[{"data":1,"prerenderedAt":548},["ShallowReactive",2],{"method-clic2023":3},{"method":4,"reference":62,"equipment":87,"figures":133,"results":134},{"id":5,"label":6,"shortName":7,"title":8,"year":9,"era":10,"cluster":11,"scope":12,"keyIdeaZh":13,"keyIdeaEn":14,"fulltextStatus":15,"publicationStatus":16,"recommendation":17,"constructionRelevance":18,"validationEnvironment":19,"strengths":23,"limitations":29,"sensors":33,"platform":37,"estimator":42,"association":43,"timeModel":44,"deskew":45,"loopClosure":46,"globalOptimization":47,"mapRepresentation":48,"prior":49,"outputGeometry":50,"compute":51,"codeUrl":52,"codeLicense":53,"relatedVersions":54},"clic2023","Lv et al., 2023","CLIC","Continuous-Time Fixed-Lag Smoothing for LiDAR-Inertial-Camera SLAM",2023,"recent","C07","full_slam_with_global_correction","CLIC 以分段三次 B 樣條表示連續時間軌跡，在固定時間長度的滑動視窗內做平滑：LiDAR 點到平面、原始 IMU、偏差與視覺重投影因子都在各自量測時刻取軌跡位姿，並推導解析雅可比矩陣、以邊緣化保留舊狀態的資訊，使連續時間方法可即時運行。框架可接入一至兩顆 LiDAR 與相機，並線上估計相機與 IMU 相對 LiDAR 的時間偏移。","Continuous-time fixed-lag smoothing on a split cubic B-spline with LiDAR point-to-plane, raw IMU and visual reprojection factors, analytic Jacobians and marginalization, supporting multiple LiDARs, a camera and online time-offset calibration in real time.","full_text_reviewed","peer_reviewed_published","supplementary","CLIC 的連續時間軌跡讓每個 LiDAR 點都在自己的時刻取位姿，等同內建點雲去畸變，對手持或無人機劇烈晃動時的點雲品質特別有幫助（推論），NCD06 手持劇烈晃動序列的結果支持這一點。測試包含校園建物、室內動作捕捉房與空曠植生區，但沒有施工現場或點雲精度評估。",[20,21,22],"public_benchmark","independent_reference","controlled_experiment",[24,25,26,27,28],"On NTU VIRAL, CLIO and CLIC average APE RMSE 0.034 and 0.035 m with one LiDAR versus 0.096 m for LIO-SAM; CLIO2 and CLIC2 0.034 m with two LiDARs (Table III)","On Newer College NCD06 with vigorous handheld shaking, CLIO APE 0.091 m versus 0.272 m for LIO-SAM (Table IV)","On the LVI-SAM handheld sequence, CLIC without loop closure 2.56 m versus 7.87 m for LVI-SAM, where LiDAR-only methods failed (Table V)","Time offset converges within about 3 s in most trials with final mean -2.0 ms and std 2.7 ms (Sec. VI-D)","Much faster than the earlier continuous-time CLINS (1601.86 s) on eee_01 (Table VIII)",[30,31,32],"CLIO fails on the LVI-SAM handheld sequence in open areas without the camera (Table V)","On the Vicon Room dataset LIC-Fusion 2.0 is more accurate than CLIC on four of six sequences (Table VII)","Several baseline values on NTU VIRAL are copied from the VIRAL SLAM preprint rather than re-run (Table III footnote)",[34,35,36],"one or two 3D LiDARs","IMU","monocular camera (optional)",[38,39,40,41],"MAV (NTU VIRAL)","handheld rigs (Newer College, LVI-SAM handheld, Vicon Room)","Jackal UGV (LVI-SAM dataset)","electric car (YQ)","continuous-time fixed-lag smoothing over a split cubic B-spline trajectory (knot spacing 0.03 s) with a 0.12 s LiDAR-inertial temporal window and a 10-keyframe visual window; Levenberg-Marquardt in Ceres with analytic Jacobians; marginalization keeps prior information when the window slides (Secs. III-V)","LiDAR point-to-plane factors from planar features, raw IMU factors, bias factors and visual reprojection factors with inverse depth; LiDAR points are evaluated on the continuous-time trajectory at their own timestamps (Sec. V)","continuous time (split B-spline); every LiDAR point, IMU sample and image is evaluated at its timestamp; online camera and IMU time offsets with LiDAR as the base clock (Sec. V)","implicit: LiDAR points are associated with trajectory poses at their own timestamps on the continuous-time trajectory","yes, Euclidean distance based detection with the two-stage continuous-time trajectory correction of CLINS (Sec. V)","two-stage continuous-time loop closure correction after loop detection (Sec. V)","LiDAR feature map plus visual landmarks (Fig. 10)","sensor extrinsics; time offsets and extrinsics can be calibrated online (Table V 'w\u002F calib' variant)","continuous-time trajectory and LiDAR map","desktop PC with Intel i7-7700K and 32 GB RAM; on eee_01 (397 s) total processing 217.82 s for CLIO and 294.57 s for CLIC, faster than real time (Table VIII)","https:\u002F\u002Fgithub.com\u002FAPRIL-ZJU\u002Fclic","GPL-3.0 (README)",[55,59],{"relation":56,"title":57,"doi_or_url":58},"preprint","CLIC arXiv v1","https:\u002F\u002Farxiv.org\u002Fabs\u002F2302.07456",{"relation":60,"title":61,"doi_or_url":52},"code_release","APRIL-ZJU\u002Fclic (GPL-3.0 per README)",{"id":5,"kind":63,"shortName":7,"title":8,"authors":64,"year":9,"venue":71,"venueType":72,"publisher":73,"volumeIssuePages":74,"doi":75,"arxivId":76,"url":77,"firstPublicDate":78,"publicationStatus":16,"metadataStatus":79,"fulltextStatus":15,"era":10,"classicReason":80,"codeUrl":52,"cluster":11,"topics":81,"mdpi":82,"verification":83,"label":6,"fulltextRoute":84,"versionRead":85,"addedByCensus":86},"method",[65,66,67,68,69,70],"Jiajun Lv","Xiaolei Lang","Jinhong Xu","Mengmeng Wang","Yong Liu","Xingxing Zuo","IEEE\u002FASME Transactions on Mechatronics","journal","IEEE","28(4), pp. 2259-2270","10.1109\u002Ftmech.2023.3241398","2302.07456","https:\u002F\u002Fdoi.org\u002F10.1109\u002FTMECH.2023.3241398","2023-02-15","metadata_verified","not_applicable",[11],false,"corrected","arXiv","arXiv v1 (2023-02-15) read in full; IEEE version of record (TMECH) checked through NTU access for section structure and Table III-VI images (values identical)",true,[88,95,99,102,106,110,115,121,126],{"category":89,"model":90,"canonical":90,"role":91,"dataset":92,"specs":93,"locator":94},"lidar","16-beam Ouster (two units)","method input","NTU VIRAL","10 Hz","Sec. VI-A",{"category":96,"model":97,"canonical":97,"role":91,"dataset":92,"specs":98,"locator":94},"imu","VN100","385 Hz",{"category":100,"model":101,"canonical":101,"role":91,"dataset":92,"specs":93,"locator":94},"camera","monocular cameras (two)",{"category":89,"model":103,"canonical":103,"role":91,"dataset":104,"specs":105,"locator":94},"64-beam Ouster with internal IMU","Newer College Dataset","LiDAR 10 Hz; internal IMU 100 Hz; stereo camera 30 Hz; handheld device",{"category":89,"model":107,"canonical":107,"role":91,"dataset":108,"specs":109,"locator":94},"16-beam LiDAR","LVI-SAM dataset","10 Hz; camera 20 Hz; IMU 500 Hz; handheld and Jackal platforms",{"category":89,"model":111,"canonical":111,"role":91,"dataset":112,"specs":113,"locator":114},"16-beam LiDAR (YQ and Vicon Room rig)","CLIC YQ and Vicon Room datasets (authors)","10 Hz; camera 20 Hz; IMU 400 Hz; rig mounted on an electric car (YQ) or handheld (Vicon Room)","Sec. VI-A; Fig. 6",{"category":116,"model":117,"canonical":117,"role":118,"dataset":119,"specs":120,"locator":94},"gnss","GPS (YQ ground truth)","reference or ground truth","CLIC YQ dataset (authors)","GPS measurements provide ground truth for the outdoor YQ dataset",{"category":122,"model":123,"canonical":123,"role":118,"dataset":124,"specs":125,"locator":94},"other","motion capture system","CLIC Vicon Room dataset (authors)","ground truth for the indoor Vicon Room dataset",{"category":127,"model":128,"canonical":128,"role":129,"dataset":130,"specs":131,"locator":132},"compute","desktop PC with Intel i7-7700K","compute for runtime",null,"32 GB RAM","Sec. VI-E",[],{"totalRows":135,"groupCount":136,"groups":137,"others":542},68,5,[138,351,425,489],{"slug":139,"group":140,"sourceId":5,"sourceLabel":6,"table":141,"selfRows":142,"metrics":143,"seqs":149,"entrants":169,"cells":192,"outcomes":344,"locators":345,"hardware":347,"wordings":348,"notes":349},"clic2023-table-iii","clic2023:Table III","Table III",36,[144],{"label":145,"unit":146,"statistic":147,"alignment":148},"APE (RMSE, meter)","m","RMSE","not_reported",[150,153,155,157,159,161,163,165,167],{"dataset":92,"sequence":151,"environment":152},"eee_01 (237 m)","campus indoor and outdoor MAV flights",{"dataset":92,"sequence":154,"environment":152},"eee_02 (171 m)",{"dataset":92,"sequence":156,"environment":152},"eee_03 (128 m)",{"dataset":92,"sequence":158,"environment":152},"nya_01 (160 m)",{"dataset":92,"sequence":160,"environment":152},"nya_02 (249 m)",{"dataset":92,"sequence":162,"environment":152},"nya_03 (315 m)",{"dataset":92,"sequence":164,"environment":152},"sbs_01 (202 m)",{"dataset":92,"sequence":166,"environment":152},"sbs_02 (184 m)",{"dataset":92,"sequence":168,"environment":152},"sbs_03 (199 m)",[170,173,175,177,180,182,184,186,188,190],{"name":171,"methodId":172,"linkable":86,"proposed":82,"self":82},"LIO-SAM(2) [L, I]","liosam2020",{"name":174,"methodId":130,"linkable":82,"proposed":82,"self":82},"MILIOM (horz. LiDAR)(2) [L, I]",{"name":176,"methodId":130,"linkable":82,"proposed":82,"self":82},"VIRAL (horz. LiDAR)(2) [L, I]",{"name":178,"methodId":179,"linkable":86,"proposed":82,"self":82},"CLINS (w\u002Fo loop) [L, I]","clins2021",{"name":181,"methodId":5,"linkable":86,"proposed":86,"self":86},"CLIO (w\u002Fo loop) [L, I]",{"name":183,"methodId":5,"linkable":86,"proposed":86,"self":86},"CLIC (w\u002Fo loop) [L, I, C]",{"name":185,"methodId":130,"linkable":82,"proposed":82,"self":82},"MILIOM (2 LiDARs)(2) [L2, I]",{"name":187,"methodId":130,"linkable":82,"proposed":82,"self":82},"VIRAL (2 LiDARs)(2) [L2, I, C]",{"name":189,"methodId":5,"linkable":86,"proposed":86,"self":86},"CLIO2 (w\u002Fo loop) [L2, I]",{"name":191,"methodId":5,"linkable":86,"proposed":86,"self":86},"CLIC2 (w\u002Fo loop) [L2, I, C]",[193,197,200,203,206,209,211,214,217,220,222,224,226,227,229,231,232,234,236,238,240,242,243,245,247,248,250,251,253,255,257,259,261,262,263,265,267,268,270,272,273,275,276,277,279,280,281,282,283,284,286,288,289,290,291,293,295,297,299,300,301,302,304,306,307,308,310,311,313,314,316,318,319,320,322,323,324,325,326,327,328,330,333,335,336,337,339,341,342,343],[194,194,194,195,196,194,196,196,194],0,0.075,-1,[194,194,198,199,196,194,196,196,194],1,0.069,[194,194,201,202,196,194,196,196,194],2,0.101,[194,194,204,205,196,194,196,196,194],3,0.076,[194,194,207,208,196,194,196,196,194],4,0.09,[194,194,136,210,196,194,196,196,194],0.137,[194,194,212,213,196,194,196,196,194],6,0.089,[194,194,215,216,196,194,196,196,194],7,0.083,[194,194,218,219,196,194,196,196,194],8,0.14,[198,194,194,221,196,194,196,196,194],0.104,[198,194,198,223,196,194,196,196,194],0.065,[198,194,201,225,196,194,196,196,194],0.063,[198,194,204,216,196,194,196,196,194],[198,194,207,228,196,194,196,196,194],0.072,[198,194,136,230,196,194,196,196,194],0.058,[198,194,212,205,196,194,196,196,194],[198,194,215,233,196,194,196,196,194],0.081,[198,194,218,235,196,194,196,196,194],0.088,[201,194,194,237,196,194,196,196,194],0.064,[201,194,198,239,196,194,196,196,194],0.051,[201,194,201,241,196,194,196,196,194],0.06,[201,194,204,225,196,194,196,196,194],[201,194,207,244,196,194,196,196,194],0.042,[201,194,136,246,196,194,196,196,194],0.039,[201,194,212,239,196,194,196,196,194],[201,194,215,249,196,194,196,196,194],0.056,[201,194,218,241,196,194,196,196,194],[204,194,194,252,196,194,196,196,194],0.059,[204,194,198,254,196,194,196,196,194],0.03,[204,194,201,256,196,194,196,196,194],0.029,[204,194,204,258,196,194,196,196,194],0.034,[204,194,207,260,196,194,196,196,194],0.04,[204,194,136,246,196,194,196,196,194],[204,194,212,256,196,194,196,196,194],[204,194,215,264,196,194,196,196,194],0.031,[204,194,218,266,196,194,196,196,194],0.033,[207,194,194,254,196,194,196,196,194],[207,194,198,269,196,194,196,196,194],0.023,[207,194,201,271,196,194,196,196,194],0.028,[207,194,204,244,196,194,196,196,194],[207,194,207,274,196,194,196,196,194],0.053,[207,194,136,244,196,194,196,196,194],[207,194,212,271,196,194,196,196,194],[207,194,215,278,196,194,196,196,194],0.032,[207,194,218,254,196,194,196,196,194],[136,194,194,254,196,194,196,196,194],[136,194,198,256,196,194,196,196,194],[136,194,201,271,196,194,196,196,194],[136,194,204,260,196,194,196,196,194],[136,194,207,285,196,194,196,196,194],0.054,[136,194,136,287,196,194,196,196,194],0.041,[136,194,212,256,196,194,196,196,194],[136,194,215,264,196,194,196,196,194],[136,194,218,266,196,194,196,196,194],[212,194,194,292,196,194,196,196,194],0.067,[212,194,198,294,196,194,196,196,194],0.066,[212,194,201,296,196,194,196,196,194],0.052,[212,194,204,298,196,194,196,196,194],0.057,[212,194,207,292,196,194,196,196,194],[212,194,136,244,196,194,196,196,194],[212,194,212,294,196,194,196,196,194],[212,194,215,303,196,194,196,196,194],0.082,[212,194,218,305,196,194,196,196,194],0.093,[215,194,194,241,196,194,196,196,194],[215,194,198,230,196,194,196,196,194],[215,194,201,309,196,194,196,196,194],0.037,[215,194,204,239,196,194,196,196,194],[215,194,207,312,196,194,196,196,194],0.043,[215,194,136,278,196,194,196,196,194],[215,194,212,315,196,194,196,196,194],0.048,[215,194,215,317,196,194,196,196,194],0.062,[215,194,218,285,196,194,196,196,194],[218,194,194,260,196,194,196,196,194],[218,194,198,321,196,194,196,196,194],0.021,[218,194,201,264,196,194,196,196,194],[218,194,204,254,196,194,196,196,194],[218,194,207,309,196,194,196,196,194],[218,194,136,258,196,194,196,196,194],[218,194,212,266,196,194,196,196,194],[218,194,215,309,196,194,196,196,194],[218,194,218,329,196,194,196,196,194],0.044,[331,194,194,332,196,194,196,196,194],9,0.038,[331,194,198,334,196,194,196,196,194],0.025,[331,194,201,254,196,194,196,196,194],[331,194,204,256,196,194,196,196,194],[331,194,207,338,196,194,196,196,194],0.036,[331,194,136,340,196,194,196,196,194],0.035,[331,194,212,258,196,194,196,196,194],[331,194,215,340,196,194,196,196,194],[331,194,218,312,196,194,196,196,194],[],[346],"Table III; Sec. VI",[],[],[350],"NTU VIRAL dataset (MAV, indoor and outdoor); APE RMSE in metres; sensors L = LiDAR, I = IMU, C = camera, L2 = two LiDARs; rows marked (2) are results quoted from [51] (VIRAL SLAM preprint) and their loop-closure setting is not stated; CLINS, CLIO and CLIC variants run without loop closure",{"slug":352,"group":353,"sourceId":5,"sourceLabel":6,"table":354,"selfRows":355,"metrics":356,"seqs":358,"entrants":365,"cells":383,"outcomes":417,"locators":419,"hardware":421,"wordings":422,"notes":423},"clic2023-table-v","clic2023:Table V","Table V",10,[357],{"label":145,"unit":146,"statistic":147,"alignment":148},[359,362],{"dataset":108,"sequence":360,"environment":361},"Handheld (1642 s)","outdoor open vegetated area, handheld",{"dataset":108,"sequence":363,"environment":364},"Jackal (2182 s)","outdoor open vegetated area, Jackal UGV",[366,368,369,372,373,375,377,379,381],{"name":367,"methodId":172,"linkable":86,"proposed":82,"self":82},"LIO-SAM (w\u002Fo loop) [L, I]",{"name":181,"methodId":5,"linkable":86,"proposed":86,"self":86},{"name":370,"methodId":371,"linkable":86,"proposed":82,"self":82},"LVI-SAM (w\u002Fo loop) [L, I, C]","lvisam2021",{"name":183,"methodId":5,"linkable":86,"proposed":86,"self":86},{"name":374,"methodId":172,"linkable":86,"proposed":82,"self":82},"LIO-SAM (w\u002F loop) [L, I]",{"name":376,"methodId":5,"linkable":86,"proposed":86,"self":86},"CLIO (w\u002F loop) [L, I]",{"name":378,"methodId":371,"linkable":86,"proposed":82,"self":82},"LVI-SAM (w\u002F loop) [L, I, C]",{"name":380,"methodId":5,"linkable":86,"proposed":86,"self":86},"CLIC (w\u002F loop) [L, I, C]",{"name":382,"methodId":5,"linkable":86,"proposed":86,"self":86},"CLIC (w\u002F loop, w\u002F calib) [L, I, C]",[384,386,388,389,391,393,395,397,399,400,402,403,405,407,409,411,413,415],[194,194,194,385,196,194,196,196,194],53.62,[194,194,198,387,196,194,196,196,194],3.54,[198,194,194,130,194,194,196,196,194],[198,194,198,390,196,194,196,196,194],3.43,[201,194,194,392,196,194,196,196,194],7.87,[201,194,198,394,196,194,196,196,194],4.05,[204,194,194,396,196,194,196,196,194],2.56,[204,194,198,398,196,194,196,196,194],2.55,[207,194,194,130,194,194,196,196,194],[207,194,198,401,196,194,196,196,194],1.52,[136,194,194,130,194,194,196,196,194],[136,194,198,404,196,194,196,196,194],1.01,[212,194,194,406,196,194,196,196,194],0.83,[212,194,198,408,196,194,196,196,194],0.67,[215,194,194,410,196,194,196,196,194],0.65,[215,194,198,412,196,194,196,196,194],0.88,[218,194,194,414,196,194,196,196,194],0.56,[218,194,198,416,196,194,196,196,194],0.84,[418],"failure ('fail' in Table V)",[420],"Table V; Sec. VI-C",[],[],[424],"LVI-SAM dataset (handheld and Jackal, outdoor open vegetated and geometrically degenerate areas; 16-beam LiDAR 10 Hz, camera 20 Hz, IMU 500 Hz); APE RMSE in metres",{"slug":426,"group":427,"sourceId":5,"sourceLabel":6,"table":428,"selfRows":355,"metrics":429,"seqs":441,"entrants":445,"cells":451,"outcomes":481,"locators":482,"hardware":484,"wordings":486,"notes":487},"clic2023-table-viii","clic2023:Table VIII","Table VIII",[430,433,435,437,439],{"label":431,"unit":432,"statistic":80,"alignment":80},"Update Local Map time over the sequence","s",{"label":434,"unit":432,"statistic":80,"alignment":80},"Update Trajectory time over the sequence",{"label":436,"unit":432,"statistic":80,"alignment":80},"Update Prior time over the sequence",{"label":438,"unit":432,"statistic":80,"alignment":80},"Others time over the sequence",{"label":440,"unit":432,"statistic":80,"alignment":80},"Total time over the sequence",[442],{"dataset":92,"sequence":443,"environment":444},"eee_01 (397 s)","campus MAV flight",[446,448,450],{"name":447,"methodId":179,"linkable":86,"proposed":82,"self":82},"CLINS",{"name":449,"methodId":5,"linkable":86,"proposed":86,"self":86},"CLIO",{"name":7,"methodId":5,"linkable":86,"proposed":86,"self":86},[452,454,456,458,460,462,464,465,467,469,471,473,475,477,479],[194,194,194,453,196,194,194,196,194],17.39,[198,194,194,455,196,194,194,196,194],11.56,[201,194,194,457,196,194,194,196,194],11.52,[194,198,194,459,196,194,194,196,194],1184.34,[198,198,194,461,196,194,194,196,194],58.55,[201,198,194,463,196,194,194,196,194],80.64,[194,201,194,194,196,194,194,196,194],[198,201,194,466,196,194,194,196,194],8.45,[201,201,194,468,196,194,194,196,194],8.44,[194,204,194,470,196,194,194,196,194],400.13,[198,204,194,472,196,194,194,196,194],139.27,[201,204,194,474,196,194,194,196,194],193.97,[194,207,194,476,196,194,194,196,194],1601.86,[198,207,194,478,196,194,194,196,194],217.82,[201,207,194,480,196,194,194,196,194],294.57,[],[483],"Table VIII; Sec. VI-E",[485],"desktop PC, Intel i7-7700K, 32 GB RAM",[],[488],"Time consumption (seconds) of main modules over the whole eee_01 sequence (397 s) of NTU VIRAL on an Intel i7-7700K desktop with 32 GB RAM",{"slug":490,"group":491,"sourceId":5,"sourceLabel":6,"table":492,"selfRows":212,"metrics":493,"seqs":495,"entrants":503,"cells":512,"outcomes":535,"locators":536,"hardware":538,"wordings":539,"notes":540},"clic2023-table-iv","clic2023:Table IV","Table IV",[494],{"label":145,"unit":146,"statistic":147,"alignment":148},[496,499,501],{"dataset":104,"sequence":497,"environment":498},"NCD_01 (1530 s \u002F 1609 m)","college campus, handheld",{"dataset":104,"sequence":500,"environment":498},"NCD_02 (2656 s \u002F 3063 m)",{"dataset":104,"sequence":502,"environment":498},"NCD_06 (120 s \u002F 97 m)",[504,506,508,510],{"name":505,"methodId":172,"linkable":86,"proposed":82,"self":82},"LIO-SAM (w\u002Fo loop)",{"name":507,"methodId":5,"linkable":86,"proposed":86,"self":86},"CLIO (w\u002Fo loop)",{"name":509,"methodId":172,"linkable":86,"proposed":82,"self":82},"LIO-SAM (w\u002F loop)",{"name":511,"methodId":5,"linkable":86,"proposed":86,"self":86},"CLIO (w\u002F loop)",[513,515,517,519,521,523,525,527,529,530,532,534],[194,194,194,514,196,194,196,196,194],1.66,[194,194,198,516,196,194,196,196,194],2.305,[194,194,201,518,196,194,196,196,194],0.272,[198,194,194,520,196,194,196,196,194],0.792,[198,194,198,522,196,194,196,196,194],2.686,[198,194,201,524,196,194,196,196,194],0.091,[201,194,194,526,196,194,196,196,194],0.544,[201,194,198,528,196,194,196,196,194],0.592,[201,194,201,518,196,194,196,196,194],[204,194,194,531,196,194,196,196,194],0.408,[204,194,198,533,196,194,196,196,194],0.381,[204,194,201,524,196,194,196,196,194],[],[537],"Table IV; Sec. VI-B",[],[],[541],"Newer College Dataset (handheld, 64-beam Ouster with internal IMU); APE RMSE in metres; LiDAR-IMU methods only",[543],{"group":544,"slug":545,"sourceLabel":6,"table":546,"selfRows":212,"datasets":547},"clic2023:Table VII","clic2023-table-vii","Table VII",[124],1790510657642]