Robotics Bottleneck Research机器人瓶颈研究

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CE-N: how the bottlenecks are scoredCE-N:瓶颈如何评分

The inputs, calculation, and limitations behind the current research ranking.

当前研究排名的输入、计算方式与局限。

  • RESEARCH CUT heatmap 2026-08-12 / landscape 2026-08-13研究截点 heatmap 2026-08-12 / landscape 2026-08-13

CE-N compares the eighteen bottlenecks using three research judgments: whether customers have budgets, whether a solution is feasible, and whether suppliers can retain value. The score expresses a research priority. It does not measure a company’s return on invested capital or expected stock return.

Six ratings, three calculation inputs

The current records use a 1–5 scale. Higher values indicate more of the property described, not equal units of economic value.

AxisQuestionCurrent rangeCalculation role
BudgetIs there an identified buyer with money available to spend?3.5–5.0One third of the standardized composite
SolvabilityCan the task be solved reliably under its intended conditions?2.6–4.2One third of the standardized composite
Value captureCan the supplier retain economic value after costs and competition?3.4–4.8One third of the standardized composite
MaturityHow established are the technology and deployments?2.0–4.0Context
PainHow costly or consequential is the customer’s problem?4.0–5.0Context
TimingWhat makes adoption feasible or urgent in the stated period?4.1–5.0Context

What supports an input rating?

The bottleneck pages describe the research reasoning and show the stored ratings. The current records do not provide a complete, source-linked rubric explaining every decimal rating. A value such as 4.1 should therefore be read as an analyst judgment with unresolved measurement precision, rather than an observed physical quantity.

The scoring review sets out the evidence requirements and rating anchors approved for the pilot. Replacement ratings still require approval. Each bottleneck’s score panel makes the remaining evidence requirements visible.

Why Pain, Timing, and Maturity remain context

The current calculation excludes these three axes. Pain and Timing cluster toward the high end of the scale, but that alone does not demonstrate that they contain no useful information. Selection of already-important bottlenecks, overlapping definitions, or insufficiently specific rating anchors could explain the clustering.

Maturity describes progress already achieved. Whether it adds useful information beyond Solvability is also a review question. We keep the current calculation unchanged while examining these issues.

The calculation behind the stored scores

The documented v0.2 calculation uses the following steps:

  1. Cap each of the three input axes at its 10th and 90th percentiles across the eighteen problems.
  2. Subtract the axis mean and divide by its population standard deviation. A constant axis contributes zero.
  3. Average the three standardized values with equal weights.
  4. Map the composite to 0–100 using (composite + 3) / 6 × 100, clipped to that range.
  5. Multiply by 0.85 if any of the three raw input ratings is below 2.5, then round to one decimal place.

A read-only audit reproduced all eighteen stored scores using this rule. The website displays the current approved score; historical calculations and candidate comparisons remain in the source repository.

A worked example

For P18, Vertical workflow ROI, the stored inputs are Budget 5.0, Solvability 4.1, and Value capture 4.8. Applying the calculation to the full board produces the stored CE-N score of 71.2.

The full board is needed because the percentile cutoffs, means, and standard deviations depend on all eighteen records. A change to one record can affect other records’ scores. Fixed 0–100 endpoints do not make scores from different research cuts directly comparable when the reference distribution changes.

The audit script and input hashes accompany this revision in tools/research-review and operations/reviews of the source repository. The review page explains the evidence and rating rules.

From a score to a portfolio

Company valuation, eligibility, and position sizing are separate steps. The website displays one current approved CE-N score. Internal evidence-confidence analysis is not displayed as a second CE-N score; this presentation rule does not change portfolio calculations.

CE-N 根据三项研究判断比较十八个瓶颈:客户是否有预算、解决方案是否可行、供应商能否保留价值。分数表达研究优先级,不衡量公司的投入资本回报率或股票预期回报。

六项评级,三项进入计算

当前条目采用 1–5 分。数值越高表示所描述属性越强,不代表相同单位的经济价值。

维度问题当前范围计算作用
预算是否有明确买方与可用预算?3.5–5.0标准化合成值的三分之一
可解性能否在预期条件下可靠完成任务?2.6–4.2标准化合成值的三分之一
价值获取扣除成本并考虑竞争后,供应商能否保留经济价值?3.4–4.8标准化合成值的三分之一
成熟度技术与部署已经发展到什么程度?2.0–4.0背景信息
痛点客户的问题造成多大成本或影响?4.0–5.0背景信息
时机在明确期间内,什么因素促成或推动采用?4.1–5.0背景信息

输入评级依据是什么?

瓶颈页解释研究判断并展示已存储评级。当前条目尚未提供完整、逐项关联来源的量表,不能解释每一个小数评级。因此,4.1 这样的数值应视为精度仍待论证的分析判断,而非直接测得的物理量。

评分评审说明试点采用的证据要求与评级基准。替换评分仍需批准。各瓶颈的评分面板会说明尚缺哪些证据要求。

为什么痛点、时机与成熟度仍作为背景

当前计算不纳入这三项。痛点与时机集中在量表高端,但这本身不能证明它们不含有用信息。选择的瓶颈原本就重要、定义重叠,或评级基准不够具体,都可能造成这种集中。

成熟度描述已经取得的进展。它能否在可解性之外提供额外信息,也需要评审。在检验这些问题期间,当前计算保持不变。

已存储分数的计算方式

已记录的 v0.2 计算采用以下步骤:

  1. 在十八个问题中,将三项输入分别限制在该维度的第 10 与第 90 百分位。
  2. 减去该维度均值,再除以总体标准差。若整列为常数,该维度贡献为零。
  3. 以相同权重平均三项标准化值。
  4. 用 (合成值 + 3) / 6 × 100 映射至 0–100,并限制在该区间内。
  5. 若三项原始输入中任一项低于 2.5,将结果乘以 0.85,最后保留一位小数。

只读审计已复现全部十八个已存储评分。网站展示当前已批准分数;历史计算与候选比较保留在源代码仓库。

一个计算例子

P18,垂直工作流 ROI的已存储输入为预算 5.0、可解性 4.1、价值获取 4.8。对整张评分表应用上述计算,得到已存储的 CE-N 71.2。

计算需要完整评分表,因为百分位、均值与标准差取决于全部十八个条目。一个条目的变化可能影响其他条目。0–100 端点固定,并不意味着参照分布变化后,不同研究截点的分数仍可直接比较。

证据与评分规则说明评估要求。审计材料与历史比较保存在源代码仓库。

从分数到组合

公司估值、资格与仓位配置是独立步骤。网站展示一个当前已批准的 CE-N 分数;证据置信度的内部分析不会以第二个 CE-N 分数展示,也不会因此改变组合计算。