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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("SanghaviMurty2020.V4-pls")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	compact_resnet50_robust_V4	.348
2	FrankRobWobv0	.330
3	compact_vgg19_V4	.317
4	compact_resnet50_V4	.295
5	compact_cornets_V4	.293
6	ReAlnet01_cornet_fov4	.273
7	ReAlnet10_cornet	.258
8	efficientnet_b2_imagenet_full	.257
9	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.256
10	cvt_cvt-21-384-in1k_4_LucyV4	.256
11	mobilenet_v2_0_75_224	.256
12	ReAlnet08_cornet	.254
13	konkle_alexnetgn_ipcl_ref01_primary_model	.253
14	resnet50_cpc_linhead	.247
15	effnetb1_272x240	.246
16	ReAlnet05_cornet	.246
17	mobilenet_v2_1_0_192	.245
18	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.245
19	resnet_101_v1	.245
20	compact_cornets_IT	.244
21	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.244
22	inception_v1	.244
23	mobilenet_v2_1_3_224	.243
24	mobilenet_v2_1.0_192-tf	.243
25	resnet101_imagenet_full	.243
26	resnet152_imagenet_full	.243
27	ReAlnet02_cornet	.242
28	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.242
29	ReAlnet03_cornet	.242
30	ReAlnet07_cornet	.241
31	focalnet_tiny_lrf_in1k	.240
32	resnet152_ecoset_full	.240
33	resnet-101_v2-tf	.240
34	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.240
35	mehrer2020_alexnet_training_seed_01_fov4	.240
36	ReAlnet01_cornet	.240
37	convnext_large:fb_in22k_ft_in1k	.239
38	deit3_base_patch16_224_fb_in22k_ft_in1k	.239
39	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.239
40	resnet-152_v1-tf	.239
41	ReAlnet04_cornet	.239
42	vit_large_patch14_clip_224:laion2b_ft_in1k	.239
43	resnet-152_v2-tf	.239
44	vision_transformer_vit_large_patch16_224	.239
45	RN50	.239
46	ReAlnet06_cornet	.238
47	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.238
48	grcnn_robust_v1	.237
49	ReAlnet09_cornet	.237
50	omnivore_swinB	.237
51	omnivore_swinS	.237
52	cvt_cvt-21-224-in1k_4_LucyV4	.236
53	convnext_large_clip_laion2b_finelayers	.236
54	cvt_cvt-13-384-in1k_4_LucyV4	.235
55	custom_model_cv_18_dagger_408	.235
56	convnext_tiny:in12k_ft_in1k	.235
57	resnet101_ecoset_full	.235
58	grcnn_v2_text_noise	.235
59	dinov2_vitl14_reg_lc	.234
60	dinov2_vitl14_reg_lc_featread	.234
61	ReAlnet10_ALL	.233
62	mobilenet_v2_1.0_160-tf	.233
63	ReAlnet09_ALL	.233
64	ReAlnet07_ALL	.233
65	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.232
66	vit_base_patch16_clip_224:openai_ft_in1k	.232
67	convnext_femto_ols:d1_in1k	.232
68	convnext_xlarge:fb_in22k_ft_in1k	.232
69	tv_efficientnet-b1	.232
70	ReAlnet04_ALL	.232
71	vit_base_patch16_dinov3-lvd1689m	.231
72	mobilenet_v2_0.75_224-tf	.231
73	vit_large_clip336_openai	.231
74	vit_large_patch14_clip_224:openai_ft_in1k	.231
75	grcnn	.231
76	ReAlnet05_ALL	.231
77	ReAlnet08_ALL	.231
78	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.231
79	ReAlnet01_ALL	.230
80	mobilenet_v2_0.75_192-tf	.230
81	vit_large_patch14_clip_336:laion2b_ft_in1k	.230
82	dinov2_vitg14_lc	.230
83	vit_base_patch14_dinov2-lvd142m	.230
84	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.230
85	ReAlnet02_ALL	.230
86	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.230
87	convnext_tiny_sup	.229
88	ReAlnet03_ALL	.229
89	resnet50_ewconplus_wzc	.229
90	mobilenet_v2_1_0_160	.229
91	omnivore_swinT	.229
92	ReAlnet06_ALL	.228
93	Res2Net50_26w_4s	.228
94	CORnet-S	.228
95	mobilenet_v2_0_75_192	.228
96	cvt_cvt-13-224-in1k_4_LucyV4	.228
97	resnet50_robust_l2_eps1	.227
98	convnext_large_imagenet_full_seed-0	.227
99	vit_base_patch14_reg4_dinov2-lvd142m	.227
100	eva02_large_in22k	.227
101	dinov2_vitl14_lc	.227
102	resnet50_ewconplus_wzc_seed2_2__323	.226
103	mobilenet_v2_0_75_160	.226
104	resnet50_st_wzc_seed7_2_323	.225
105	resnet-50_v2-tf	.225
106	voneresnet-50-non_stochastic	.225
107	xception-keras	.225
108	vonegrcnn_47e	.225
109	mobilenet_v2_1.3_224-tf	.225
110	efficientnet_b0	.225
111	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.224
112	vit_relpos_base_patch16_clsgap_224:sw_in1k	.224
113	inception_v1-tf	.223
114	densenet-121	.223
115	densenet-169-keras	.223
116	resnet50_hvs_wzc	.223
117	mobilenet_v2_0.5_160	.223
118	ViT-B/32	.222
119	AdvProp_efficientnet-b6	.222
120	barlow-twins-resnet50	.222
121	resnet50-VITO-8deg-cc	.222
122	mobilenet_v2_0_5_192	.222
123	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.222
124	mobilenet_v2_1_4_224	.222
125	CLIP_ViT-B_32	.222
126	resnet-101_v1-tf	.221
127	grcnn_109	.221
128	dinov2_vitg14_reg_lc	.220
129	convnext_xxlarge_clip	.220
130	vonegrcnn_52e_full	.220
131	antialias-resnet152	.220
132	mobilenet_v2_1.4_224-tf	.219
133	resnet-18-LC_1st_conv_m	.219
134	inception_v3-tf	.219
135	resnet50_ewconplus_wzc_seed5_2__323	.219
136	inception_v2-tf	.219
137	effnetv2m_custom384	.219
138	resnet50_st_wzc_seed3_2_323	.219
139	resnet50_st_wzc_2	.218
140	vonegrcnn_62e_nobn	.218
141	inception_resnet_v2	.218
142	mobilenet_v2_0_5_224	.217
143	convnext_base:clip_laiona_augreg_ft_in1k_384	.217
144	densenet-201-keras	.217
145	resnet50-vicregl0p9	.216
146	deit_small_imagenet_full_seed-0	.216
147	vgg-19-keras	.216
148	deit_large_imagenet_full_seed-0	.216
149	resnet50_ewconplus_wzc_seed6_2_323	.215
150	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.215
151	deit3_base_patch16_224_fb_in1k	.215
152	vgg-16-keras	.214
153	resnet50_primary_visual_cortex	.214
154	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.214
155	voneresnet-50	.214
156	mobilenet_v2_0.5_192-tf	.213
157	antialiased-rnext101_32x8d	.213
158	AdvProp_efficientnet-b0	.213
159	regnety_032	.212
160	convnext_large_in22k_supervised	.212
161	VOneCORnet-S	.212
162	alexnet_fov4	.212
163	resnext101_32x48d_wsl	.212
164	BiT-M-R50x1	.211
165	inception_v3	.211
166	vonegrcnn_47e	.211
167	resnet-18-LC_w_sh_100_iter_m	.211
168	resnet34_ecoset_full	.211
169	resnet18-instance_recognition	.211
170	cv_18_dagger_408_pretrained	.210
171	resnet50-vitoimagevidnet8	.210
172	AdvProp_efficientnet-b7	.210
173	mobilenet_v2_0.5_224-tf	.210
174	convnext_base_imagenet_full_seed-0	.209
175	resnet-18-LC_w_sh_100_iter_conv_init_m	.209
176	CLIP-RN50	.209
177	mobilenet_v2_1.0_224-tf	.209
178	dinov2_vitl14_lc_res336	.209
179	0.5x_resnet-18_LC	.209
180	yolos_tiny	.208
181	resnet50-moclr8deg	.208
182	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.208
183	resnet50-vicreg	.208
184	AT_efficientnet-b7	.207
185	resnet50-simclr-vissl	.207
186	densenet-121-keras	.206
187	pnasnet_large_halfPrecision	.206
188	resnet50-barlow	.206
189	mobilenet_v2_1_0_224	.206
190	BiT-M-R101x1	.205
191	antialiased-r50	.205
192	pnasnet_large-tf	.205
193	AdvProp_efficientnet-b4	.205
194	0.5x_resnet-18_LC_w_sh_100_iter	.205
195	mobilenet_v1_0.75_224	.205
196	mobilenet_v2_0.75_160-tf	.205
197	ReAlnet01_cornet_fov12	.205
198	resnext101_32x8d_wsl	.205
199	resnet-50-pytorch	.204
200	resnet-50-robust	.204
201	BiT-M-R50x3	.204
202	convnext_small_imagenet_full_seed-0	.204
203	resnet50_imagenet_100_seed-0	.203
204	compact_vgg19_IT	.203
205	resnext101_32x16d_wsl	.203
206	resnet-18-LC_w_sh_1_iter_conv_init_m	.203
207	AlexNet_SIN_fov4	.202
208	0.5x_resnet-18_LC_w_sh_1_iter	.202
209	deit_base_imagenet_full_seed-0	.202
210	resnet18-local_aggregation	.202
211	CORnet-Z	.202
212	mobilenet_v2_0.35_224	.202
213	resnet50-vicregl0p75	.202
214	densenet-201	.202
215	vgg_16	.201
216	resnext101_32x32d_wsl	.201
217	resnet18-relative_position	.201
218	vit_huge_clip336_laion	.201
219	resnet-50_v1-tf	.201
220	resnet18-deepcluster	.201
221	resnet50_random_linf8_perturb	.201
222	resnet-34	.200
223	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.200
224	resnet-18-LC_d_w_sh_1x1_conv_init_m	.200
225	convnext_small_imagenet_100_seed-0	.200
226	resnet-18-LC_w_sh_1_iter_m	.200
227	0.5x_resnet-18_LC_w_sh_10_iter	.199
228	nasnet_mobile	.199
229	resnet50	.199
230	BiT-S-R50x1	.199
231	fixres_resnext101_32x48d_wsl	.199
232	resnet-18-LC_w_sh_10_iter_conv_init_m	.199
233	mobilenet_v1_0.75_128	.198
234	BiT-M-R152x2	.198
235	BiT-M-R101x3	.198
236	resnet50_st_wzc_seed6_2_323	.198
237	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.198
238	resnet18_imagenet21kP	.198
239	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.198
240	mobilenet_v2_0.5_128	.198
241	resnet50_linf_4_robust	.197
242	convnext_tiny_imagenet_full_seed-0	.197
243	mobilenet_v1_1.0_192	.197
244	resnet50-SIN_IN	.197
245	BiT-S-R101x3	.196
246	0.5x_resnet-18	.196
247	CLIP_resnet50	.196
248	CLIP_resnet50_float32	.196
249	mobilenet_v1_1.0_224	.196
250	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.196
251	resnet_SIN_IN_FT_IN	.195
252	resnet50-SIN_IN_IN	.195
253	mobilenet_v1_0.75_192	.195
254	BiT-S-R50x3	.195
255	densenet-169	.195
256	AdvProp_efficientnet-b8	.195
257	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.194
258	resnet-18	.194
259	resnet_50_v1_spiking_l4	.194
260	resnet_50_v1_spiking	.194
261	resnet_50_v1_spiking_l4a	.194
262	resnet50_tutorial	.194
263	resnet_50_v1_spiking_l3	.194
264	resnet50-sup	.194
265	resnet_50_v1	.194
266	yudixie_resnet50_imagenet1kpret_0_240908	.194
267	resnet50_random_l2_perturb	.193
268	resnet50-SIN	.193
269	mobilenet_v1_0.5_128	.193
270	mobilenet_v2_0.35_160	.193
271	BiT-S-R152x2	.192
272	mobilenet_v2_1_0_128	.192
273	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.192
274	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.192
275	resnet-18-LC_m	.191
276	inception_v4-tf	.191
277	nasnet_large-tf	.191
278	mobilenet_v2_0.75_128	.190
279	my-model	.190
280	mobilenet_v1_0.25_224	.190
281	BiT-S-R101x1	.190
282	mobilenet_v1_1.0_160	.189
283	resnet18_ecoset_full	.189
284	nasnet_mobile-tf	.187
285	resnet34_imagenet_full	.187
286	mobilenet_v1_1.0_128	.186
287	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.186
288	resnet18-contrastive_multiview	.186
289	resnet50_imagenet_full	.185
290	alexnet_l2_3_robust	.185
291	resnet-18-LC_w_sh_10_iter_m	.185
292	efficientnet_b1_imagenet_full	.184
293	resnet50_robust_l2_eps3	.184
294	mehrer2020_alexnet_training_seed_08	.184
295	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.183
296	mobilenet_v1_0.25_192	.183
297	mobilenet_v1_0.75_160	.183
298	mobilenet_v1_0.5_224	.183
299	shufflenet_v2_x1_0	.183
300	resnet50_l2_3_robust	.183
301	BiT-M-R152x4	.183
302	mehrer2020_alexnet_training_seed_02	.182
303	alexnet_random_linf8_perturb	.181
304	squeezenet1_1	.181
305	resnet50_vicreg_linhead	.181
306	voneresnet-50-robust	.181
307	resnet-18-LC_conv_init_m	.181
308	mobilenet_v1_0.5_192	.181
309	deepeisnn_ei_imagenet_resnet18	.180
310	squeezenet1_0	.180
311	mehrer2020_alexnet_training_seed_04	.179
312	resnet18-supervised	.179
313	resnet18-colorization	.179
314	resnet18_imagenet_full	.179
315	texture_shape_resnet50_trained_on_SIN	.179
316	mobilenet_v2_0.35_192	.179
317	mehrer2020_alexnet_training_seed_06	.179
318	eicircuit_resnet18_bn_20260919	.178
319	imagenet_l2_3_0	.178
320	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.178
321	yudixie_resnet50_object_class_0_240908	.178
322	ijepa_vith14_linhead	.178
323	SWSL_resnet50	.177
324	AdvProp_efficientnet-b2	.177
325	resnet50_linf_8_robust	.177
326	vonealexnet	.177
327	resnet50_barlowtwins_linhead	.175
328	BiT-S-R152x4	.175
329	yudixie_resnet18_distance_translation_rotation_0_240719	.175
330	mehrer2020_alexnet_training_seed_09	.174
331	resnet101	.174
332	regnet_y_400mf	.174
333	resnet18_fair	.174
334	alexnet_random_l2_3_perturb	.173
335	resnet50_ecoset_full	.173
336	r3m_resnet50	.173
337	resnet50_simsiam_linhead	.172
338	resnet50_moco_v2	.172
339	AT_efficientnet-b4	.172
340	mobilenet_v1_0.25_160	.172
341	ReAlnet10	.171
342	RN50	.171
343	resnet50_simclr	.171
344	seresnext50_32x4d	.171
345	mobilenet_v2_1.0_128-tf	.171
346	r3m_resnet50_nocrop	.170
347	mehrer2020_alexnet_training_seed_05	.170
348	yudixie_wbh_object_class_scaling_0415_imagenet	.170
349	yudixie_resnet18_imagenet1kpret_0_240719	.170
350	resnet_50_v2	.170
351	mobilenet_v1_0.5_160	.169
352	mehrer2020_alexnet_training_seed_03	.169
353	persistence_memory	.169
354	yudixie_resnet18_distance_translation_0_240719	.169
355	alexnet_training_seed_01_fov4	.169
356	texture_shape_alexnet_trained_on_SIN	.168
357	prednet	.167
358	convnext_base_fb_in22k_ft_in1k	.167
359	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.167
360	persistence_mem	.167
361	resnet-18_test_m	.167
362	mehrer2020_alexnet_training_seed_07	.167
363	deit_small_imagenet_100_seed-0	.166
364	yudixie_resnet18_translation_reg_0_240719	.166
365	vgg_19	.166
366	r3m_resnet18	.165
367	ReAlnet01_cornet_fov16	.165
368	ViT_L_32_imagenet1k	.165
369	yudixie_resnet50_category_class_0_240908	.165
370	alexnet_ks_torevert	.164
371	alexnet	.164
372	yudixie_resnet18_distance_reg_0_240719	.164
373	mobilenet_v2_0.75_96	.164
374	mehrer2020_alexnet_training_seed_01	.164
375	mehrer2020_alexnet_training_seed_10	.164
376	mobilenet_v2_1.0_96	.163
377	ReAlnet08	.163
378	mobilenet_v2_0.35_128	.163
379	AT_efficientnet-b2	.163
380	mobilenet_v1_0.25_128	.162
381	mobilenet_v2_1-4_224_pytorch	.162
382	yudixie_resnet18_object_class_0_240719	.162
383	efficientnet_b0_imagenet_full	.160
384	cornet_s	.160
385	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.160
386	ReAlnet07	.160
387	mehrer2020_alexnet_training_seed_01_fov12	.159
388	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.159
389	resnet50_imagenet_10_seed-0	.158
390	ReAlnet06	.158
391	resnet50_byol_linhead	.158
392	vonealexnet_gaussian_noise_std4_fixed	.158
393	AlexNet_SIN	.157
394	resnet50_byol	.157
395	yudixie_resnet50_translation_rotation_0_240908	.157
396	vggface	.157
397	imagenet_l2_10_0	.156
398	efficientnet-b7	.156
399	artResNet18_1	.156
400	ReAlnet02	.155
401	resnet18-depth_prediction	.155
402	resnet50_ijepacnn_linhead	.155
403	ReAlnet05	.154
404	alexnet_linf_8_robust	.154
405	yudixie_resnet50_distance_translation_0_240908	.154
406	mobilenet_v2_0.35_96	.154
407	yudixie_resnet50_distance_translation_rotation_0_240908	.153
408	mobilenet_v2_0.5_96	.153
409	yudixie_resnet50_translation_reg_0_240908	.152
410	ReAlnet04	.152
411	SWSL_resnext101_32x8d	.152
412	yudixie_resnet18_distance_rotation_0_240719	.152
413	ReAlnet03	.151
414	yudixie_resnet50_distance_rotation_0_240908	.151
415	ReAlnet09	.150
416	resnet18-contrastive_predictive	.150
417	compact_resnet50_IT	.150
418	alexnet_fov12	.149
419	yudixie_resnet18_translation_rotation_0_240719	.149
420	ReAlnet01	.148
421	AlexNet_SIN_fov12	.148
422	yudixie_resnet18_rotation_reg_0_240719	.147
423	convnext_base_fb_in1k	.145
424	convnext_base_fb_in1k_gram_aligned_dinov3	.145
425	r3m_resnet34	.145
426	yudixie_resnet50_distance_reg_0_240908	.145
427	resnet50_simclr_linhead_01norm	.145
428	blt_vs	.144
429	alexnet_early_checkpoint	.143
430	yudixie_resnet18_category_class_0_240719	.143
431	yudixie_resnet50_rotation_reg_0_240908	.141
432	alexnet_reduced_aliasing_early_checkpoint	.139
433	alexnet_robust_correct	.138
434	mehrer2020_alexnet_training_seed_01_fov16	.137
435	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.135
436	compact_resnet50_robust_IT	.132
437	briaai_rmbg_1_4	.132
438	AlexNet_SIN_fov16	.130
439	deepeisnn_ei_cifar10_resnet18	.129
440	alexnet_fov16	.128
441	resnet50_supervised_linhead	.127
442	gabor_filter_mean_abs_4x4_v2	.124
443	gabor_filter_entropy_4x4_v2	.119
444	gabor_filter_entropy_4x4_v2_forcedCosine	.117
445	vith14_supervised_linhead	.113
446	v1-pyr-nodown	.112
447	alexnet_training_seed_02	.112
448	deepeisnn_ei_cifar10_vgg19	.111
449	resnet50-cifar	.110
450	alexnet_training_seed_01	.105
451	resnet18-autoencoder	.105
452	CORnetZ_CIFAR10	.104
453	alexnet_training_seed_03	.102
454	alexnet_training_seed_05	.102
455	alexnet_training_seed_01_fov12	.101
456	alexnet_training_seed_08	.100
457	alexnet_training_seed_10	.100
458	alexnet_training_seed_06	.098
459	alexnet_training_seed_09	.098
460	alexnet_training_seed_07	.095
461	yudixie_wbh_object_class_scaling_0415_run_2	.095
462	resnet-50_untrained	.092
463	resnet50_FractalDB	.091
464	resnet50_pretrained_with_retinal_waves	.091
465	resnet-50x2_untrained	.091
466	alexnet_training_seed_04	.089
467	yudixie_wbh_object_class_scaling_0415_run_1	.088
468	alexnet_training_seed_01_fov16	.087
469	resnet-18_untrained	.086
470	yudixie_wbh_object_class_scaling_0415_run_0	.084
471	resnet50_untrained_linhead	.081
472	hmax	.080
473	CORnetZ_CIFAR10_bs32_20_04	.079
474	yudixie_wbh_object_class_scaling_0415_run_3	.074
475	yudixie_resnet18_random_0_240719	.074
476	vith14_untrained_linhead	.069
477	yudixie_resnet50_random_0_240908	.065
478	resnet50_imagenet_1_seed-0	.063
479	mobilevit_small	.060
480	predictive_coding_pc	.054
481	pr1_stl10_disentangled_alpha04	.050
482	resnet-18-LC_untrained	.049
483	convnext_small_imagenet_10_seed-0	.040
484	gabor_filter_entropy_4x4	.039
485	resnet-152_v2_pytorch	.036
486	convnext_small_imagenet_1_seed-0	.030
487	deit_small_imagenet_10_seed-0	.026
488	deit_small_imagenet_1_seed-0	.020
489	fitvid_trained_on_physion	.020
490	pixels	.014
491	my-model	.013

Benchmark bibtex

@misc{Sanghavi_Murty_DiCarlo_2021,
  title={SanghaviMurty2020},
  url={osf.io/fchme},
  DOI={10.17605/OSF.IO/FCHME},
  publisher={OSF},
  author={Sanghavi, Sachi and Murty, N A R and DiCarlo, James J},
  year={2021},
  month={Nov}
}

Ceiling

0.97.

Note that scores are relative to this ceiling.

Data: SanghaviMurty2020.V4

300 stimuli recordings from 46 sites in V4

Metric: pls