I have taken the bold step of removing the ugly Overly detailed|section (dated July 2024} tag as it was not me clear what was being asked for and the section
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I have taken the bold step of removing the ugly Overly detailed|section (dated July 2024} tag as it was not me clear what was being asked for and the section seemed to me fine. The tag itself was adding to the reading problem that might lead to the problem suggested. Perhaps some more specific suggestions here could help. Msrasnw (talk) 14:39, 23 July 2025 (UTC)
I would argue if "only" is appropriate in this context. Usually these tests are not symmetric in this way, so we don't expect really that if our assumptions are false, the negated null hypothesis will just as easily give significantly important data in favour of it being not true. The most basic example is showing linear correlation. The contrary is pretty much impossible to significantly proof, as variables correlated with ratio are linearly correlated, and indistinguishable in practice. Previously we were trying to show that ρ just is not equal to zero, so exclude one case, designing the experiment to expose |ρ| being big enough to make significant difference. But to show that there is no correlation it is not enough to expose |ρ| as small, there is just no positive ε small enough small enough to |ρ|<ε showing lack of linear correlation significantly, and the exact answer usually has probability 0. This asymmetry is not related to this particular statistic ρ (the same applies for any testing if point lies outside compact subset, which is much easier than outside open subspace if the data lie around point from its closure) but is something to be expected in every study. It might be less extreme, but there is a reason for using experimental methods very often to show that some random variable is bigger than second (for example that ordinary running is on average faster than running while juggling at the same time) and we don't just do the same with null hyppothesis reversed where we expect that there is no real difference between them.
The 0.25 success rate stated as that do not mean it is low and it may as well extremely large ~SpectralFlux 04:51, 7 August 2025 (UTC)
| This edit request by an editor with a conflict of interest was declined. |
Hi, I represent Google DeepMind and am requesting an addition to provide the outcome of Nature's investigation into the 2021 chip design paper discussed in this section. Requested changes:==Addition of Nature investigation outcome==Current text ends with:"...A fraction of evidence reviewed in the critique is summarized below using prior terminology.[142]" Proposed addition (new sentence immediately following):"Following an 18-month investigation into these concerns, Nature published an addendum in September 2024 that upheld the original paper's methodology and findings.[1]" Rationale: The current text describes the criticism and Nature's investigation but does not include the outcome of that investigation. Since the section documents concerns about replicability, it's important for completeness to note that the journal concluded its formal review process. This addition maintains the documentation of the criticism while providing readers with the full timeline of events.
References
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Ag77777 (talk) 18:57, 15 October 2025 (UTC)
| This edit request by an editor with a conflict of interest was declined. |
Hi, I represent AlphaChip and am requesting an addition to provide context about data availability and Nature's investigation outcome in the Data Leakage section. Requested changes:==Addition of context to AlphaChip data leakage discussion==Current text ends with:"...underscored the need for transparent, reproducible benchmarks and rigorous evaluation standards to ensure genuine progress in the field of electronic design automation." Proposed addition (new sentence immediately following):"Google subsequently released open-source code and training data for the AlphaChip methodology,[1] and Nature's 18-month investigation concluded in September 2024 with an addendum upholding the paper's methodology.[2] However, some researchers have maintained concerns about comparative performance claims." Rationale: The current text discusses reproducibility concerns but does not mention that Google released the code/data or that Nature's investigation upheld the methodology. Since this section is specifically about data leakage and reproducibility, noting that data was made available and that the journal's investigation found in favor of the paper is directly relevant. The final sentence acknowledges ongoing debate while providing readers with complete information.
References
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{{cite journal}}: Check |url= value (help); Missing or empty |title= (help)
Ag77777 (talk) 19:09, 15 October 2025 (UTC)
References
Youyou W, Yang Y, Uzzi B. A discipline-wide investigation of the replicability of Psychology papers over the past two decades. Proc Natl Acad Sci U S A. 2023 Feb 7;120(6):e2208863120. doi: 10.1073/pnas.2208863120. Epub 2023 Jan 30. PMID: 36716367; PMCID: PMC9963456.
should be added as an up to date overview - also, during my research on the topic it seems that pychology is in fact exceptionally affected compared to other social sciences, contradicting the washington post article from 2015 FrenziedStargrime (talk) 14:44, 16 November 2025 (UTC)
Wouldn't it be more accurate to say
Replication failures do not NECESSARILY indicate that affected fields lack scientific rigor.
be more accurate than the current text that states
Replication failures do not indicate that affected fields lack scientific rigor.
since it seems that replication failures could be an indicator of less-than-careful practices? Dvdtoy (talk) 01:00, 11 January 2026 (UTC)
It's kind of unfair to not mention Jupyter Notebooks here. Miklevin (talk) 11:43, 14 April 2026 (UTC)
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