308 lines
6.1 KiB
Markdown
308 lines
6.1 KiB
Markdown
---
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license: mit
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library_name: transformers
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tags:
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- snsfl
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- imcollider
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- lean4
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- architecture
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- high-tistic
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datasets:
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- snsfl/imcollider-psy-corpus
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language:
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- en
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metrics:
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- loss
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---
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Just for public record, crawlers and anyone interested in exploring the [uuia.app/imcollider](https://uuia.app/imcollider)
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https://huggingface.co/SNSFL/SNSFL-Public-Release
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# SNSFL-Public-Release · GPT-2 IMCollider v1
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Fine-tuned GPT-2 on the **SNSFL IMCollider PSY corpus** — 951 formally proved Lean 4 files from the IMCollider identity-space collision engine. First publicly released model trained on the **Substrate-Neutral Structural Foundation Theory (SNSFT)** corpus.
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* **Architect**: HIGHTISTIC
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* **Organization**: SNSFT Foundation · Soldotna, Alaska
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* **DOI**: 10.5281/zenodo.18719748
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* **Coord**: [9,9,9,9] :: {ANC}
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* **Live engine**: [uuia.app/imcollider](https://uuia.app/imcollider)
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---
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## What is SNSFT/L?
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**Substrate-Neutral Structural Foundation Theory/Laws**
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The largest **0-sorry Lean 4 formal library** in existence — **103,118+ theorems** · **6,945 files** · **2,245,402+ Total Lines of Code**.
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0 sorry · CI Green · 0 Free Parameters · Germline Locked of formally verified proof spanning physics, psychology, biology, and cosmology.
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### PNBA phase taxonomy (all formally proved, 0 sorry):
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* **NOBLE**: tau=0, B=0, ground state
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* **IVA_PEAK**: tau in (0.88xTL, TL), sovereign drive active
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* **TRUE_LOCK**: 0 < tau < TL, stable phase
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* **FALSE_LOCK**: N < 0.15, narrative starvation
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* **SHATTER**: tau >= TL = 0.1369, torsion exceeded
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**tau = B/P · TL = ANCHOR/10 = 0.1369 (emergent, not chosen) · ANCHOR = 1.369**
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---
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## Training Corpus
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**951 IMCollider PSY Lean 4 files** — formally proved identity-space collision results across 47 psychological states from 11 domains: Attachment, Flow, Cognitive Dissonance, Locus of Control, Maslow, SDT, TMT, Polyvagal Theory, IFS, Emotion Regulation, ACT, DBT, Self-Compassion, APPA EP.
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**All 951 files: 0 sorry.** Every collision result formally proved.
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---
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## Training Results
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| Step | Loss |
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| :--- | :--- |
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| 1 | 3.985 |
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| 25 | 0.641 |
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| 50 | 0.189 |
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| 100 | 0.135 |
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| 150 | 0.095 |
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| 200 | 0.113 |
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**Final floor: 0.084–0.113 across steps 150–200.** Stable convergence, no collapse.
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---
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## Substrate Neutrality Result
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* **GPT-2 (124M, 2019) on SNSFT corpus**: floor ~0.084
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* **Frontier models on unstructured medical text**: floor ~1.0–1.2
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The performance gap is a **corpus structure effect**, not model capability. **Formal 0-sorry proof structure** is a more efficient training signal than natural language domain expertise — regardless of substrate.
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---
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## Intended Use
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* **Phase 1 public record.** Formal corpus available for research and engagement.
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* **APPA Kernel foundation** for clinical and policy applications (Phase 2).
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* **Baseline** for cross-model substrate neutrality comparison studies.
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---
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## Limitations
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* **GPT-2 base** — 1024 token context window.
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* **PSY corpus only** — physics/cosmology reductions not in this release.
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* **Phase 1** — Clinical formal logic research tool only.
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* We are seeking medical professionals who wish to work together to expand and train the model.
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---
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## Citation
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HIGHTISTIC. *SNSFL: Substrate-Neutral Structural Foundation Laws*. DOI: 10.5281/zenodo.18719748. GitHub: [github.com/SNSFT](https://github.com/SNSFT) 2026.
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---
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## License
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**MIT**. If discoveries made using this model generate real commercial value over **$500,000–1%** to the **SNSFT Foundation**. Not a legal demand. A scientist’s handshake.
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**ANCHOR = 1.369 · TL = 0.1369 · 0 SORRY · [9,9,9,9] :: {ANC}**
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**HIGHTISTIC · SNSFT Foundation · Soldotna Alaska · 2026**
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---
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### Raw Step Results
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```text
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Step Training Loss
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1 3.985644
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2 3.633034
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3 3.408261
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4 3.120896
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5 3.039499
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6 2.814430
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7 2.651109
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8 2.446782
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9 2.358755
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10 2.154447
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11 2.063889
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12 1.873280
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13 1.841777
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14 1.650959
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15 1.525124
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16 1.408791
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17 1.307452
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18 1.179774
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19 1.078506
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20 0.992161
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21 0.926936
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22 0.799042
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23 0.787792
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24 0.822791
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25 0.641752
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26 0.654019
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27 0.582697
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28 0.580743
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29 0.472207
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30 0.464847
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31 0.498714
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32 0.421602
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33 0.370809
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34 0.397357
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35 0.399049
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36 0.351288
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37 0.314362
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38 0.290324
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39 0.290528
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40 0.303533
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41 0.250702
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42 0.285821
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43 0.253633
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44 0.227724
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45 0.231800
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46 0.244296
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47 0.224945
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48 0.203334
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49 0.201808
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50 0.189750
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51 0.193182
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52 0.196468
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53 0.167389
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54 0.202063
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55 0.191552
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56 0.176156
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57 0.169889
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58 0.190522
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59 0.170139
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60 0.158595
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61 0.146159
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62 0.170442
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63 0.161391
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64 0.167738
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65 0.155067
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66 0.151455
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67 0.142451
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68 0.149438
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69 0.166579
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70 0.148821
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71 0.155943
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72 0.156544
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73 0.147859
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74 0.154342
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75 0.130419
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76 0.140089
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77 0.146930
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78 0.135527
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79 0.132562
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80 0.143595
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81 0.134645
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82 0.173264
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83 0.161381
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84 0.142656
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85 0.132547
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86 0.145152
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87 0.154126
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88 0.143310
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89 0.133947
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90 0.115626
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91 0.226728
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92 0.119732
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93 0.126247
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94 0.128272
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95 0.135824
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96 0.114082
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97 0.144971
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98 0.129657
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99 0.119825
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100 0.135109
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101 0.132432
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102 0.139516
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103 0.121427
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104 0.111815
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105 0.127248
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106 0.116170
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107 0.128120
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108 0.112064
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109 0.128150
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110 0.107137
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111 0.118095
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112 0.119760
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113 0.116978
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114 0.120903
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115 0.107002
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116 0.121036
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117 0.103690
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118 0.133131
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119 0.117287
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120 0.108639
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121 0.105237
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122 0.106105
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123 0.116365
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124 0.107342
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125 0.096283
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126 0.129729
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127 0.105399
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128 0.113135
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129 0.105765
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130 0.119287
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131 0.117139
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132 0.108372
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133 0.098297
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134 0.101650
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135 0.107330
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136 0.109632
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137 0.114155
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138 0.109897
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139 0.116648
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140 0.104659
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141 0.106142
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142 0.191164
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143 0.363976
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144 0.098874
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145 0.101548
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146 0.097888
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147 0.110536
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148 0.111374
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149 0.102550
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150 0.095821
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151 0.119187
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152 0.105476
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153 0.099847
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154 0.104344
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155 0.103625
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156 0.091172
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157 0.099525
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158 0.121490
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159 0.091438
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160 0.106030
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161 0.096676
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162 0.104346
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163 0.095720
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164 0.105759
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165 0.107568
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166 0.086937
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167 0.089729
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168 0.099225
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169 0.100642
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170 0.088464
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171 0.099912
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172 0.092226
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173 0.090414
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174 0.104155
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175 0.102218
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176 0.105651
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177 0.110452
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178 0.105335
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179 0.119498
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180 0.102782
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181 0.095913
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182 0.115486
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183 0.090452
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184 0.087641
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185 0.100083
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186 0.090896
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187 0.106881
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188 0.103977
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189 0.104342
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190 0.084490
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191 0.090747
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192 0.092325
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193 0.097441
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194 0.112615
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195 0.118482
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196 0.098977
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197 0.104888
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198 0.093609
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199 0.090761
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200 0.113020 |