Board Position
#7 · AI coding still leads, while agent products are starting to break out.
reasoning-models is currently ranked #7 on the Momentum board. First time on the board. Active window: 24h.
Score72
Confidence78%
Surge+9%
Sourcesgithub
NEW
Reading Flow
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Tool Detail
reasoning-models
AI Coding
reasoning-models
Experiments with reasoning models, training techniques, papers
AI CodingGitHubbenchmarkscotdeepseekgithub
reasoning-models appears on 2 boards right now, with the primary position at #7 on Momentum.
This signal is supported by GitHub, spanning 1 source directions.
The system has tracked this tool for 4 runs, first seen Jun 19, 20:11 and most recently updated Oct 15, 20:24.
Score72
Weekly growth+9%
Confidence78%
Primary statusMomentum #7
NEW · First time on the board
Discovery statusWatchlist
Pool score 75, based on 1 contributing sources.
Tracked runs4
First seen Jun 19, 20:11, last updated Oct 15, 20:24.
Source coverage1
GitHub
7-day score trend
GitHub signals are derived from stars, forks, watchers, and recent activity.7-day rank movement
Lower numbers are closer to the top#3D1
#3D2
#3D3
#3D4
#5D5
#4D6
#7D7
Signal summary
reasoning-models appears on 2 boards right now, with the primary position at #7 on Momentum.
This signal is supported by GitHub, spanning 1 source directions.
The system has tracked this tool for 4 runs, first seen Jun 19, 20:11 and most recently updated Oct 15, 20:24.
Discovery assessment
Discovery originPrimary provider
1 sources contributed to the candidate judgement.
Candidate typeProduct candidate
Currently in the Watchlist stage.
Quality score76
Higher scores usually indicate a real product rather than editorial or noisy content.
Manual ruleAutomatic
No manual rule is active, so the system judgement is still automatic.
Includes product-like sources
System judgement
This section shows how source page evidence, multi-run stability, and auto-promotion logic are combined into the candidate judgement.
Source page evidence+4
1 matched
Stability3 consecutive runs
watchlist 3 · ranked 1 · strong 3
Recent snapshotBest 90
Last seen Jul 30, 17:59
Board footprint
Momentum#7
NEWFirst time on the board
Score 72Confidence 78%Surge +9%
Newcomers#4
NEWFirst time on the board
Score 72Confidence 78%Surge +9%
Why it matters now
- GitHub is showing a clear upward signal and is worth adding to the watchlist first.
- Current category: AI Coding. A good fit for the watchlist.
- Current board score: 72. A useful starting point for the next round of real-data validation.
What could make it noisy
- The signal still mainly comes from a single source, so more cross-validation is recommended.
- This is still a short-window snapshot and lacks longer-term real history.
Source timeline
2026-10-15 20:24
Source page evidence
This panel aggregates source pages the system has already fetched and cached, so you can judge whether the tool points to a real product site, an editorial page, or just a seed domain.
Cached pages1
Total number of fetched pages that are currently available to display.
Successful pages1
Pages fetched successfully with a readable title and summary.
Failed / stale0 / 0
Failed pages will be retried, and stale pages will be refreshed in later syncs.
Domains covered1
Broader domain overlap usually suggests the signal is not just isolated noise.
Status filter
Showing 1 / 1 pages
Sorted by fetch success, freshness, and summary richnessHigh value · 1
High-value hitLinked signalFetch successRich summary
GitHub - benjaminzwhite/reasoning-models: Experiments with reasoning models, training techniques, papers
Experiments with reasoning models, training techniques, papers - benjaminzwhite/reasoning-models
https://github.com/benjaminzwhite/reasoning-modelsOct 15, 20:24
FetchedGitHubgithub.comHTTP 200
Why it is prioritized
The fetch succeeded and the cache is still fresh, which makes this page a strong signal for judging whether the product is active and real.
This evidence is already linked to a raw signal record, so you can continue tracing the source from the signal detail page.
Raw signals
GitHubNewcomers #4
Oct 15, 20:24Experiments with reasoning models, training techniques, papers
GitHubbenchmarkscot
GitHubMomentum #7
Oct 15, 20:24Experiments with reasoning models, training techniques, papers
GitHubbenchmarkscot
GitHubDurable Growth #4
Jul 30, 17:59Experiments with reasoning models, training techniques, papers
GitHubbenchmarkscot
GitHubNewcomers #2
Jul 30, 17:59Experiments with reasoning models, training techniques, papers
GitHubbenchmarkscot
GitHubMomentum #4
Jul 30, 17:59Experiments with reasoning models, training techniques, papers
GitHubbenchmarkscot
GitHubNewcomers #2
Jul 30, 16:58Experiments with reasoning models, training techniques, papers
GitHubbenchmarkscot
GitHubMomentum #5
Jul 30, 16:58Experiments with reasoning models, training techniques, papers
GitHubbenchmarkscot
GitHubNewcomers #1
Jun 19, 20:11Experiments with reasoning models, training techniques, papers
GitHubbenchmarkscot
GitHubMomentum #3
Jun 19, 20:11Experiments with reasoning models, training techniques, papers
GitHubbenchmarkscot
Continue reading
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