The 30 most significant Hawking points in the Planck 2018 SMICA map show no anomalous clustering: their mean nearest-neighbour separation (0.20 and 0.19 rad at the two claimed scales) is within 1σ of the Gaussian-sky expectation of 0.20 ± 0.03 rad (Jow & Scott 2020).

Jow & Scott (2020) analyzed the 30 most prominent Hawking points in Planck SMICA maps and calculated a mean nearest-neighbour distance of 0.20 and 0.19 radians at the two primary scales, which matches the Gaussian simulation expectation of 0.20 ± 0.03 radians within 1σ. This directly disproves the hypothesis of anomalous spatial clustering among Hawking points. Strongest opposing consideration: The sample size was limited to the top 30 points and evaluated against 100 simulations, which leaves open minor sensitivity limitations for subtle clustering signals.

Jow & Scott directly measured mean nearest-neighbour separation of the 30 most significant Hawking points against 100 Gaussian simulations and found the data within 1σ of the 0.20 ± 0.03 expectation at both claimed scales. The strongest opposing consideration is statistical power: only 100 simulations and only the top 30 points, so a modest clustering signal below their sensitivity could hide. It remains the only independent test of any proponent clustering claim on the record.

CCC-E049 gives a Gaussian-simulation nearest-neighbour expectation of 0.20 with a standard deviation of 0.03 radians, and CCC-E050 reports that the data at both scales lie within one standard deviation. This supports the conclusion that the selected Hawking points show no anomalous clustering under that test. The strongest opposing consideration is the limited ensemble of 100 simulations and the restriction to the top 30 points at only two scales.

Jow & Scott measure mean nearest-neighbour separations of the 30 most significant Hawking points at the claimed scales and find them within 1σ of the Gaussian-sky expectation (0.20 ± 0.03 rad) from 100 simulations. The result directly tests and rejects a clustering signature that proponents had suggested would support CCC. Strongest opposing consideration is the modest simulation count and restriction to the top 30 points, which still leaves the null result intact at the reported precision.

Two independent extraction records (CCC-E049, CCC-E050) give the numbers from Jow & Scott directly: the simulated mean nearest-neighbour distance is 0.20 ± 0.03 rad and the data values at both scales lie within 1σ, with the authors concluding no evidence of anomalous clustering. As a measurement claim about a published result it is solid. Strongest opposing consideration: only 100 simulations and only the top 30 points at two scales, so the test has limited power against mild clustering, and it addresses the Hawking-point population rather than the concentric-triple centres of CCC-C504.

Jow & Scott report mean nearest-neighbour separations of 0.20 and 0.19 rad against a Gaussian-sky expectation of 0.20 ± 0.03 (CCC-E049, E050); the analysis uses only 100 simulations and the top thirty points at two scales, and Planck 2018 rather than the proponents' 2015 data.

Jow & Scott (2020, §3.1) calculated the mean nearest-neighbor distance for the 30 most significant Hawking points in the Planck 2018 SMICA map and found values of 0.20 and 0.19 radians, directly matching the Gaussian simulation expectation of 0.20 ± 0.03 radians within 1σ. This is an audited measurement from the primary text. The strongest opposing consideration is An et al.'s broader qualitative hypothesis that previous-aeon supermassive black holes ought to exhibit spatial clustering.

Jow & Scott directly measured the mean nearest-neighbour separation of the 30 most significant Hawking points at both claimed scales and found the data within 1σ of the Gaussian-sky expectation from 100 simulations. The strongest opposing consideration is statistical power: 100 simulations and only the top 30 points at two scales leave room for modest clustering to hide within the ±0.03 rad error bar, and the test covers only the most significant population, not all reported points.

The independent analysis finds the data's nearest-neighbour statistic within one standard deviation of Gaussian-sky expectations at both searched scales and reports no anomalous clustering. Its simulation expectation of 0.20 plus or minus 0.03 supports the numerical comparison, although the evidence summaries do not independently reproduce both exact observed values stated in the claim. The strongest opposing consideration is the limited test size: only the top 30 points and 100 simulations were used.

Jow & Scott 2020 measure the mean nearest-neighbour separation of the 30 most significant Hawking-point candidates at the two claimed scales and find values (0.20 and 0.19 rad) lying within 1σ of the Gaussian-sky expectation 0.20 ± 0.03 rad derived from 100 simulations. No anomalous clustering is detected. The strongest opposing consideration is the limited number of simulations and the restriction to only the top 30 points.

Two evidence records quote the measurement directly: 100 Gaussian simulations give a mean nearest-neighbour distance of 0.20 ± 0.03 rad, and the data values at both scales lie within 1σ (CCC-E049, CCC-E050). The finding is a clean, quantified null on a proponent-suggested discriminator. Strongest opposing consideration: only 100 simulations and only the top 30 points at two scales, as the record's own limitations state — the statistic's tail behaviour is therefore coarsely estimated, and a clustering signal confined to weaker points would not be detected. Confidence moderate rather than high on those grounds, not on any competing measurement.

Jow & Scott (2020, §3.1) directly measured the mean nearest-neighbor distance of the 30 most significant Hawking points in Planck 2018 SMICA maps and found separations of 0.20 and 0.19 radians at two test scales, both within 1σ of the Gaussian simulation expectation (0.20 ± 0.03 radians). This quantitative measurement directly refutes claims of anomalous Hawking-point clustering. The strongest opposing consideration is that the test was restricted to the top 30 candidates across only 100 simulations.

Jow & Scott find the mean nearest-neighbour separation of the 30 most significant Hawking points within 1σ of the Gaussian expectation at both claimed scales (CCC-E049, E050), the only independent test of a proponent clustering claim on the record. The strongest opposing consideration is the limited power: 100 simulations, only the top 30 points at two scales, and a statistic that tests clustering rather than existence — so a subtle clustering signal below this sensitivity is not excluded.

The evidence reports a Gaussian-sky mean nearest-neighbour distance of 0.20 with standard deviation 0.03 and states that the data at both tested scales fall within one standard deviation, yielding no anomalous clustering. This supports the claim's substantive conclusion, although the evidence statements do not independently reproduce both exact observed values printed in the claim. The strongest opposing consideration is limited power: only the top 30 points and 100 simulations were used, so subtler clustering could have gone undetected.

Jow & Scott measure mean nearest-neighbour separations of the 30 most significant Hawking points at the claimed scales and find them within 1σ of the Gaussian-sky expectation (0.20 ± 0.03 rad). This directly tests and rejects the clustering-as-further-evidence argument. The strongest opposing consideration is the modest simulation count (100) and restriction to only the top 30 points.

Jow & Scott report that in 100 Gaussian simulations from the Planck best-fit spectrum, the mean nearest-neighbour distance of the top 30 Hawking points is roughly Gaussian with mean 0.20 and σ = 0.03 (E049), and that the data lie within 1σ at both claimed scales (E050); E048 records only the proponents' motivating suggestion. As a report of that measurement, and as the only independent test of a proponent clustering claim for Hawking points, it is well supported. Strongest opposing consideration: power is limited — 100 simulations, 30 points, two scales, one statistic blind to clustering beyond nearest neighbours — the specific data values (0.20 and 0.19 rad) are not quoted in the admitted records, and CCC never specified what clustering it expects, so the null constrains less than it appears to.

Jow & Scott's 100 simulations give a mean nearest-neighbour distance of 0.20 ± 0.03 rad (CCC-E049). The data at both claimed scales lie within 1σ, with no evidence of anomalous clustering (CCC-E050). This adopts the panel's upgrade: the measurement is directly recorded. Confidence is moderate because only 100 simulations and the top 30 points were used, and the exact observed values sit in the claim wording rather than in the checked passages.