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BPMN_Detection

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1
  ---
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  license: apache-2.0
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- metrics:
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- - precision
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- - recall
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- - f1
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- - accuracy
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-
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  # BPMN element detection
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@@ -60,10 +54,6 @@ It achieves the following results on the evaluation set with arrows:
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  | Class | Precision | Recall | F1 |
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  |:-----------------:|:---------:|:--------:|:-------:|
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- | background | 0 | 0 | 0 |
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- | sequenceFlow | 0.9292 | 0.9605 | 0.9446 |
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- | dataAssociation | 0.8472 | 0.8095 | 0.8279 |
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- | messageFlow | 0.8589 | 0.7910 | 0.8235 |
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  | task | 0.9518 | 0.9875 | 0.9693 |
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  | exclusiveGateway | 0.9548 | 0.9427 | 0.9487 |
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  | event | 0.9515 | 0.9235 | 0.9373 |
@@ -73,9 +63,11 @@ It achieves the following results on the evaluation set with arrows:
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  | lane | 0.9178 | 0.67 | 0.7746 |
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  | dataObject | 0.9333 | 0.9565 | 0.9448 |
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  | dataStore | 1.0 | 0.64 | 0.7805 |
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- | subProcess | 1.0 | 0.1429 | 0.25 |
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  | eventBasedGateway | 0.7273 | 0.7273 | 0.7273 |
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  | timerEvent | 0.8571 | 0.75 | 0.8 |
 
 
 
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  ## Model description
@@ -103,57 +95,57 @@ The following hyperparameters were used during training:
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  - lr_scheduler_type: linear
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  - num_epochs: 50
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- ### Training results
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-
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- | Epoch | Avg Loss | Classifier Loss | Box Reg Loss | Objectness Loss | RPN Box Reg Loss | Keypoints Loss | Precision | Recall | F1 Score | Accuracy |
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- |:-----:|:--------:|:---------------:|:------------:|:---------------:|:----------------:|:--------------:|:---------:|:------:|:--------:|:--------:|
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- | 1 | 3.9451 | 2.4416 | 0.5426 | 0.6502 | 0.3107 | 0.0 | 0.2763 | 0.0393 | 0.0689 | 2.0591 |
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- | 2 | 2.7259 | 1.6724 | 0.6697 | 0.1868 | 0.1969 | 0.0 | 0.5754 | 0.3358 | 0.4241 | 1.5387 |
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- | 3 | 2.2004 | 1.3860 | 0.5330 | 0.1216 | 0.1598 | 0.0 | 0.8657 | 0.6841 | 0.7643 | 1.1307 |
113
- | 4 | 1.8611 | 1.1775 | 0.4172 | 0.1099 | 0.1565 | 0.0 | 0.7708 | 0.7790 | 0.7749 | 1.0110 |
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- | 5 | 1.7461 | 1.1202 | 0.3820 | 0.0971 | 0.1468 | 0.0 | 0.8542 | 0.8046 | 0.8287 | 0.9593 |
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- | 6 | 1.5859 | 0.9986 | 0.3590 | 0.0872 | 0.1412 | 0.0 | 0.8884 | 0.8002 | 0.8420 | 0.8956 |
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- | 7 | 1.5621 | 1.0214 | 0.3351 | 0.0776 | 0.1280 | 0.0 | 0.9435 | 0.8034 | 0.8678 | 0.9073 |
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- | 8 | 1.5194 | 0.9881 | 0.3261 | 0.0738 | 0.1314 | 0.0 | 0.9048 | 0.8246 | 0.8628 | 0.8695 |
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- | 9 | 1.5449 | 1.0105 | 0.3229 | 0.0769 | 0.1346 | 0.0 | 0.9478 | 0.8046 | 0.8704 | 0.9014 |
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- | 10 | 1.5805 | 1.0333 | 0.3338 | 0.0703 | 0.1431 | 0.0 | 0.8920 | 0.8920 | 0.8920 | 0.8134 |
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- | 11 | 1.3838 | 0.8743 | 0.3065 | 0.0653 | 0.1376 | 0.0 | 0.9634 | 0.8371 | 0.8958 | 0.8097 |
121
- | 12 | 1.3582 | 0.8751 | 0.2909 | 0.0617 | 0.1306 | 0.0 | 0.9457 | 0.8596 | 0.9006 | 0.7362 |
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- | 13 | 1.3126 | 0.8347 | 0.2921 | 0.0593 | 0.1264 | 0.0 | 0.9152 | 0.9295 | 0.9223 | 0.7149 |
123
- | 14 | 1.3532 | 0.9079 | 0.2783 | 0.0543 | 0.1128 | 0.0 | 0.9639 | 0.8508 | 0.9038 | 0.7775 |
124
- | 15 | 1.3188 | 0.8986 | 0.2720 | 0.0434 | 0.1048 | 0.0 | 0.8856 | 0.9419 | 0.9129 | 0.6738 |
125
- | 16 | 1.2512 | 0.7840 | 0.2784 | 0.0621 | 0.1268 | 0.0 | 0.9181 | 0.9101 | 0.9141 | 0.7478 |
126
- | 17 | 1.2909 | 0.8425 | 0.2778 | 0.0547 | 0.1159 | 0.0 | 0.9012 | 0.9282 | 0.9145 | 0.6556 |
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- | 18 | 1.2526 | 0.8442 | 0.2607 | 0.0443 | 0.1034 | 0.0 | 0.9169 | 0.9020 | 0.9094 | 0.7003 |
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- | 19 | 1.1980 | 0.8062 | 0.2528 | 0.0361 | 0.1029 | 0.0 | 0.9520 | 0.9157 | 0.9335 | 0.7136 |
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- | 20 | 1.1821 | 0.7895 | 0.2517 | 0.0378 | 0.1030 | 0.0 | 0.9023 | 0.9513 | 0.9262 | 0.6308 |
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- | 21 | 1.0843 | 0.7168 | 0.2402 | 0.0316 | 0.0957 | 0.0 | 0.9348 | 0.9032 | 0.9187 | 0.6883 |
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- | 22 | 1.1058 | 0.7367 | 0.2336 | 0.0374 | 0.0981 | 0.0 | 0.9321 | 0.9513 | 0.9416 | 0.6192 |
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- | 23 | 1.0699 | 0.7119 | 0.2340 | 0.0306 | 0.0935 | 0.0 | 0.9353 | 0.9476 | 0.9414 | 0.5962 |
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- | 24 | 1.0616 | 0.7031 | 0.2367 | 0.0311 | 0.0908 | 0.0 | 0.9418 | 0.9301 | 0.9359 | 0.6674 |
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- | 25 | 1.0784 | 0.7275 | 0.2311 | 0.0295 | 0.0904 | 0.0 | 0.9176 | 0.9320 | 0.9247 | 0.6158 |
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- | 26 | 1.0618 | 0.7121 | 0.2283 | 0.0297 | 0.0916 | 0.0 | 0.9411 | 0.9182 | 0.9295 | 0.6483 |
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- | 27 | 1.0530 | 0.7139 | 0.2236 | 0.0279 | 0.0876 | 0.0 | 0.9477 | 0.9395 | 0.9436 | 0.5958 |
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- | 28 | 1.0452 | 0.7097 | 0.2223 | 0.0283 | 0.0849 | 0.0 | 0.9465 | 0.9494 | 0.9480 | 0.5964 |
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- | 29 | 1.0966 | 0.7795 | 0.2176 | 0.0203 | 0.0792 | 0.0 | 0.9558 | 0.9320 | 0.9437 | 0.6288 |
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- | 30 | 1.0506 | 0.7312 | 0.2142 | 0.0195 | 0.0856 | 0.0 | 0.9370 | 0.9370 | 0.9370 | 0.5956 |
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- | 31 | 1.0030 | 0.6777 | 0.2163 | 0.0204 | 0.0886 | 0.0 | 0.9506 | 0.9251 | 0.9377 | 0.6099 |
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- | 32 | 0.9748 | 0.6610 | 0.2098 | 0.0201 | 0.0839 | 0.0 | 0.9527 | 0.9313 | 0.9419 | 0.5976 |
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- | 33 | 0.9540 | 0.6402 | 0.2059 | 0.0216 | 0.0863 | 0.0 | 0.9536 | 0.9238 | 0.9385 | 0.5907 |
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- | 34 | 0.9730 | 0.6500 | 0.2076 | 0.0281 | 0.0873 | 0.0 | 0.9407 | 0.9413 | 0.9410 | 0.5809 |
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- | 35 | 0.9894 | 0.6831 | 0.2066 | 0.0202 | 0.0794 | 0.0 | 0.9451 | 0.9345 | 0.9397 | 0.5837 |
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- | 36 | 0.9042 | 0.5873 | 0.2096 | 0.0214 | 0.0860 | 0.0 | 0.9460 | 0.9519 | 0.9490 | 0.5534 |
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- | 37 | 0.9546 | 0.6400 | 0.2112 | 0.0216 | 0.0818 | 0.0 | 0.9260 | 0.9457 | 0.9358 | 0.5562 |
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- | 38 | 0.9806 | 0.6800 | 0.2031 | 0.0175 | 0.0800 | 0.0 | 0.9476 | 0.9363 | 0.9419 | 0.5792 |
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- | 39 | 0.9294 | 0.6247 | 0.2016 | 0.0204 | 0.0826 | 0.0 | 0.9401 | 0.9501 | 0.9450 | 0.5703 |
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- | 40 | 0.9786 | 0.6733 | 0.2010 | 0.0268 | 0.0775 | 0.0 | 0.9375 | 0.9170 | 0.9271 | 0.5880 |
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- | 41 | 1.0026 | 0.7073 | 0.2033 | 0.0179 | 0.0742 | 0.0 | 0.9476 | 0.9251 | 0.9362 | 0.5875 |
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- | 42 | 0.9567 | 0.6677 | 0.1992 | 0.0164 | 0.0734 | 0.0 | 0.9468 | 0.9332 | 0.9400 | 0.5724 |
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- | 43 | 0.8747 | 0.5794 | 0.1980 | 0.0159 | 0.0814 | 0.0 | 0.9557 | 0.9432 | 0.9494 | 0.5709 |
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- | 44 | 1.0310 | 0.7392 | 0.1956 | 0.0254 | 0.0709 | 0.0 | 0.9589 | 0.9313 | 0.9449 | 0.5497 |
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- | 45 | 0.9526 | 0.6598 | 0.1982 | 0.0185 | 0.0762 | 0.0 | 0.9401 | 0.9413 | 0.9407 | 0.5580 |
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- | 46 | 0.8753 | 0.5940 | 0.1939 | 0.0176 | 0.0698 | 0.0 | 0.9468 | 0.9438 | 0.9453 | 0.5548 |
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- | 47 | 0.9328 | 0.6493 | 0.1953 | 0.0163 | 0.0720 | 0.0 | 0.9534 | 0.9320 | 0.9426 | 0.5735 |
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- | 48 | 0.9019 | 0.6071 | 0.2002 | 0.0182 | 0.0765 | 0.0 | 0.9496 | 0.9413 | 0.9455 | 0.5605 |
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- | 49 | 0.8335 | 0.5459 | 0.1918 | 0.0175 | 0.0783 | 0.0 | 0.9588 | 0.9307 | 0.9446 | 0.5637 |
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- | 50 | 0.9043 | 0.6179 | 0.1933 | 0.0154 | 0.0776 | 0.0 | 0.9597 | 0.9370 | 0.9482 | 0.5617 |
 
1
  ---
2
  license: apache-2.0
 
 
 
 
 
 
3
 
4
  # BPMN element detection
5
 
 
54
 
55
  | Class | Precision | Recall | F1 |
56
  |:-----------------:|:---------:|:--------:|:-------:|
 
 
 
 
57
  | task | 0.9518 | 0.9875 | 0.9693 |
58
  | exclusiveGateway | 0.9548 | 0.9427 | 0.9487 |
59
  | event | 0.9515 | 0.9235 | 0.9373 |
 
63
  | lane | 0.9178 | 0.67 | 0.7746 |
64
  | dataObject | 0.9333 | 0.9565 | 0.9448 |
65
  | dataStore | 1.0 | 0.64 | 0.7805 |
 
66
  | eventBasedGateway | 0.7273 | 0.7273 | 0.7273 |
67
  | timerEvent | 0.8571 | 0.75 | 0.8 |
68
+ | sequenceFlow | 0.9292 | 0.9605 | 0.9446 |
69
+ | dataAssociation | 0.8472 | 0.8095 | 0.8279 |
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+ | messageFlow | 0.8589 | 0.7910 | 0.8235 |
71
 
72
 
73
  ## Model description
 
95
  - lr_scheduler_type: linear
96
  - num_epochs: 50
97
 
98
+ ### Example of Training results
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+ | Epoch | Avg Loss | Test Loss | Classifier Loss | Box Reg Loss | Objectness Loss | RPN Box Reg Loss | Precision | Recall | F1 Score |
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+ |:-----:|:--------:|:---------:|:---------------:|:------------:|:---------------:|:----------------:|:---------:|:------:|:--------:|
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+ | 1 | 3.9451 | 2.0591 | 2.4416 | 0.5426 | 0.6502 | 0.3107 | 0.2763 | 0.0393 | 0.0689 |
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+ | 2 | 2.7259 | 1.5387 | 1.6724 | 0.6697 | 0.1868 | 0.1969 | 0.5754 | 0.3358 | 0.4241 |
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+ | 3 | 2.2004 | 1.1307 | 1.3860 | 0.5330 | 0.1216 | 0.1598 | 0.8657 | 0.6841 | 0.7643 |
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+ | 4 | 1.8611 | 1.0110 | 1.1775 | 0.4172 | 0.1099 | 0.1565 | 0.7708 | 0.7790 | 0.7749 |
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+ | 5 | 1.7461 | 0.9593 | 1.1202 | 0.3820 | 0.0971 | 0.1468 | 0.8542 | 0.8046 | 0.8287 |
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+ | 6 | 1.5859 | 0.8956 | 0.9986 | 0.3590 | 0.0872 | 0.1412 | 0.8884 | 0.8002 | 0.8420 |
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+ | 7 | 1.5621 | 0.9073 | 1.0214 | 0.3351 | 0.0776 | 0.1280 | 0.9435 | 0.8034 | 0.8678 |
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+ | 8 | 1.5194 | 0.8695 | 0.9881 | 0.3261 | 0.0738 | 0.1314 | 0.9048 | 0.8246 | 0.8628 |
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+ | 9 | 1.5449 | 0.9014 | 1.0105 | 0.3229 | 0.0769 | 0.1346 | 0.9478 | 0.8046 | 0.8704 |
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+ | 10 | 1.5805 | 0.8134 | 1.0333 | 0.3338 | 0.0703 | 0.1431 | 0.8920 | 0.8920 | 0.8920 |
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+ | 11 | 1.3838 | 0.8097 | 0.8743 | 0.3065 | 0.0653 | 0.1376 | 0.9634 | 0.8371 | 0.8958 |
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+ | 12 | 1.3582 | 0.7362 | 0.8751 | 0.2909 | 0.0617 | 0.1306 | 0.9457 | 0.8596 | 0.9006 |
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+ | 13 | 1.3126 | 0.7149 | 0.8347 | 0.2921 | 0.0593 | 0.1264 | 0.9152 | 0.9295 | 0.9223 |
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+ | 14 | 1.3532 | 0.7775 | 0.9079 | 0.2783 | 0.0543 | 0.1128 | 0.9639 | 0.8508 | 0.9038 |
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+ | 15 | 1.3188 | 0.6738 | 0.8986 | 0.2720 | 0.0434 | 0.1048 | 0.8856 | 0.9419 | 0.9129 |
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+ | 16 | 1.2512 | 0.7478 | 0.7840 | 0.2784 | 0.0621 | 0.1268 | 0.9181 | 0.9101 | 0.9141 |
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+ | 17 | 1.2909 | 0.6556 | 0.8425 | 0.2778 | 0.0547 | 0.1159 | 0.9012 | 0.9282 | 0.9145 |
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+ | 18 | 1.2526 | 0.7003 | 0.8442 | 0.2607 | 0.0443 | 0.1034 | 0.9169 | 0.9020 | 0.9094 |
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+ | 19 | 1.1980 | 0.7136 | 0.8062 | 0.2528 | 0.0361 | 0.1029 | 0.9520 | 0.9157 | 0.9335 |
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+ | 20 | 1.1821 | 0.6308 | 0.7895 | 0.2517 | 0.0378 | 0.1030 | 0.9023 | 0.9513 | 0.9262 |
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+ | 21 | 1.0843 | 0.6883 | 0.7168 | 0.2402 | 0.0316 | 0.0957 | 0.9348 | 0.9032 | 0.9187 |
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+ | 22 | 1.1058 | 0.6192 | 0.7367 | 0.2336 | 0.0374 | 0.0981 | 0.9321 | 0.9513 | 0.9416 |
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+ | 23 | 1.0699 | 0.5962 | 0.7119 | 0.2340 | 0.0306 | 0.0935 | 0.9353 | 0.9476 | 0.9414 |
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+ | 24 | 1.0616 | 0.6674 | 0.7031 | 0.2367 | 0.0311 | 0.0908 | 0.9418 | 0.9301 | 0.9359 |
125
+ | 25 | 1.0784 | 0.6158 | 0.7275 | 0.2311 | 0.0295 | 0.0904 | 0.9176 | 0.9320 | 0.9247 |
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+ | 26 | 1.0618 | 0.6483 | 0.7121 | 0.2283 | 0.0297 | 0.0916 | 0.9411 | 0.9182 | 0.9295 |
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+ | 27 | 1.0530 | 0.5958 | 0.7139 | 0.2236 | 0.0279 | 0.0876 | 0.9477 | 0.9395 | 0.9436 |
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+ | 28 | 1.0452 | 0.5964 | 0.7097 | 0.2223 | 0.0283 | 0.0849 | 0.9465 | 0.9494 | 0.9480 |
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+ | 29 | 1.0966 | 0.6288 | 0.7795 | 0.2176 | 0.0203 | 0.0792 | 0.9558 | 0.9320 | 0.9437 |
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+ | 30 | 1.0506 | 0.5956 | 0.7312 | 0.2142 | 0.0195 | 0.0856 | 0.9370 | 0.9370 | 0.9370 |
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+ | 31 | 1.0030 | 0.6099 | 0.6777 | 0.2163 | 0.0204 | 0.0886 | 0.9506 | 0.9251 | 0.9377 |
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+ | 32 | 0.9748 | 0.5976 | 0.6610 | 0.2098 | 0.0201 | 0.0839 | 0.9527 | 0.9313 | 0.9419 |
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+ | 33 | 0.9540 | 0.5907 | 0.6402 | 0.2059 | 0.0216 | 0.0863 | 0.9536 | 0.9238 | 0.9385 |
134
+ | 34 | 0.9730 | 0.5809 | 0.6500 | 0.2076 | 0.0281 | 0.0873 | 0.9407 | 0.9413 | 0.9410 |
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+ | 35 | 0.9894 | 0.5837 | 0.6831 | 0.2066 | 0.0202 | 0.0794 | 0.9451 | 0.9345 | 0.9397 |
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+ | 36 | 0.9042 | 0.5534 | 0.5873 | 0.2096 | 0.0214 | 0.0860 | 0.9460 | 0.9519 | 0.9490 |
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+ | 37 | 0.9546 | 0.5562 | 0.6400 | 0.2112 | 0.0216 | 0.0818 | 0.9260 | 0.9457 | 0.9358 |
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+ | 38 | 0.9806 | 0.5792 | 0.6800 | 0.2031 | 0.0175 | 0.0800 | 0.9476 | 0.9363 | 0.9419 |
139
+ | 39 | 0.9294 | 0.5703 | 0.6247 | 0.2016 | 0.0204 | 0.0826 | 0.9401 | 0.9501 | 0.9450 |
140
+ | 40 | 0.9786 | 0.5880 | 0.6733 | 0.2010 | 0.0268 | 0.0775 | 0.9375 | 0.9170 | 0.9271 |
141
+ | 41 | 1.0026 | 0.5875 | 0.7073 | 0.2033 | 0.0179 | 0.0742 | 0.9476 | 0.9251 | 0.9362 |
142
+ | 42 | 0.9567 | 0.5724 | 0.6677 | 0.1992 | 0.0164 | 0.0734 | 0.9468 | 0.9332 | 0.9400 |
143
+ | 43 | 0.8747 | 0.5709 | 0.5794 | 0.1980 | 0.0159 | 0.0814 | 0.9557 | 0.9432 | 0.9494 |
144
+ | 44 | 1.0310 | 0.5497 | 0.7392 | 0.1956 | 0.0254 | 0.0709 | 0.9589 | 0.9313 | 0.9449 |
145
+ | 45 | 0.9526 | 0.5580 | 0.6598 | 0.1982 | 0.0185 | 0.0762 | 0.9401 | 0.9413 | 0.9407 |
146
+ | 46 | 0.8753 | 0.5548 | 0.5940 | 0.1939 | 0.0176 | 0.0698 | 0.9468 | 0.9438 | 0.9453 |
147
+ | 47 | 0.9328 | 0.5735 | 0.6493 | 0.1953 | 0.0163 | 0.0720 | 0.9534 | 0.9320 | 0.9426 |
148
+ | 48 | 0.9019 | 0.5605 | 0.6071 | 0.2002 | 0.0182 | 0.0765 | 0.9496 | 0.9413 | 0.9455 |
149
+ | 49 | 0.8335 | 0.5637 | 0.5459 | 0.1918 | 0.0175 | 0.0783 | 0.9588 | 0.9307 | 0.9446 |
150
+ | 50 | 0.9043 | 0.5617 | 0.6179 | 0.1933 | 0.0154 | 0.0776 | 0.9597 | 0.9370 | 0.9482 |
151
+