004737334,0.0000685894,9.346682e-7],"category_scores_gemma":[0.0000132893,0.0001654536,0.00002919707,0.00009070132,0.00002469601,0.00009975144,0.00001248559,0.00009212486,0.000006173225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002674516,"about_ca_system_score_gemma":0.00001475105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000885104,"about_ca_topic_score_gemma":0.000001749303,"domain_scores_codex":[0.9992067,0.00003369298,0.0002331474,0.0001744034,0.000150129,0.0002018831],"domain_scores_gemma":[0.9996488,0.00002290804,0.00004902967,0.0001250071,0.00003187515,0.0001223915],"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":[0.00001555301,0.00001262945,0.0004197719,0.0001253763,0.0000461179,0.00001535536,0.0007439741,0.9887119,0.006578236,0.0001126993,0.00008670654,0.003131691],"study_design_scores_gemma":[0.00054257,0.00003601218,0.00007122313,0.0001185959,0.00002941293,0.00002799878,0.0009028768,0.9833559,0.01388826,0.00005709326,0.000779374,0.0001906985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7655176,0.00007827877,0.2336182,0.000006076243,0.0003031924,0.0002415957,0.00005946946,0.0001009489,0.00007469593],"genre_scores_gemma":[0.9863908,0.000003895738,0.01320755,0.000008318644,0.0001056803,0.000005591754,0.0001910178,0.00005604199,0.00003110134],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2208732,"threshold_uncertainty_score":0.6747001,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3160257224","doi":"10.1023/a:1016636024246","title":"Multi-robot collaboration for robust exploration","year":2001,"lang":"en","type":"article","venue":"Annals of Mathematics and Artificial Intelligence","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":162,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Dalhousie University; McGill University","funders":"","keywords":"Robot; Odometry; Computer science; Artificial intelligence; Computer vision; Modality (human–computer interaction); Mobile robot","retraction":null,"screen_n_in":null,"score":{"opus":0.2377829921572342,"gpt":0.344475517158919,"spread":0.1066925250016848,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001721522,0.00008901588,0.0001340141,0.00006148093,0.00005604347,0.00004965962,0.00004943989,0.0000515369,0.00001350337],"category_scores_gemma":[0.00009256314,0.00008797113,0.00002981254,0.0001612727,0.00003097617,0.0001449106,0.000006314623,0.00002922298,0.000005254656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003983665,"about_ca_system_score_gemma":0.000007340121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002966272,"about_ca_topic_score_gemma":0.00002836929,"domain_scores_codex":[0.9993567,0.000005831677,0.0003455479,0.00009099858,0.0000848132,0.0001161356],"domain_scores_gemma":[0.9995078,0.0000730284,0.00006118579,0.000100942,0.0002189588,0.00003809204],"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":[0.0000084296,0.0001156797,0.000004434448,0.000161736,0.00001558483,7.102608e-7,0.001394674,0.9327926,0.01219774,0.03535825,0.0001647182,0.01778545],"study_design_scores_gemma":[0.00001703116,0.00004832018,0.00000316456,0.00003822318,0.00000703762,8.54661e-7,0.001234717,0.8973715,0.08368797,0.01735705,0.0001442731,0.00008987002],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03065161,0.0001683451,0.9684091,0.0003131525,0.0001010168,0.0002239264,0.000008485104,0.00004158633,0.00008284132],"genre_scores_gemma":[0.8538882,0.0009251435,0.1449507,0.00005478522,0.00007503569,0.00002404069,0.0000233105,0.00002537755,0.00003348086],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8234584,"threshold_uncertainty_score":0.3587359,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1703761565","doi":"10.1109/icinfa.2015.7279659","title":"Convolutional neural network-based image representation for visual loop closure detection","year":2015,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":161,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Convolutional neural network; Computer science; Artificial intelligence; Focus (optics); Representation (politics); Margin (machine learning); Image (mathematics); Computer vision; Deep learning; Pattern recognition (psychology); Feature extraction; Machine learning","retraction":null,"screen_n_in":null,"score":{"opus":0.02689194968211465,"gpt":0.2675600184116189,"spread":0.2406680687295043,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001233271,0.0001000142,0.00009527319,0.00004814915,0.00005608799,0.00004340785,0.00003754427,0.00007443467,0.00002136833],"category_scores_gemma":[0.00004829603,0.0001022313,0.00005473522,0.0001604718,0.00001993267,0.000129319,0.000004887557,0.00005764587,0.00001566648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007092943,"about_ca_system_score_gemma":0.00002222451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001905745,"about_ca_topic_score_gemma":0.00003939885,"domain_scores_codex":[0.9993284,0.00002438338,0.0001803158,0.0001332147,0.0001491855,0.0001845138],"domain_scores_gemma":[0.9995694,0.00005558228,0.00002505083,0.00008971059,0.0001782596,0.00008206129],"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":[0.00004280228,0.00001231988,0.0009168558,0.00001483245,0.00001037152,7.629114e-7,0.000009317468,0.9900478,0.003703015,0.0003013283,0.00406507,0.0008755202],"study_design_scores_gemma":[0.0008316478,0.00008420939,0.0008456804,0.000003734178,0.00001510625,0.000001837498,0.00002184946,0.9841974,0.01306896,0.0002766686,0.0005282106,0.0001246566],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09501196,0.000037846,0.9032366,0.00008049619,0.0006508005,0.0002409859,0.000004714825,0.0002813336,0.0004552556],"genre_scores_gemma":[0.9909846,0.000001449892,0.008146177,0.00009510837,0.0003997134,0.00002668742,0.0001836243,0.00002905953,0.0001335713],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8959727,"threshold_uncertainty_score":0.416887,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2129091674","doi":"10.1177/0278364910369190","title":"Object Recognition in 3D Point Clouds Using Web Data and Domain Adaptation","year":2010,"lang":"en","type":"article","venue":"The International Journal of Robotics Research","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":157,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Office of Naval Research; Multidisciplinary University Research Initiative; Natural Sciences and Engineering Research Council of Canada; Defense Advanced Research Projects Agency","keywords":"Point cloud; Computer science; Domain (mathematical analysis); Object (grammar); Artificial intelligence; Adaptation (eye); Cognitive neuroscience of visual object recognition; Domain adaptation; Robot; Field (mathematics); Robotics; Point (geometry); Computer vision; Data set; Object detection; Set (abstract data type); Machine learning; Data mining; Pattern recognition (psychology)","retraction":null,"screen_n_in":null,"score":{"opus":0.1304818124340743,"gpt":0.3624452842621493,"spread":0.2319634718280749,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002569685,0.00007345519,0.0001034633,0.0003668881,0.00005813712,0.0001506917,0.0005574819,0.00006385976,0.00002275267],"category_scores_gemma":[0.000373565,0.0000583141,0.00002102948,0.0002060383,0.000080288,0.0002670636,0.0001240551,0.0007311075,0.000005124034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001030792,"about_ca_system_score_gemma":0.0001243789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004587135,"about_ca_topic_score_gemma":0.0003156286,"domain_scores_codex":[0.9985289,0.0001140328,0.0003579104,0.00009475154,0.0007415702,0.0001628543],"domain_scores_gemma":[0.9987991,0.0003093514,0.00007275501,0.0001912906,0.0005716664,0.00005581836],"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":[0.00006531948,0.00003732682,0.000793264,0.0000120285,0.000055081,0.00004661402,0.0004937951,0.947285,0.04345724,0.0005927963,0.0001786165,0.006982905],"study_design_scores_gemma":[0.0004416777,0.00003237821,0.0007444893,0.00007316613,0.000007210634,0.0001612512,0.0003856448,0.9929315,0.0005483212,0.004399104,0.0002096101,0.00006559758],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8910311,0.0001286664,0.1060623,0.001230034,0.001056539,0.0001199618,0.00001978136,0.0000109818,0.0003405843],"genre_scores_gemma":[0.9690511,0.0003389633,0.03014506,0.00002468163,0.0003892223,5.409703e-7,0.00002423997,0.00001876391,0.000007385186],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07802,"threshold_uncertainty_score":0.3176339,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2758772066","doi":"10.1016/j.robot.2017.09.010","title":"Keyframe-based monocular SLAM: design, survey, and future directions","year":2017,"lang":"en","type":"article","venue":"Robotics and Autonomous Systems","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":152,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Monocular; Simultaneous localization and mapping; Artificial intelligence; Computer vision; Initialization; Computer science; Robotics; Monocular vision; Field (mathematics); Filter (signal processing); Robot; Mobile robot; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.02164201054065732,"gpt":0.2219662018917059,"spread":0.2003241913510486,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002874345,0.000203982,0.0002857173,0.00007274278,0.0005048642,0.0005622342,0.0001158331,0.0001622605,0.00000227063],"category_scores_gemma":[0.000026167,0.0001972051,0.00003368716,0.00005163491,0.00005970572,0.00009745378,0.00002327942,0.0001246673,0.000005264299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004383619,"about_ca_system_score_gemma":0.00002806441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003319005,"about_ca_topic_score_gemma":0.00005992495,"domain_scores_codex":[0.9991373,0.00006805356,0.000242464,0.0002236527,0.00009218622,0.0002363525],"domain_scores_gemma":[0.9992365,0.00006773397,0.00007999988,0.0004140811,0.00007368092,0.0001280435],"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":[0.000003548314,0.00001539954,0.004420065,0.0001309128,0.00004390247,0.000006690396,0.00005887065,0.9910992,0.0001476325,0.0010939,0.0002395944,0.002740263],"study_design_scores_gemma":[0.0002929274,0.00003685751,0.01266519,0.00004474606,0.00002546979,0.000009476591,0.00002586464,0.9760775,0.0000803186,0.00003512455,0.01045442,0.0002521198],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01966486,0.01049417,0.9650204,0.0003702071,0.00269946,0.000667999,0.00004926836,0.0003774479,0.0006562319],"genre_scores_gemma":[0.9945833,0.001064769,0.003825514,0.00002250255,0.0003016618,0.00001427874,0.00002851786,0.00005509363,0.0001043567],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9749184,"threshold_uncertainty_score":0.8041791,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4388755261","doi":"10.1109/lra.2023.3333742","title":"Swarm-SLAM: Sparse Decentralized Collaborative Simultaneous Localization and Mapping Framework for Multi-Robot Systems","year":2023,"lang":"en","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":146,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal","funders":"Canadian Space Agency","keywords":"Simultaneous localization and mapping; Swarm behaviour; Robot; Computer science; Artificial intelligence; Computer vision; Mobile robot","retraction":null,"screen_n_in":null,"score":{"opus":0.02601459182044358,"gpt":0.254779201941507,"spread":0.2287646101210635,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001505452,0.0002227838,0.0002626655,0.0001983767,0.0002060973,0.0002268511,0.00005796123,0.0001511687,0.00000119949],"category_scores_gemma":[0.0001195843,0.0002369812,0.00003255113,0.0005247681,0.00005094943,0.0001348682,0.00001105896,0.00009246427,0.000008542945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000566876,"about_ca_system_score_gemma":0.00001323051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008266512,"about_ca_topic_score_gemma":0.000004509209,"domain_scores_codex":[0.9988477,0.00004633865,0.0003760072,0.0002500681,0.0001673069,0.0003125458],"domain_scores_gemma":[0.9992545,0.0002949256,0.00009251289,0.0001348974,0.0001206858,0.0001024549],"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":[0.000005622627,0.000009692637,0.0001324796,0.0002825134,0.00005251298,0.00000787194,0.0006786133,0.9917397,0.002850004,0.00294368,0.0006848169,0.0006124216],"study_design_scores_gemma":[0.0006510807,0.00002036348,0.0002211248,0.0001644558,0.00004098806,0.000003887841,0.0002444679,0.9970431,0.0005000785,0.0001411597,0.00069022,0.0002790962],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03062641,0.0002248148,0.9664419,0.0005040771,0.0009091746,0.0006798409,0.00003085021,0.0005794051,0.000003578873],"genre_scores_gemma":[0.9273598,0.0007813848,0.07097177,0.0003891471,0.0001426139,0.00005520693,0.0001883584,0.00008616517,0.00002550684],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8967334,"threshold_uncertainty_score":0.9663814,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2889923199","doi":"10.1109/icra.2018.8460519","title":"Autonomous Vehicle Navigation in Rural Environments Without Detailed Prior Maps","year":2018,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":146,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal","funders":"","keywords":"Waypoint; Computer science; Odometry; Benchmark (surveying); Trajectory; Frame (networking); Real-time computing; Artificial intelligence; Mobile robot; Computer vision; Global Positioning System; Robot; Geography; Telecommunications","retraction":null,"screen_n_in":null,"score":{"opus":0.006430709297873504,"gpt":0.2027611254150328,"spread":0.1963304161171593,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005087437,0.00008128654,0.00007944719,0.00004128201,0.00003018729,0.00002000543,0.00004921784,0.00005481623,0.00009123314],"category_scores_gemma":[0.000004303967,0.00007961331,0.00001538239,0.00007759103,0.00002439489,0.00008802905,0.000009436244,0.00005263366,0.0002387895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008894283,"about_ca_system_score_gemma":0.000004818093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002331179,"about_ca_topic_score_gemma":0.00005088374,"domain_scores_codex":[0.9995163,0.00001155233,0.0001535487,0.00008533754,0.00008553467,0.0001477358],"domain_scores_gemma":[0.9998193,0.000006609311,0.00001340688,0.0001157968,0.000007360371,0.0000375508],"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":[0.00004149407,0.0001278202,0.1845998,0.00006230101,0.000046204,0.00001310469,0.001191368,0.5965849,0.1771385,0.001832588,0.0005841391,0.0377778],"study_design_scores_gemma":[0.0005058372,0.00003701833,0.03648661,0.00002046133,0.000004948967,0.000001371652,0.00004664746,0.933979,0.02773573,0.0001428284,0.0008946757,0.0001448153],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9594808,0.00001506645,0.03799486,0.00002909353,0.0001319817,0.0001289922,0.000001213869,0.0001048482,0.002113186],"genre_scores_gemma":[0.9978186,0.000005769608,0.001671334,0.00003771403,0.0000538135,0.000005468328,0.00002767905,0.00002012238,0.0003595074],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3373942,"threshold_uncertainty_score":0.3246537,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2148557232","doi":"10.1109/iros.2001.973392","title":"Local and global localization for mobile robots using visual landmarks","year":2002,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":144,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Landmark; Computer vision; Artificial intelligence; Computer science; Mobile robot; Invariant (physics); Kalman filter; Robot; Pattern recognition (psychology); Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.01465649035482852,"gpt":0.2414226795827619,"spread":0.2267661892279334,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003347727,0.00009583636,0.00009804661,0.00002606074,0.00005681929,0.00003920598,0.00002583806,0.00007844174,0.00006563792],"category_scores_gemma":[0.000006053659,0.0000934749,0.00002247271,0.0001116485,0.00002215963,0.00007431067,0.000008003952,0.00002495955,0.000004944161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005933268,"about_ca_system_score_gemma":0.000002687735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001858191,"about_ca_topic_score_gemma":0.00002044898,"domain_scores_codex":[0.9995213,0.000007317827,0.0001327617,0.0001132233,0.0000712296,0.000154187],"domain_scores_gemma":[0.9998185,0.00001663216,0.0000114221,0.00005959037,0.00003540885,0.00005844969],"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":[0.000002863933,0.00001398692,0.0005380932,0.00003608062,0.000008986582,7.413017e-7,0.00002093759,0.991152,0.0001114922,0.0006389177,0.0006684568,0.006807441],"study_design_scores_gemma":[0.0003251434,0.00004389316,0.00006203534,0.00001003067,0.000013949,0.00000571727,0.00003718857,0.9979829,0.0004274552,0.00009240368,0.0008756696,0.0001235938],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0240809,0.0002434951,0.9743987,0.000008514882,0.0001194324,0.0001860786,0.000005203304,0.0001310263,0.0008266849],"genre_scores_gemma":[0.9950125,0.00004730376,0.004735561,0.00006420418,0.00004323593,0.000007392196,0.00002312579,0.0000188328,0.00004784145],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9709316,"threshold_uncertainty_score":0.3811796,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2161112350","doi":"10.1007/11957959_4","title":"What and Where: 3D Object Recognition with Accurate Pose","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":142,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Artificial intelligence; Computer vision; Augmented reality; Object (grammar); Pose; Viewpoints; Cognitive neuroscience of visual object recognition; Feature (linguistics); 3D pose estimation; Metric (unit); Object model; Mobile device; 3d model; Computer graphics (images)","retraction":null,"screen_n_in":null,"score":{"opus":0.01157666681071887,"gpt":0.2023655268711988,"spread":0.19078886006048,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001194526,0.0002644182,0.0002109039,0.00024799,0.00007526616,0.0004225618,0.0001634569,0.0001709394,0.00001170621],"category_scores_gemma":[0.000006838877,0.0002273406,0.00002144442,0.0001703526,0.0001848108,0.000373544,0.00004294818,0.0002806709,0.000008038396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008825998,"about_ca_system_score_gemma":0.00004661442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001396046,"about_ca_topic_score_gemma":0.0002127571,"domain_scores_codex":[0.9988976,0.000007522896,0.0001866726,0.0004079432,0.0002645398,0.0002357768],"domain_scores_gemma":[0.9994844,0.00008892365,0.00005201036,0.0002293947,0.00009009988,0.00005519147],"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":[0.000003462967,0.000002940726,0.00001246724,0.00004979766,0.000004741325,0.00002276389,0.0000823989,0.7777253,0.00006609007,0.00003849435,0.00002840717,0.2219631],"study_design_scores_gemma":[0.0002023734,0.00009495068,0.00006399968,0.0007970126,0.00001368863,0.00004039456,2.374336e-7,0.9909495,0.0007290844,0.006133806,0.0005444075,0.0004305958],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0006689987,0.000946995,0.9959379,0.00007794253,0.0008625537,0.0001859992,0.00000431938,0.0001044256,0.001210898],"genre_scores_gemma":[0.6213089,0.004232642,0.3694288,0.001470189,0.002086639,0.00001758106,0.00024076,0.0003394251,0.0008751334],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6265091,"threshold_uncertainty_score":0.9270681,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2922457702","doi":"10.3390/rs11060610","title":"Tight Fusion of a Monocular Camera, MEMS-IMU, and Single-Frequency Multi-GNSS RTK for Precise Navigation in GNSS-Challenged Environments","year":2019,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":141,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"Fundamental Research Funds for the Central Universities; National Key Research and Development Program of China; Wuhan University; National Natural Science Foundation of China","keywords":"GNSS applications; Computer science; Inertial measurement unit; Kalman filter; Extended Kalman filter; Air navigation; Inertial navigation system; Sensor fusion; Satellite system; GNSS augmentation; Computer vision; Remote sensing; Artificial intelligence; Real-time computing; Global Positioning System; Geography; Inertial frame of reference; Telecommunications","retraction":null,"screen_n_in":null,"score":{"opus":0.01644935281492487,"gpt":0.2171013570308638,"spread":0.2006520042159389,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001415374,0.000152304,0.0002288816,0.0001057855,0.00003306703,0.00001643375,0.00003760647,0.0001265823,0.000002949953],"category_scores_gemma":[0.00002885553,0.0001659718,0.00004405681,0.00009193445,0.00002212993,0.00009547167,0.00001617901,0.00009555717,0.000004318041],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001083153,"about_ca_system_score_gemma":0.000006527286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006884815,"about_ca_topic_score_gemma":0.00002318244,"domain_scores_codex":[0.9991121,0.00003069873,0.0003126755,0.0002144742,0.0001389625,0.0001910551],"domain_scores_gemma":[0.9995916,0.00005500529,0.00007023623,0.0002076071,0.00002954419,0.00004594129],"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":[0.00001459163,0.0000202895,0.00009981872,0.000174766,0.00001547539,0.000005256258,0.0006793895,0.2146758,0.727934,0.000009056549,0.00000131967,0.05637025],"study_design_scores_gemma":[0.0008940949,0.00004937402,0.0003824877,0.0003219461,0.00001576337,0.000005564808,0.00009390061,0.9300667,0.06776981,0.0001594562,0.00007506763,0.0001658567],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7964556,0.0003992702,0.2024484,0.00002369595,0.0001340548,0.000422828,0.000003900559,0.00002871385,0.00008350814],"genre_scores_gemma":[0.9574807,0.0001721422,0.04219636,0.000008411452,0.00002437799,7.388766e-8,0.00004872023,0.00004352093,0.00002571634],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7153909,"threshold_uncertainty_score":0.6768135,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4390719155","doi":"10.1017/9781009299909","title":"State Estimation for Robotics","year":2024,"lang":"en","type":"book","venue":"Cambridge University Press eBooks","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":141,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Artificial intelligence; Robotics; Particle filter; Bundle adjustment; Kalman filter; Computer vision; Pose; Extended Kalman filter; Robot; Computer science; Outlier; Inertial measurement unit; Machine learning; Photogrammetry","retraction":null,"screen_n_in":null,"score":{"opus":0.01445612392829241,"gpt":0.1910384622767757,"spread":0.1765823383484833,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0000468112,0.0002608942,0.0002468667,0.0001659674,0.00006975898,0.00007249379,0.0001702156,0.0002388775,4.547981e-7],"category_scores_gemma":[0.000005830586,0.000330325,0.0001363623,0.00001423385,0.00004474738,0.00005089628,0.00004746325,0.0002342632,0.00001574846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003888247,"about_ca_system_score_gemma":0.00009414605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006937375,"about_ca_topic_score_gemma":0.000001020695,"domain_scores_codex":[0.9992361,0.00001075052,0.0001576299,0.0002447226,0.0001364025,0.0002143732],"domain_scores_gemma":[0.9994649,0.00005601909,0.00004456988,0.0002494866,0.00009730257,0.00008771384],"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":[0.000009929837,0.00000222695,3.982614e-8,0.0007300308,0.0000973012,0.00003215535,0.00002337407,0.5611774,0.00001447238,0.1942892,0.2427119,0.0009119041],"study_design_scores_gemma":[0.0001610978,0.0000174715,2.827213e-7,0.0001355069,0.0001668149,0.000001721051,0.000002958476,0.541975,0.0001514947,0.00004167893,0.4571112,0.0002348323],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000006280483,0.0001200988,0.4502454,0.000005314046,0.0005253742,0.0003719406,0.0003539349,0.0003913835,0.5479802],"genre_scores_gemma":[0.0001753871,0.00007123918,0.002622036,0.00001316865,0.00009338347,0.000001328256,0.0005511717,0.0001037889,0.9963685],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4483882,"threshold_uncertainty_score":0.9999149,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2122301224","doi":"10.1007/s11263-012-0587-7","title":"Modeling Coverage in Camera Networks: A Survey","year":2012,"lang":"en","type":"article","venue":"International Journal of Computer Vision","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":138,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Context (archaeology); Artificial intelligence; Computer vision; Network planning and design; Data mining; Computer network; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.01389906773714351,"gpt":0.2573686605412988,"spread":0.2434695928041553,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000445472,0.00007524998,0.0001191885,0.0001872497,0.000009977811,0.0000544845,0.0001608477,0.00004754779,0.0000117321],"category_scores_gemma":[0.00001410853,0.00006964841,0.00004756539,0.00008130817,0.000004686284,0.0003249643,0.0000240485,0.0001657001,0.000004240243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009367012,"about_ca_system_score_gemma":0.000008971689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002053396,"about_ca_topic_score_gemma":0.000009217842,"domain_scores_codex":[0.9991556,0.00005250346,0.0003624554,0.00004286321,0.0002645331,0.0001220641],"domain_scores_gemma":[0.9995783,0.00006782684,0.00005333105,0.00004973032,0.0001916974,0.00005913199],"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":[0.00002555053,0.00003771843,0.006662063,0.000002051433,0.00002498071,0.00001347883,0.00008328658,0.9811399,0.00004798298,0.00007217193,0.0003074354,0.01158336],"study_design_scores_gemma":[0.0003622275,0.00003005069,0.01714132,0.00008350068,0.00000222634,0.00003849836,0.000002348884,0.9819989,0.00002307101,0.00004563987,0.0002035584,0.00006868599],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3577239,0.0001926833,0.640215,0.00002332279,0.001786447,0.00001647165,0.000001022094,0.000007994076,0.00003309577],"genre_scores_gemma":[0.9960818,0.0001828528,0.002851024,0.0000878406,0.0007693568,1.75704e-7,0.00001153174,0.00001324573,0.00000219455],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6383579,"threshold_uncertainty_score":0.284018,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2056798562","doi":"10.1006/gmod.2001.0554","title":"A Silhouette-Based Algorithm for Texture Registration and Stitching","year":2001,"lang":"en","type":"article","venue":"Graphical Models","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":127,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Image stitching; Silhouette; Computer vision; Artificial intelligence; Computer science; Texture (cosmology); Position (finance); Process (computing); Texture mapping; Image (mathematics); Computer graphics (images); Image registration","retraction":null,"screen_n_in":null,"score":{"opus":0.01582594386614879,"gpt":0.2139958481717614,"spread":0.1981699043056126,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007513446,0.0001053134,0.0001064704,0.00007523517,0.00007125185,0.00004730295,0.00004148589,0.0001129372,0.00000251802],"category_scores_gemma":[0.000008907537,0.0001022558,0.00004476886,0.0001412685,0.00002409999,0.0000975348,0.000003397111,0.00009675766,4.99138e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001190663,"about_ca_system_score_gemma":0.00000686977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008802847,"about_ca_topic_score_gemma":0.00001310776,"domain_scores_codex":[0.9994404,0.00000991968,0.0001427448,0.0001458047,0.0001024366,0.0001586482],"domain_scores_gemma":[0.9997177,0.0000493545,0.00001611045,0.000108482,0.00003773908,0.00007057669],"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":[0.000008021746,0.00001552282,0.00004521454,0.00002574188,0.00001133217,0.00000372687,0.00002891609,0.8968678,0.0003961381,0.01211425,0.0002388701,0.0902445],"study_design_scores_gemma":[0.0003659138,0.00003212682,0.00007912573,0.00001844632,0.00001401183,0.000003013409,0.000005409367,0.9798902,0.00007601952,0.01887937,0.0005093638,0.0001270508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01168844,0.0001861702,0.9871171,0.0003215649,0.00007078856,0.000183271,0.00001025068,0.0001586141,0.0002638133],"genre_scores_gemma":[0.96986,0.00007625412,0.02968041,0.0001943141,0.0000828556,0.00002016787,0.00004501429,0.00002489556,0.00001610137],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9581715,"threshold_uncertainty_score":0.4169871,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2163003390","doi":"10.1177/0278364908096316","title":"3D Perception and Environment Map Generation for Humanoid Robot Navigation","year":2008,"lang":"en","type":"article","venue":"The International Journal of Robotics Research","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":117,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"University of British Columbia","keywords":"Computer vision; Artificial intelligence; Computer science; Humanoid robot; Segmentation; Occupancy grid mapping; Robot; Stereopsis; Noise (video); Mobile robot","retraction":null,"screen_n_in":null,"score":{"opus":0.09760256191343164,"gpt":0.3254271614327084,"spread":0.2278245995192768,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007821175,0.00007788154,0.00009417805,0.0001686822,0.0001905673,0.0000769053,0.0002318823,0.00005300839,0.0000223791],"category_scores_gemma":[0.00004837389,0.00006123339,0.00004716147,0.00004299768,0.00009664207,0.000145812,0.00003323621,0.000234584,0.0000113758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002169271,"about_ca_system_score_gemma":0.00003585251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005544931,"about_ca_topic_score_gemma":0.000002182975,"domain_scores_codex":[0.9986647,0.00006117059,0.0003059881,0.00008357701,0.0007402336,0.0001443633],"domain_scores_gemma":[0.999186,0.0001269915,0.00006541616,0.00009739104,0.0004708787,0.00005333582],"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":[0.00002494711,0.00002446005,0.00009478997,0.00001105489,0.00004845564,0.000007550278,0.0004441805,0.9380569,0.05599423,0.0005303849,0.002152669,0.002610405],"study_design_scores_gemma":[0.000463676,0.0001336402,0.0008014865,0.00003268569,0.00001241163,0.0001341753,0.000106977,0.992466,0.003118193,0.0008295474,0.001819078,0.00008212753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2410865,0.0003633341,0.7547662,0.002619817,0.0007870546,0.0002585254,0.000006331935,0.00001529449,0.00009702377],"genre_scores_gemma":[0.9799013,0.001348778,0.01750247,0.00003604223,0.0009091593,0.000005779693,0.00004003764,0.00002275958,0.0002337178],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7388148,"threshold_uncertainty_score":0.2497025,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2084635560","doi":"10.1109/icra.2012.6224891","title":"A textured object recognition pipeline for color and depth image data","year":2012,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":117,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Canadian Institute for Advanced Research; U.S. Department of Defense; National Science Foundation","keywords":"Artificial intelligence; Computer vision; Computer science; Cognitive neuroscience of visual object recognition; Pipeline (software); Object (grammar); Pose; Segmentation; Fidelity; Robotics; Object detection; 3D single-object recognition; Perception; Image segmentation; Robot; Pattern recognition (psychology)","retraction":null,"screen_n_in":null,"score":{"opus":0.05083619574030567,"gpt":0.2667008357370874,"spread":0.2158646399967817,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001099276,0.00006485709,0.00006989735,0.00002829802,0.00002760923,0.00002492679,0.00004432404,0.0000420207,0.00003761505],"category_scores_gemma":[0.00005592371,0.00005762895,0.000009966057,0.00004688249,0.000008693763,0.000197636,0.0000157976,0.00002835499,0.00001793861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009447401,"about_ca_system_score_gemma":0.00000331163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007297112,"about_ca_topic_score_gemma":0.00002877176,"domain_scores_codex":[0.9996396,0.000006300127,0.00009557451,0.00008310316,0.00003935786,0.0001360194],"domain_scores_gemma":[0.9997231,0.00004369969,0.000009809601,0.0001444626,0.00002835364,0.00005055151],"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":[0.0002196824,0.0003832596,0.002675582,0.001217911,0.0002235325,0.000004701337,0.0009086968,0.02620572,0.1535422,0.002397721,0.3842642,0.4279568],"study_design_scores_gemma":[0.0003699239,0.00001411675,0.0004318522,0.000007624771,0.00002731232,0.000003076207,0.00003754256,0.9877254,0.005933497,0.00008595489,0.005250746,0.00011289],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01512635,0.0001943605,0.9802675,0.00006169359,0.0001836129,0.0002567027,0.00008413939,0.0001550356,0.003670627],"genre_scores_gemma":[0.9472806,0.00006184692,0.05115864,0.0001034163,0.0002036126,0.00001026282,0.0009647153,0.00002497594,0.000191875],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9615197,"threshold_uncertainty_score":0.235004,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2137596640","doi":"10.1109/tmi.2007.901984","title":"Point-Based Rigid-Body Registration Using an Unscented Kalman Filter","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":112,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"Johns Hopkins University","keywords":"Kalman filter; Computer science; Computer vision; Point (geometry); Artificial intelligence; Extended Kalman filter; Rigid body; Fast Kalman filter; Unscented transform; Physics; Mathematics; Geometry; Classical mechanics","retraction":null,"screen_n_in":null,"score":{"opus":0.01604256381870591,"gpt":0.2667263843505842,"spread":0.2506838205318783,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004155924,0.0001886297,0.000150361,0.000246285,0.0001696996,0.00005837894,0.0001208656,0.0001152981,0.0002869957],"category_scores_gemma":[0.00001607113,0.000197448,0.00007833324,0.0002982935,0.00008066248,0.0002510532,3.636401e-7,0.0003728356,0.00001921589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000146524,"about_ca_system_score_gemma":0.00005259801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008425948,"about_ca_topic_score_gemma":0.0001001622,"domain_scores_codex":[0.9984641,0.00004376997,0.000387152,0.0002356293,0.000517646,0.0003516765],"domain_scores_gemma":[0.9992481,0.00008121308,0.00003683489,0.0002608945,0.0000667647,0.0003062323],"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":[0.00002834442,0.0001962752,0.00006330473,0.00004558036,0.0000244988,0.00008184983,0.00007449498,0.9613103,0.02082376,0.00006251753,0.0001645295,0.01712453],"study_design_scores_gemma":[0.0005702712,0.00002472454,0.00007449596,0.0001035138,0.00003770558,0.0000219612,0.00005875177,0.9468257,0.0517692,0.00002444102,0.0002833784,0.000205846],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03613778,0.00001928881,0.9618372,0.0002627654,0.0007911772,0.0001276567,0.000006056067,0.0004058764,0.0004122168],"genre_scores_gemma":[0.9943506,0.00000815333,0.004796688,0.0005983132,0.0001341006,0.0000030693,0.00002883027,0.00005322104,0.00002708338],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9582127,"threshold_uncertainty_score":0.8051696,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4221112862","doi":"10.3390/drones6040085","title":"Simultaneous Localization and Mapping (SLAM) and Data Fusion in Unmanned Aerial Vehicles: Recent Advances and Challenges","year":2022,"lang":"en","type":"article","venue":"Drones","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":111,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Simultaneous localization and mapping; Artificial intelligence; Computer vision; Odometry; Sensor fusion; Computer science; Kalman filter; Robotics; Extended Kalman filter; Search and rescue; Fuse (electrical); Photogrammetry; Object (grammar); Scalability; Robot; Mobile robot; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.02938577811892392,"gpt":0.2340428110544115,"spread":0.2046570329354876,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001186002,0.00008420871,0.000107343,0.00007098243,0.0001020189,0.0000250814,0.00005402764,0.00003089155,0.000007179662],"category_scores_gemma":[0.00003473811,0.00009175386,0.000003044172,0.00009369889,0.00002450014,0.0001138544,0.00012108,0.00005849398,2.533021e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000213302,"about_ca_system_score_gemma":0.000004229028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001131997,"about_ca_topic_score_gemma":0.00009530163,"domain_scores_codex":[0.9994332,0.00003649576,0.0001322992,0.0002006314,0.00008968262,0.0001076828],"domain_scores_gemma":[0.9997511,0.00006182526,0.00002038245,0.0001255072,0.0000115791,0.00002963619],"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":[0.00003022791,0.00002019937,0.0006701257,0.0002788931,0.000007282064,0.00001613715,0.001431449,0.7825192,0.0006252535,0.0002902726,0.00003166409,0.2140793],"study_design_scores_gemma":[0.00039406,0.00004051824,0.000340419,0.00002838877,0.000005292175,0.000008630155,0.001077724,0.9407093,0.00005862495,0.0002986922,0.05691447,0.0001239171],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8409684,0.1318054,0.0244024,0.001278533,0.0006132604,0.0004786795,0.00007118744,0.0001996537,0.0001825212],"genre_scores_gemma":[0.89485,0.1047516,0.0001923477,0.00002410557,0.0000401381,0.000004950044,0.0001165318,0.00001534721,0.000005011022],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2139554,"threshold_uncertainty_score":0.3741614,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}