Sample stimuli

sample 0 sample 1 sample 2 sample 3 sample 4 sample 5 sample 6 sample 7 sample 8 sample 9

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("tong.Coggan2024_behavior-ConditionWiseAccuracySimilarity")
score = benchmark(my_model)

Model scores

Min Alignment Max Alignment

Rank

Model

Score

1
.844
2
.779
3
.707
4
.700
5
.689
6
.677
7
.673
8
.659
9
.636
10
.635
11
.628
12
.626
13
.619
14
.613
15
.611
16
.603
17
.597
18
.595
19
.591
20
.590
21
.590
22
.588
23
.588
24
.586
25
.575
26
.573
27
.571
28
.566
29
.558
30
.555
31
.554
32
.552
33
.552
34
.552
35
.551
36
.542
37
.542
38
.541
39
.540
40
.536
41
.535
42
.535
43
.535
44
.534
45
.529
46
.526
47
.526
48
.523
49
.520
50
.519
51
.519
52
.515
53
.515
54
.507
55
.505
56
.504
57
.501
58
.497
59
.484
60
.482
61
.478
62
.476
63
.471
64
.469
65
.469
66
.467
67
.466
68
.465
69
.463
70
.460
71
.459
72
.457
73
.454
74
.453
75
.448
76
.448
77
.446
78
.434
79
.430
80
.425
81
.421
82
.412
83
.411
84
.409
85
.409
86
.407
87
.398
88
.397
89
.393
90
.392
91
.383
92
.383
93
.379
94
.374
95
.372
96
.372
97
.371
98
.371
99
.360
100
.359
101
.356
102
.351
103
.342
104
.339
105
.338
106
.333
107
.331
108
.331
109
.331
110
.329
111
.326
112
.323
113
.320
114
.320
115
.317
116
.317
117
.316
118
.315
119
.312
120
.311
121
.305
122
.303
123
.303
124
.300
125
.299
126
.298
127
.295
128
.293
129
.288
130
.284
131
.277
132
.273
133
.261
134
.258
135
.258
136
.256
137
.251
138
.250
139
.236
140
.235
141
.229
142
.229
143
.228
144
.226
145
.226
146
.219
147
.216
148
.215
149
.214
150
.211
151
.211
152
.210
153
.207
154
.201
155
.198
156
.191
157
.186
158
.180
159
.180
160
.180
161
.170
162
.166
163
.165
164
.162
165
.162
166
.162
167
.159
168
.156
169
.154
170
.154
171
.153
172
.148
173
.144
174
.144
175
.143
176
.142
177
.139
178
.133
179
.133
180
.132
181
.132
182
.132
183
.129
184
.129
185
.129
186
.123
187
.123
188
.122
189
.113
190
.113
191
.113
192
.111
193
.111
194
.110
195
.110
196
.108
197
.106
198
.103
199
.101
200
.101
201
.099
202
.096
203
.096
204
.095
205
.092
206
.092
207
.092
208
.089
209
.079
210
.079
211
.078
212
.077
213
.077
214
.077
215
.064
216
.063
217
.062
218
.058
219
.052
220
.048
221
.044
222
.043
223
.038
224
.036
225
.035
226
.023
227
.023
228
.022
229
.021
230
.020
231
.019
232
.018
233
.012
234
.009
235
.007
236
.007
237
.007
238
.006
239
.006
240
.006
241
.006
242
.005
243
.005
244
.005
245
.004
246
.003
247
.003
248
.002
249
.002
250
.001
251
.000
252
.000
253
.000
254
.000
255
.002
256
.002
257
.002
258
.002
259
.004
260
.006
261
.007
262
.008
263
.009
264
.017
265
.023
266
.023
267
.033
268
.034
269
.067
270
.069
271
.142
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304

Benchmark bibtex

None

Ceiling

0.69.

Note that scores are relative to this ceiling.

Data: tong.Coggan2024_behavior

Metric: ConditionWiseAccuracySimilarity