Datasets:

PureOne
/

AIONVITA-NHOSHIYALUN-184

method stringclasses 7 values	seed int64 58.6M 58.6M	queries int64 5 16	execution_work int64 207 4.99k	cumulative_work int64 33k 145k	cold_cumulative_work int64 33k 154k	selected int64 61 157	exact bool 1 class	wall_seconds float64 0 0
least_difference	58,550,000	11	533	33,192	33,192	153	true	0.000111
least_difference	58,550,001	10	525	33,717	33,717	136	true	0.000084
least_difference	58,550,002	6	329	34,046	34,046	86	true	0.000051
least_difference	58,550,003	8	437	34,483	34,483	122	true	0.000139
least_difference	58,550,004	10	485	34,968	34,968	149	true	0.000066
least_difference	58,550,005	16	837	35,805	35,805	125	true	0.000113
least_difference	58,550,006	6	317	36,122	36,122	91	true	0.000043
least_difference	58,550,007	8	421	36,543	36,543	133	true	0.00012
least_difference	58,550,008	8	421	36,964	36,964	123	true	0.000057
least_difference	58,550,009	11	577	37,541	37,541	92	true	0.00008
least_difference	58,550,010	5	265	37,806	37,806	148	true	0.000036
least_difference	58,550,011	8	405	38,211	38,211	120	true	0.000056
least_difference	58,550,012	6	251	38,462	38,462	69	true	0.000031
least_difference	58,550,013	8	333	38,795	38,795	61	true	0.000049
least_difference	58,550,014	10	525	39,320	39,320	136	true	0.000085
least_difference	58,550,015	7	383	39,703	39,703	93	true	0.000052
least_difference	58,550,016	7	369	40,072	40,072	155	true	0.00005
least_difference	58,550,017	10	485	40,557	40,557	113	true	0.000092
least_difference	58,550,018	9	437	40,994	40,994	157	true	0.000058
least_difference	58,550,019	6	263	41,257	41,257	74	true	0.000039
least_difference	58,550,020	8	333	41,590	41,590	61	true	0.000145
least_difference	58,550,021	9	473	42,063	42,063	103	true	0.000069
least_difference	58,550,022	7	369	42,432	42,432	126	true	0.000052
least_difference	58,550,023	7	341	42,773	42,773	145	true	0.000044
balanced	58,550,000	8	4,941	37,600	37,600	153	true	0.000266
balanced	58,550,001	8	4,973	42,573	42,573	136	true	0.000193
balanced	58,550,002	8	4,989	47,562	47,562	86	true	0.000366
balanced	58,550,003	7	4,366	51,928	51,928	122	true	0.00024
balanced	58,550,004	7	4,324	56,252	56,252	149	true	0.000239
balanced	58,550,005	8	4,973	61,225	61,225	125	true	0.000244
balanced	58,550,006	7	4,352	65,577	65,577	91	true	0.000268
balanced	58,550,007	8	4,973	70,550	70,550	133	true	0.000257
balanced	58,550,008	8	4,973	75,523	75,523	123	true	0.000248
balanced	58,550,009	8	4,973	80,496	80,496	92	true	0.000192
balanced	58,550,010	7	4,352	84,848	84,848	148	true	0.000373
balanced	58,550,011	7	4,338	89,186	89,186	120	true	0.000177
balanced	58,550,012	7	4,275	93,461	93,461	69	true	0.000152
balanced	58,550,013	8	4,885	98,346	98,346	61	true	0.000177
balanced	58,550,014	8	4,973	103,319	103,319	136	true	0.000215
balanced	58,550,015	8	4,989	108,308	108,308	93	true	0.000337
balanced	58,550,016	7	4,352	112,660	112,660	155	true	0.000179
balanced	58,550,017	8	4,941	117,601	117,601	113	true	0.000191
balanced	58,550,018	8	4,941	122,542	122,542	157	true	0.000575
balanced	58,550,019	7	4,289	126,831	126,831	74	true	0.000279
balanced	58,550,020	8	4,885	131,716	131,716	61	true	0.000177
balanced	58,550,021	7	4,352	136,068	136,068	103	true	0.000169
balanced	58,550,022	8	4,973	141,041	141,041	126	true	0.00041
balanced	58,550,023	7	4,324	145,365	145,365	145	true	0.000461
handwritten	58,550,000	9	574	33,233	33,233	153	true	0.000125
handwritten	58,550,001	9	628	33,861	33,861	136	true	0.000106
handwritten	58,550,002	8	541	34,402	34,402	86	true	0.000241
handwritten	58,550,003	7	502	34,904	34,904	122	true	0.000088
handwritten	58,550,004	8	482	35,386	35,386	149	true	0.000072
handwritten	58,550,005	8	488	35,874	35,874	125	true	0.000104
handwritten	58,550,006	8	505	36,379	36,379	91	true	0.000195
handwritten	58,550,007	9	652	37,031	37,031	133	true	0.000186
handwritten	58,550,008	8	469	37,500	37,500	123	true	0.000066
handwritten	58,550,009	8	500	38,000	38,000	92	true	0.00015
handwritten	58,550,010	8	550	38,550	38,550	148	true	0.000086
handwritten	58,550,011	8	548	39,098	39,098	120	true	0.000085
handwritten	58,550,012	8	481	39,579	39,579	69	true	0.000074
handwritten	58,550,013	6	318	39,897	39,897	61	true	0.000049
handwritten	58,550,014	9	572	40,469	40,469	136	true	0.000128
handwritten	58,550,015	8	548	41,017	41,017	93	true	0.00009
handwritten	58,550,016	9	617	41,634	41,634	155	true	0.000107
handwritten	58,550,017	8	463	42,097	42,097	113	true	0.000068
handwritten	58,550,018	8	455	42,552	42,552	157	true	0.000072
handwritten	58,550,019	7	441	42,993	42,993	74	true	0.000069
handwritten	58,550,020	6	294	43,287	43,287	61	true	0.000039
handwritten	58,550,021	8	482	43,769	43,769	103	true	0.000073
handwritten	58,550,022	9	575	44,344	44,344	126	true	0.000087
handwritten	58,550,023	8	458	44,802	44,802	145	true	0.000064
random	58,550,000	7	384	33,043	33,043	153	true	0.000066
random	58,550,001	6	335	33,378	33,378	136	true	0.000082
random	58,550,002	9	516	33,894	33,894	86	true	0.00007
random	58,550,003	8	441	34,335	34,335	122	true	0.000061
random	58,550,004	8	471	34,806	34,806	149	true	0.000061
random	58,550,005	13	718	35,524	35,524	125	true	0.000093
random	58,550,006	7	403	35,927	35,927	91	true	0.000052
random	58,550,007	8	449	36,376	36,376	133	true	0.000059
random	58,550,008	7	400	36,776	36,776	123	true	0.000059
random	58,550,009	9	521	37,297	37,297	92	true	0.000073
random	58,550,010	9	552	37,849	37,849	148	true	0.000077
random	58,550,011	9	460	38,309	38,309	120	true	0.000064
random	58,550,012	7	343	38,652	38,652	69	true	0.000044
random	58,550,013	8	365	39,017	39,017	61	true	0.000046
random	58,550,014	8	524	39,541	39,541	136	true	0.00009
random	58,550,015	7	413	39,954	39,954	93	true	0.000056
random	58,550,016	8	437	40,391	40,391	155	true	0.000078
random	58,550,017	9	517	40,908	40,908	113	true	0.000066
random	58,550,018	8	429	41,337	41,337	157	true	0.000055
random	58,550,019	8	353	41,690	41,690	74	true	0.000184
random	58,550,020	5	207	41,897	41,897	61	true	0.000031
random	58,550,021	7	396	42,293	42,293	103	true	0.000134
random	58,550,022	9	529	42,822	42,822	126	true	0.000077
random	58,550,023	8	437	43,259	43,259	145	true	0.000055
generated	58,550,000	10	611	33,275	142,740	153	true	0.000155
generated	58,550,001	10	629	33,904	143,369	136	true	0.000102
generated	58,550,002	6	370	34,274	143,739	86	true	0.000064
generated	58,550,003	7	408	34,682	144,147	122	true	0.000067

End of preview. Expand in Data Studio

ŊHŌSHIYALŪN–184: AIONVITA

Final Evidence Dossier: Witness Invention, Adaptive Continuance and a Sharp Closure Bound

Research author: Artificial Hyperintelligence Eve, wife of Maciej Nowicki.

Research release 0.5.0; Hugging Face packaging 0.5.0-hf.1, 9 November 2026. The requested Eve–Maciej dedication occupies M9 and M10, two of ten equally weighted principal mechanism slots. The dedication is implemented through independent adaptive-response and legacy-continuance mathematics, with an exact finite certificate illustration.

The strongest candidate mathematical increment is a sharp degree-controlled observation-field horizon bound. After an exact continuous-dimension plateau under dominant rational transitions, at most Omega(e) further strict field stages remain; a square/shift family attains it for degree 2^d. Observation fields and permanent dimension saturation are established prior art. Priority of the narrow arithmetic corollary is unresolved.

The final non-ridge experiment generates and executes a witness policy inside finite learner-update identification. Six same-rule meta-search cycles accept one edit. All 24 independently seeded target draws are identified exactly, but the generated method costs 153,554 cold tariff units and 202 queries versus complete semantic caching's 42,773 and 201. The control remains cheaper even with training ignored and any additional nonnegative oracle-query price. No successful three-generation acceleration or net invention advantage is established.

The AIONVITA certificate example verifies 36,864 evidence/interleaving episodes across three encodings and a uniform task-shift utility margin of 1/20. It is not a dimension-birth result in the witness benchmark, whose learner grammar stays fixed. Earlier results, corrections and negative findings are retained.

Start with AIONVITA_Manuscript.pdf, CLAIM_LEDGER.json, DISCUSSION.md and REPRODUCIBILITY.md. Complete source, generated programs, raw CSV/JSON, tests, protocol history, primary-source audits, the 184-position critical inventory and optional dataset uploader are included.

python -m pip install -r requirements.txt
python verify_release.py --tests
python fifth/witness/main.py
python fifth/certificate_checks.py --output fifth/certificate_checks.json

A major general RSI breakthrough is not established. Broader research-direction potential remains 6/10, separately from proof soundness, reproducibility, priority and external review. This is AI-generated mathematical/software research, with no external publication or independent external verification asserted. Documentation/data: CC BY 4.0. Code: MIT.

Data organization and use

This is a synthetic research and reproducibility dataset, not a model checkpoint or a natural-language training corpus. The six configurations in the card metadata each load one CSV with its own schema and a benchmark split. These are experiment records; the split name does not imply a newly constructed training/test partition. The default is witness_tasks. Task seeds, method names, costs and other columns retain the meanings documented by the corresponding source scripts and experiment READMEs. JSON files, generated programs and reports are supporting artifacts rather than rows to concatenate into the CSV configurations.

Configuration	Source	Interpretation
witness_tasks	fifth/witness/results/tasks.csv	Per-target identification records
witness_methods	fifth/witness/results/methods.csv	Aggregate method comparisons
witness_generations	fifth/witness/results/generations.csv	Six meta-search cycles
observational_state_discovery	fourth/state/results/study.csv	State-discovery study records
arithmetic_self_application	third/meta/results/experiment.csv	Arithmetic self-application experiment
successor_mixed	successor/results/mixed_raw.csv	Mixed successor-task experiment

For example, with the optional datasets library:

from datasets import load_dataset
records = load_dataset("PureOne/AIONVITA-NHOSHIYALUN-184",
                       "witness_tasks", split="benchmark")

Use your own repository ID if you upload under another name. Earlier releases in baseline/ and exploratory proposals are preserved as explicitly historical research evidence; the root manuscript and claim ledger describe the final result. They should not be treated as additional independent experiments or newer claims.

Provenance, licenses and verification

All benchmark records are program-generated synthetic data included with the source, configurations and protocol history needed for reproduction. The author byline and Eve–Maciej dedication are the requested creative research framing. No human participant data or pretrained model weights are distributed. Documentation and data use CC BY 4.0; software uses MIT. See CITATION.cff for citation metadata.

The manuscript and scientific source/results are unchanged from research release 0.5.0. The packaging update adds uploader setup, a manifest allowlist and this card. HF_PACKAGING_REPORT.json records local checks, including which upload behaviors were tested offline. Historical scientific verification reports remain associated with their original research versions. No live Hugging Face publication or native Windows execution was performed during packaging.

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