OpenScientificCodeRegistry/Database
Open Scientific Code Registry (OSCR): the authors' scripts The code published by the authors of open-access neuroscience papers, as found and verified by Open Scientific Code Registry (OSCR). Each file is here exactly as it is at the source, at the verified commit, under the license of its repository. 421,275 unique files (3,782 MB of text) from 8,849 repositories, in 24 Parquet block(s). Only files whose repository's license allows redistribution, confirmed by the repository's… See the full description on the dataset page: https://huggingface.co/datasets/OpenScientificCodeRegistry/Database.
05.6k
1{2 "format": "oscr-script-manifest/1",3 "repository": "github.com/morrocwi/rrhm-open-lab",4 "url": "https://github.com/morrocwi/rrhm-open-lab/releases/tag/staveland-lock-v4",5 "host": "github.com",6 "commit": "16b5e09acf62e8e39adb1d5d309be1065d1aef2a",7 "license": "MIT",8 "license_confirmed_by": "license file LICENSE",9 "redistribution": "yes",10 "files": [11 {12 "path": "LICENSE",13 "sha256": "efb424c9cfa2563bacbb2d3607f861c46026f754c6f59532d40d391834052244",14 "language": "License",15 "lines": 24,16 "truncated": false,17 "block": 10,18 "row": 613919 },20 {21 "path": "README.md",22 "sha256": "6d6c99cb0fa407ff4316a6b9db45a257f097bdb4d88a1bbff6bfe57ddbbd5e7d",23 "language": "Text",24 "lines": 150,25 "truncated": false,26 "block": 10,27 "row": 1999428 },29 {30 "path": "code/calculators/recalibration.py",31 "sha256": "1b4c744db2692b1a43999b593f2ffc14b08fc6186c69b268ccf55b8af7f7331d",32 "language": "Python",33 "lines": 59,34 "truncated": false,35 "block": 10,36 "row": 1206437 },38 {39 "path": "code/figures/make_figures.py",40 "sha256": "7922fd2cbdfb2cabf530fff00250fe04d847cfb3947e57e779f6bfc81429a47d",41 "language": "Python",42 "lines": 33,43 "truncated": false,44 "block": 10,45 "row": 1164146 },47 {48 "path": "code/gates/rrhm_gates_k3_k6_k8_k9.py",49 "sha256": "1dc517cce07911ec009bef2fb625620a71fb7f748d0e2f8078b3462e6046f9c1",50 "language": "Python",51 "lines": 273,52 "truncated": false,53 "block": 10,54 "row": 1606555 },56 {57 "path": "code/opendata/c23_hra1_artifact_controls.py",58 "sha256": "852fce6496a1efb9df05c0f5d7655b3130a3a29adb0344c21f7f0f0981c879a0",59 "language": "Python",60 "lines": 54,61 "truncated": false,62 "block": 10,63 "row": 1237964 },65 {66 "path": "code/opendata/c23_hra1_timing.py",67 "sha256": "d720a8b1703db4d55bc08ef14118c1c2ea474387935deadc387e7c1d5e35932a",68 "language": "Python",69 "lines": 54,70 "truncated": false,71 "block": 10,72 "row": 1222473 },74 {75 "path": "code/opendata/c23_lane_dissociation.py",76 "sha256": "534c602024ecc38ab3d9b46a8ca3fda0d7b9da46f9452ea6564f2f349aecfe9a",77 "language": "Python",78 "lines": 55,79 "truncated": false,80 "block": 10,81 "row": 1205682 },83 {84 "path": "code/opendata/c25_lane_mtmm.py",85 "sha256": "412f0777e68053de9f66035b4dba6d6a079dbce9bda4ce4dfcb4011e7976b54d",86 "language": "Python",87 "lines": 89,88 "truncated": false,89 "block": 10,90 "row": 1317591 },92 {93 "path": "code/opendata/c26_stress_transport.py",94 "sha256": "4628020e1961c240e390f98b22216a34076fb3d84c5b9b25d54789d48fff37e8",95 "language": "Python",96 "lines": 73,97 "truncated": false,98 "block": 10,99 "row": 12925100 },101 {102 "path": "code/opendata/c27_predictability_clamp.py",103 "sha256": "0da9a41c0a2e60d85e8729bc6aaaa47ded1daf08da7535021f967ebe3cf2e401",104 "language": "Python",105 "lines": 158,106 "truncated": false,107 "block": 10,108 "row": 14814109 },110 {111 "path": "code/opendata/c28_rankstab_mtmm.py",112 "sha256": "4741c9333b4ee7d00324f3b679b27e6f096a97138fad3a16796b579f9fa833c6",113 "language": "Python",114 "lines": 93,115 "truncated": false,116 "block": 10,117 "row": 13123118 },119 {120 "path": "code/opendata/c28_sensitivity.py",121 "sha256": "d6a00ad2e7c0c4bb07b866631d42dac34a0986a947690adcf40313f703194e0a",122 "language": "Python",123 "lines": 99,124 "truncated": false,125 "block": 10,126 "row": 13135127 },128 {129 "path": "code/opendata/c29_audit_phi_tail.py",130 "sha256": "cc95dc4485cfbaf39ac9e23d6c6fff0eaf4e1879de9e4324a5437e3d0be68474",131 "language": "Python",132 "lines": 130,133 "truncated": false,134 "block": 10,135 "row": 13922136 },137 {138 "path": "code/opendata/c29_model_comparison.py",139 "sha256": "48443b46c470771704c63a242bf16253b7e80f675a339fc5b18b945b766c8c01",140 "language": "Python",141 "lines": 134,142 "truncated": false,143 "block": 10,144 "row": 14020145 },146 {147 "path": "code/opendata/c30_external_transport.py",148 "sha256": "a9713dc3fba46372b1649993ea76580167da3052dc55caf76706859d6c4cc26a",149 "language": "Python",150 "lines": 134,151 "truncated": false,152 "block": 10,153 "row": 13732154 },155 {156 "path": "code/opendata/c31_2w_rofl_fourcell.py",157 "sha256": "b3ee7d659600d4f1737d167a74676ee6dbfcb7804d027813b7be390a8c372f79",158 "language": "Python",159 "lines": 136,160 "truncated": false,161 "block": 10,162 "row": 13842163 },164 {165 "path": "code/opendata/c31_degradation_calibration.py",166 "sha256": "dfc18cf780fc03d4d01405acf49425210d4adbfc96b7ce8d145133704fc14dfb",167 "language": "Python",168 "lines": 221,169 "truncated": false,170 "block": 10,171 "row": 15252172 },173 {174 "path": "code/sims/coupling_extension_sims.py",175 "sha256": "087f05a9ad6de29e12835057113e7cb7159f4e226300780ae61f63d3d13e5392",176 "language": "Python",177 "lines": 64,178 "truncated": false,179 "block": 10,180 "row": 12888181 },182 {183 "path": "code/tools/verify_citations.py",184 "sha256": "17c4f57b50fbf55706c8334667bead96fb89e11838407923b6aaf2e2e7d78731",185 "language": "Python",186 "lines": 144,187 "truncated": false,188 "block": 10,189 "row": 15748190 },191 {192 "path": "targets/staveland_2026/code/01_reproduce_staveland.py",193 "sha256": "fb45bf6bfba0269befa53bcaac1b84554df00d43176bf3728ffe1888a28b36c1",194 "language": "Python",195 "lines": 48,196 "truncated": false,197 "block": 10,198 "row": 12149199 },200 {201 "path": "targets/staveland_2026/code/02_recoverability_margin.py",202 "sha256": "cc080143a91692640a50eeee3b29a02fa95741b939e74b3cb7919878b089427c",203 "language": "Python",204 "lines": 37,205 "truncated": false,206 "block": 10,207 "row": 11705208 },209 {210 "path": "targets/staveland_2026/code/03_reproduce_fig1_turnaround_reward.py",211 "sha256": "18272c4b2222361c5ac9ed52dd818c0d57e16cb9d97a665ef2016350bbdd75bd",212 "language": "Python",213 "lines": 89,214 "truncated": false,215 "block": 10,216 "row": 13279217 }218 ]219}