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1
+ # UCI Adult Data Analysis model using Tensorflow
2
+
3
+ **Version:** 0.1
4
+
5
+ **Short Description:** UCI Adult Data analysis using Tensorflow for demonstration of Patra Model Cards.
6
+
7
+ **Full Description:** We have trained a ML model using the tensorflow framework to predict income for the UCI Adult Dataset. We leverage this data to run the Patra model cards to capture metadata about the model as well as fairness and explainability metrics.
8
+
9
+ **Keywords:** uci adult, tensorflow, explainability, fairness, patra
10
+
11
+ **Author:** Your Name
12
+
13
+ **Input Type:** Tabular
14
+
15
+ **Category:** classification
16
+
17
+ **Foundational Model:** None
18
+
19
+ **Input Data:** https://archive.ics.uci.edu/ml/datasets/adult
20
+
21
+ **Output Data:** https://github.iu.edu/d2i/dockerhub/tensorflow/adult_modelv01
22
+
23
+ ## AI Model
24
+
25
+ **Name:** Income prediction tensorflow model
26
+
27
+ **Version:** 0.1
28
+
29
+ **Description:** Census classification problem using TensorFlow Neural Network using the UCI Adult Dataset
30
+
31
+ **Owner:** Your Name or Organization
32
+
33
+ **Location:** https://example.com/path-to-model
34
+
35
+ **License:** BSD-3 Clause
36
+
37
+ **Framework:** tensorflow
38
+
39
+ **Model Type:** dnn
40
+
41
+ **Test Accuracy:** 0.7919545769691467
42
+
43
+ ### Model Structure
44
+
45
+ ```json
46
+ {
47
+ "module": "keras",
48
+ "class_name": "Sequential",
49
+ "config": {
50
+ "name": "sequential",
51
+ "trainable": true,
52
+ "dtype": {
53
+ "module": "keras",
54
+ "class_name": "DTypePolicy",
55
+ "config": {
56
+ "name": "float32"
57
+ }
58
+ },
59
+ "layers": [
60
+ {
61
+ "module": "keras.layers",
62
+ "class_name": "InputLayer",
63
+ "config": {
64
+ "batch_shape": [
65
+ 100
66
+ ],
67
+ "dtype": "float32",
68
+ "sparse": false,
69
+ "name": "input_layer"
70
+ }
71
+ },
72
+ {
73
+ "module": "keras.layers",
74
+ "class_name": "Dense",
75
+ "config": {
76
+ "name": "dense",
77
+ "trainable": true,
78
+ "dtype": {
79
+ "module": "keras",
80
+ "class_name": "DTypePolicy",
81
+ "config": {
82
+ "name": "float32"
83
+ }
84
+ },
85
+ "units": 64,
86
+ "activation": "relu",
87
+ "use_bias": true,
88
+ "kernel_initializer": {
89
+ "module": "keras.initializers",
90
+ "class_name": "GlorotUniform",
91
+ "config": {}
92
+ },
93
+ "bias_initializer": {
94
+ "module": "keras.initializers",
95
+ "class_name": "Zeros",
96
+ "config": {}
97
+ }
98
+ },
99
+ "build_config": {
100
+ "input_shape": [
101
+ 100
102
+ ]
103
+ }
104
+ },
105
+ {
106
+ "module": "keras.layers",
107
+ "class_name": "Dense",
108
+ "config": {
109
+ "name": "dense_1",
110
+ "trainable": true,
111
+ "dtype": {
112
+ "module": "keras",
113
+ "class_name": "DTypePolicy",
114
+ "config": {
115
+ "name": "float32"
116
+ }
117
+ },
118
+ "units": 128,
119
+ "activation": "relu",
120
+ "use_bias": true,
121
+ "kernel_initializer": {
122
+ "module": "keras.initializers",
123
+ "class_name": "GlorotUniform",
124
+ "config": {}
125
+ },
126
+ "bias_initializer": {
127
+ "module": "keras.initializers",
128
+ "class_name": "Zeros",
129
+ "config": {}
130
+ }
131
+ },
132
+ "build_config": {
133
+ "input_shape": [
134
+ 64
135
+ ]
136
+ }
137
+ },
138
+ {
139
+ "module": "keras.layers",
140
+ "class_name": "Dense",
141
+ "config": {
142
+ "name": "dense_2",
143
+ "trainable": true,
144
+ "dtype": {
145
+ "module": "keras",
146
+ "class_name": "DTypePolicy",
147
+ "config": {
148
+ "name": "float32"
149
+ }
150
+ },
151
+ "units": 64,
152
+ "activation": "relu",
153
+ "use_bias": true,
154
+ "kernel_initializer": {
155
+ "module": "keras.initializers",
156
+ "class_name": "GlorotUniform",
157
+ "config": {}
158
+ },
159
+ "bias_initializer": {
160
+ "module": "keras.initializers",
161
+ "class_name": "Zeros",
162
+ "config": {}
163
+ }
164
+ },
165
+ "build_config": {
166
+ "input_shape": [
167
+ 128
168
+ ]
169
+ }
170
+ },
171
+ {
172
+ "module": "keras.layers",
173
+ "class_name": "Dense",
174
+ "config": {
175
+ "name": "dense_3",
176
+ "trainable": true,
177
+ "dtype": {
178
+ "module": "keras",
179
+ "class_name": "DTypePolicy",
180
+ "config": {
181
+ "name": "float32"
182
+ }
183
+ },
184
+ "units": 1,
185
+ "activation": "sigmoid",
186
+ "use_bias": true,
187
+ "kernel_initializer": {
188
+ "module": "keras.initializers",
189
+ "class_name": "GlorotUniform",
190
+ "config": {}
191
+ },
192
+ "bias_initializer": {
193
+ "module": "keras.initializers",
194
+ "class_name": "Zeros",
195
+ "config": {}
196
+ }
197
+ },
198
+ "build_config": {
199
+ "input_shape": [
200
+ 64
201
+ ]
202
+ }
203
+ }
204
+ ],
205
+ "build_input_shape": [
206
+ 100
207
+ ]
208
+ },
209
+ "build_config": {
210
+ "input_shape": [
211
+ 100
212
+ ]
213
+ },
214
+ "compile_config": {
215
+ "optimizer": {
216
+ "module": "keras.optimizers",
217
+ "class_name": "Adam",
218
+ "config": {
219
+ "name": "adam",
220
+ "learning_rate": 0.0010000000474974513,
221
+ "use_ema": false,
222
+ "ema_momentum": 0.99,
223
+ "beta_1": 0.9,
224
+ "beta_2": 0.999,
225
+ "epsilon": 1e-07,
226
+ "amsgrad": false
227
+ }
228
+ },
229
+ "loss": "binary_crossentropy",
230
+ "metrics": [
231
+ "accuracy"
232
+ ],
233
+ "run_eagerly": false,
234
+ "steps_per_execution": 1,
235
+ "jit_compile": false
236
+ }
237
+ }
238
+ ```
239
+
240
+ ### Metrics
241
+
242
+ - **Test loss:** 0.5084354877471924
243
+ - **Epochs:** 100
244
+ - **Batch Size:** 32
245
+ - **Optimizer:** Adam
246
+ - **Learning Rate:** 0.001
247
+ - **Input Shape:** (26048, 100)
248
+
249
+ ## Bias Analysis
250
+
251
+ - **demographic_parity_diff:** 0.032400848225782965
252
+ - **equal_odds_difference:** 0.03417438108252019
253
+
254
+ ## Explainability Analysis
255
+
256
+ - **capital_gain:** 0.14158532669974697
257
+ - **fnlwgt:** 0.015681726452377108
258
+ - **age:** 0.00021690960559580313
259
+ - **hours_per_week:** 0.00013091093136204657
260
+ - **relationship__Not_in_family:** 7.917947239345974e-05
261
+ - **marital_status__Married_civ_spouse:** 7.522924906677672e-05
262
+ - **education__HS_grad:** 5.9253134661254366e-05
263
+ - **occupation__Exec_managerial:** 5.8465765582191924e-05
264
+ - **marital_status__Never_married:** 2.9966458678243015e-05
265
+ - **education_num:** 2.848242719968154e-05
266
+
267
+ ## Model Requirements
268
+
269
+ - absl-py==1.4.0
270
+ - accelerate==1.2.1
271
+ - aiohappyeyeballs==2.4.4
272
+ - aiohttp==3.11.11
273
+ - aiosignal==1.3.2
274
+ - alabaster==1.0.0
275
+ - albucore==0.0.19
276
+ - albumentations==1.4.20
277
+ - ale-py==0.10.1
278
+ - altair==5.5.0
279
+ - annotated-types==0.7.0
280
+ - anyio==3.7.1
281
+ - argon2-cffi-bindings==21.2.0
282
+ - argon2-cffi==23.1.0
283
+ - array-record==0.6.0
284
+ - arviz==0.20.0
285
+ - astropy-iers-data==0.2025.1.27.0.32.44
286
+ - astropy==6.1.7
287
+ - astunparse==1.6.3
288
+ - atpublic==4.1.0
289
+ - attrs==25.1.0
290
+ - audioread==3.0.1
291
+ - autocommand==2.2.2
292
+ - autograd==1.7.0
293
+ - babel==2.16.0
294
+ - backcall==0.2.0
295
+ - backports.tarfile==1.2.0
296
+ - beautifulsoup4==4.12.3
297
+ - bigframes==1.33.0
298
+ - bigquery-magics==0.5.0
299
+ - bleach==6.2.0
300
+ - blinker==1.9.0
301
+ - blis==0.7.11
302
+ - blosc2==3.0.0
303
+ - bokeh==3.6.2
304
+ - bottleneck==1.4.2
305
+ - bqplot==0.12.44
306
+ - branca==0.8.1
307
+ - cachecontrol==0.14.2
308
+ - cachetools==5.5.1
309
+ - catalogue==2.0.10
310
+ - certifi==2024.12.14
311
+ - cffi==1.17.1
312
+ - chardet==5.2.0
313
+ - charset-normalizer==3.4.1
314
+ - chex==0.1.88
315
+ - clarabel==0.9.0
316
+ - click==8.1.8
317
+ - cloudpathlib==0.20.0
318
+ - cloudpickle==3.1.1
319
+ - cmake==3.31.4
320
+ - cmdstanpy==1.2.5
321
+ - colorcet==3.1.0
322
+ - colorlover==0.3.0
323
+ - colour==0.1.5
324
+ - community==1.0.0b1
325
+ - confection==0.1.5
326
+ - cons==0.4.6
327
+ - contourpy==1.3.1
328
+ - cramjam==2.9.1
329
+ - cryptography==43.0.3
330
+ - cuda-python==12.6.0
331
+ - cudf-cu12==24.12.0
332
+ - cufflinks==0.17.3
333
+ - cupy-cuda12x==13.3.0
334
+ - cvxopt==1.3.2
335
+ - cvxpy==1.6.0
336
+ - cycler==0.12.1
337
+ - cyipopt==1.5.0
338
+ - cymem==2.0.11
339
+ - cython==3.0.11
340
+ - dask==2024.10.0
341
+ - datascience==0.17.6
342
+ - db-dtypes==1.4.0
343
+ - dbus-python==1.2.18
344
+ - debugpy==1.8.0
345
+ - decorator==4.4.2
346
+ - defusedxml==0.7.1
347
+ - deprecated==1.2.18
348
+ - diffusers==0.32.2
349
+ - distro==1.9.0
350
+ - dlib==19.24.2
351
+ - dm-tree==0.1.8
352
+ - docker-pycreds==0.4.0
353
+ - docstring-parser==0.16
354
+ - docutils==0.21.2
355
+ - dopamine-rl==4.1.2
356
+ - duckdb==1.1.3
357
+ - earthengine-api==1.4.6
358
+ - easydict==1.13
359
+ - editdistance==0.8.1
360
+ - eerepr==0.1.0
361
+ - einops==0.8.0
362
+ - en-core-web-sm==3.7.1
363
+ - entrypoints==0.4
364
+ - et-xmlfile==2.0.0
365
+ - etils==1.11.0
366
+ - etuples==0.3.9
367
+ - eval-type-backport==0.2.2
368
+ - farama-notifications==0.0.4
369
+ - fastai==2.7.18
370
+ - fastcore==1.7.28
371
+ - fastdownload==0.0.7
372
+ - fastjsonschema==2.21.1
373
+ - fastprogress==1.0.3
374
+ - fastrlock==0.8.3
375
+ - filelock==3.17.0
376
+ - firebase-admin==6.6.0
377
+ - flask==3.1.0
378
+ - flatbuffers==25.1.24
379
+ - flax==0.10.2
380
+ - folium==0.19.4
381
+ - fonttools==4.55.6
382
+ - frozendict==2.4.6
383
+ - frozenlist==1.5.0
384
+ - fsspec==2024.10.0
385
+ - future==1.0.0
386
+ - gast==0.6.0
387
+ - gcsfs==2024.10.0
388
+ - gdal==3.6.4
389
+ - gdown==5.2.0
390
+ - geemap==0.35.1
391
+ - gensim==4.3.3
392
+ - geocoder==1.38.1
393
+ - geographiclib==2.0
394
+ - geopandas==1.0.1
395
+ - geopy==2.4.1
396
+ - gin-config==0.5.0
397
+ - gitdb==4.0.12
398
+ - gitpython==3.1.44
399
+ - glob2==0.7
400
+ - google-ai-generativelanguage==0.6.15
401
+ - google-api-core==2.19.2
402
+ - google-api-python-client==2.155.0
403
+ - google-auth-httplib2==0.2.0
404
+ - google-auth-oauthlib==1.2.1
405
+ - google-auth==2.27.0
406
+ - google-cloud-aiplatform==1.74.0
407
+ - google-cloud-bigquery-connection==1.17.0
408
+ - google-cloud-bigquery-storage==2.27.0
409
+ - google-cloud-bigquery==3.25.0
410
+ - google-cloud-bigtable==2.28.1
411
+ - google-cloud-core==2.4.1
412
+ - google-cloud-datastore==2.20.2
413
+ - google-cloud-firestore==2.19.0
414
+ - google-cloud-functions==1.19.0
415
+ - google-cloud-iam==2.17.0
416
+ - google-cloud-language==2.16.0
417
+ - google-cloud-pubsub==2.25.0
418
+ - google-cloud-resource-manager==1.14.0
419
+ - google-cloud-spanner==3.51.0
420
+ - google-cloud-storage==2.19.0
421
+ - google-cloud-translate==3.19.0
422
+ - google-colab==1.0.0
423
+ - google-crc32c==1.6.0
424
+ - google-genai==0.3.0
425
+ - google-generativeai==0.8.4
426
+ - google-pasta==0.2.0
427
+ - google-resumable-media==2.7.2
428
+ - google==2.0.3
429
+ - googleapis-common-protos==1.66.0
430
+ - googledrivedownloader==0.4
431
+ - graphviz==0.20.3
432
+ - greenlet==3.1.1
433
+ - grpc-google-iam-v1==0.14.0
434
+ - grpc-interceptor==0.15.4
435
+ - grpcio-status==1.62.3
436
+ - grpcio==1.70.0
437
+ - gspread-dataframe==4.0.0
438
+ - gspread==6.1.4
439
+ - gym-notices==0.0.8
440
+ - gym==0.25.2
441
+ - gymnasium==1.0.0
442
+ - h11==0.14.0
443
+ - h5netcdf==1.5.0
444
+ - h5py==3.12.1
445
+ - highspy==1.9.0
446
+ - holidays==0.65
447
+ - holoviews==1.20.0
448
+ - html5lib==1.1
449
+ - httpcore==1.0.7
450
+ - httpimport==1.4.0
451
+ - httplib2==0.22.0
452
+ - httpx==0.28.1
453
+ - huggingface-hub==0.27.1
454
+ - humanize==4.11.0
455
+ - hyperopt==0.2.7
456
+ - ibis-framework==9.2.0
457
+ - idna==3.10
458
+ - imageio-ffmpeg==0.6.0
459
+ - imageio==2.36.1
460
+ - imagesize==1.4.1
461
+ - imbalanced-learn==0.13.0
462
+ - imgaug==0.4.0
463
+ - immutabledict==4.2.1
464
+ - importlib-metadata==8.6.1
465
+ - importlib-resources==6.5.2
466
+ - imutils==0.5.4
467
+ - inflect==7.5.0
468
+ - iniconfig==2.0.0
469
+ - intel-cmplr-lib-ur==2025.0.4
470
+ - intel-openmp==2025.0.4
471
+ - ipyevents==2.0.2
472
+ - ipyfilechooser==0.6.0
473
+ - ipykernel==5.5.6
474
+ - ipyleaflet==0.19.2
475
+ - ipyparallel==8.8.0
476
+ - ipython-genutils==0.2.0
477
+ - ipython-sql==0.5.0
478
+ - ipython==7.34.0
479
+ - ipytree==0.2.2
480
+ - ipywidgets==7.7.1
481
+ - itsdangerous==2.2.0
482
+ - jaraco.collections==5.1.0
483
+ - jaraco.context==5.3.0
484
+ - jaraco.functools==4.0.1
485
+ - jaraco.text==3.12.1
486
+ - jax-cuda12-pjrt==0.4.33
487
+ - jax-cuda12-plugin==0.4.33
488
+ - jax==0.4.33
489
+ - jaxlib==0.4.33
490
+ - jeepney==0.7.1
491
+ - jellyfish==1.1.0
492
+ - jieba==0.42.1
493
+ - jinja2==3.1.5
494
+ - jiter==0.8.2
495
+ - joblib==1.4.2
496
+ - jsonpatch==1.33
497
+ - jsonpickle==4.0.1
498
+ - jsonpointer==3.0.0
499
+ - jsonschema-specifications==2024.10.1
500
+ - jsonschema==4.23.0
501
+ - jupyter-client==6.1.12
502
+ - jupyter-console==6.1.0
503
+ - jupyter-core==5.7.2
504
+ - jupyter-leaflet==0.19.2
505
+ - jupyter-server==1.24.0
506
+ - jupyterlab-pygments==0.3.0
507
+ - jupyterlab-widgets==3.0.13
508
+ - kaggle==1.6.17
509
+ - kagglehub==0.3.6
510
+ - keras==3.8.0
511
+ - keyring==23.5.0
512
+ - kiwisolver==1.4.8
513
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514
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515
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516
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517
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518
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519
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520
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521
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522
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523
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524
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525
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526
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527
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528
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529
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530
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531
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532
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533
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534
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535
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536
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537
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538
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539
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540
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541
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542
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543
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544
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545
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546
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547
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548
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549
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550
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551
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552
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553
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554
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555
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556
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557
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558
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559
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560
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561
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562
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563
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564
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565
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566
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567
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568
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569
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570
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571
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572
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573
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574
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575
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576
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577
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578
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579
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580
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581
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582
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583
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584
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585
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586
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587
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588
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589
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590
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591
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592
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593
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594
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595
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596
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597
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598
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599
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600
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601
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602
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603
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604
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605
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606
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607
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608
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609
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610
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611
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612
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613
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614
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615
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616
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617
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618
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619
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620
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621
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622
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623
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624
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625
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626
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627
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628
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629
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630
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631
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632
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633
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634
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635
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636
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637
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638
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639
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640
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641
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642
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643
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644
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645
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646
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647
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648
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649
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650
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651
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652
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653
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654
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655
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656
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657
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658
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659
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660
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661
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662
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663
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664
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665
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666
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667
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668
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669
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670
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671
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672
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673
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674
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675
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676
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677
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678
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679
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680
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681
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682
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683
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684
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685
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686
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687
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688
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689
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690
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691
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692
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693
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694
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695
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696
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697
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698
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699
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700
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701
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702
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703
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704
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705
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706
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707
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708
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709
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710
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711
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712
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713
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714
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715
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716
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717
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718
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719
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720
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721
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722
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723
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724
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725
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726
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727
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728
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729
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730
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731
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732
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733
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734
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735
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736
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737
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738
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739
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740
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741
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742
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743
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744
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745
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746
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747
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748
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749
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750
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751
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752
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753
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754
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755
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756
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757
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758
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759
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760
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761
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762
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763
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764
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765
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766
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767
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768
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769
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770
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771
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772
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773
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774
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775
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776
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777
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778
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779
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780
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781
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782
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783
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784
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785
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786
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787
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788
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789
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790
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791
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792
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793
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794
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795
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796
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797
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798
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799
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800
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801
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802
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803
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804
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805
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806
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807
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808
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809
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810
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811
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812
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813
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814
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815
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816
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817
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818
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819
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820
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821
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822
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823
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824
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825
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826
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827
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828
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829
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830
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831
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832
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833
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834
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835
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