'uncertainty' 검색 결과

Draft and revise public replies to questions, bug reports, and community discussions. Use a warm, conversational tone while giving specific explanations, acknowledging uncertainty, asking focused follow-up questions, and making the next action clear.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Replying to a public bug report
• Explaining features or workarounds
• Requesting specific details for an investigation

Rewrite English tool descriptions, error messages, prompts, and agent instructions into clearer sentences using principles from Simplified Technical English. Preserve facts, conditions, and uncertainty, with an optional comparison explaining the rules behind each change.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Clarify English tool descriptions
• Remove ambiguity from instructions between agents
• Rewrite English error messages and status reports

Assess factual claims in AI-generated text by separating facts from opinions, choosing suitable independent evidence, and explaining what is supported or uncertain. Use it for a completed fact-check or an optional exercise in evaluating AI answers.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Fact-checking an AI-generated answer
• Choosing independent sources for a claim
• Identifying unverified numbers and assertions

Compare choices using weighted scores, pros and cons, possible failure scenarios, and what each option means giving up. Make preferences and uncertainty explicit, rank alternatives, and identify information that could change the decision.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Comparing job offers or client projects
• Prioritizing features and experiments
• Exploring failure risks before committing

Prepare scientific figures for journal submission with consistent panel layouts, error bars showing uncertainty, statistical significance labels, and accessible colors. Use matplotlib, seaborn, or plotly to adjust figure dimensions and export publication formats.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Preparing figures for journal submission
• Combining multiple plots with consistent styling
• Making figures readable in color and grayscale

Create statistical charts from tabular data to explore distributions, relationships, and group differences. This skill guides plot selection, multi-panel layouts, and styling, including box plots, heatmaps, and charts with estimates and uncertainty bands.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Exploring data distributions and unusual values
• Comparing measurements across groups
• Visualizing correlations between variables

Compare original and revised text to check whether protected content survived editing. It combines a bundled validator for structural checks with a separate meaning review, then reports errors, warnings, and specific repair targets.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking quotes and code after a rewrite
• Comparing links, numbers, and headings before and after editing
• Reviewing changes to meaning, conditions, and uncertainty

Interpret AI-writing flags without treating them as proof of authorship. Separate tool results from editorial observations, consider plausible human explanations, and identify drafts, revision histories, or other process evidence needed for consequential academic, hiring, or publication decisions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Understand what AI-writing flags actually establish
• Consider false positives in second-language or technical writing
• Review detector evidence for academic or hiring decisions

Audit causal inference in a sewage and house prices study by comparing manuscript claims with R code. Review design assumptions, statistical uncertainty, and robustness, then produce a prioritized report with concrete fixes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Comparing manuscript methods with R analysis code
• Auditing assumptions behind causal inference
• Checking standard errors and multiple testing

Evaluate research papers and scientific claims by examining study design, statistics, bias, and evidence quality. Receive a structured critique of strengths, weaknesses, supported conclusions, and practical improvements, with uncertainty and limitations made explicit.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing a paper's methods and conclusions
• Assessing evidence quality across studies
• Checking scientific claims in media reports

Estimate how an intervention affects outcomes using Bayesian causal analysis. The workflow confirms causal assumptions with the user, selects a suitable method, checks whether findings withstand challenges, and reports effects with uncertainty and limitations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Estimating the effect of a policy or intervention
• Mapping causal relationships before analysis
• Selecting a method for observational data

Estimate software development effort by breaking requirements into tasks and choosing three-point estimates, relative T-shirt sizes, or function points that measure functional scope. Produce workload reports with uncertainty ranges and relevant risk adjustments.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Rough effort estimates during early project planning
• Task estimation for sprint planning
• Effort breakdowns for client quotes

Keep implementation work moving by turning routine uncertainty into explicit assumptions. The agent follows existing project patterns, makes small reversible changes, validates results, and reports its decisions, completed changes, checks, and remaining risks.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Continue implementation while away
• Reduce routine clarification stops
• Review autonomous decisions and validation results

Turn a rough request into a structured AI prompt with a clear goal, output format, and constraints. For complex work, add smaller tasks, separate creator and reviewer roles, and explicit checks for accuracy and uncertainty.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Refining a vague AI request
• Designing prompts for API documentation
• Adding verification steps to code generation

Request an independent code review using GPT-6.1-Sol at Max reasoning through Codex and Cloudroom. Review the current environment, including uncommitted changes, and return the completed reviewer’s full response covering serious issues and readiness to merge.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Get an independent review before merging
• Review changes that are still uncommitted
• Check serious issues across related code and tests

Collect public evidence about a person, company, or topic with DeepAPI and save it as a structured JSON dossier. Source links, uncertainty checks, and coverage notes show what was found and what remains missing.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Researching a sales prospect
• Collecting evidence about a software vendor
• Organizing documentation and discussions on a technical topic

Prepare research data figures for journal submission with consistent layouts, error bars showing uncertainty, and accessible colors. Adjust figure dimensions, typography, resolution, and export formats using matplotlib, seaborn, and plotly.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Preparing figures for journal submission
• Combining multiple plots into one consistent figure
• Improving color and grayscale readability

Work through information theory problems involving entropy, a measure of uncertainty. Provides formulas, properties, and calculation examples for discrete and continuous distributions, joint and conditional entropy, and choosing distributions through the maximum entropy principle.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Calculating Shannon entropy from a probability distribution
• Working through joint and conditional entropy problems
• Calculating differential entropy for continuous distributions

Investigate firsthand sources before making a judgment or recommendation. Separate verified facts, reasoned inferences, and unknowns, document their sources, and produce a conclusion that explains the current situation, constraints, and remaining uncertainty.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Understand an unfamiliar codebase or system
• Gather evidence before making a decision
• Check when a proposed approach actually applies

Guides statistical analysis in Python, including regression, time series forecasting, and hypothesis tests. Helps interpret estimates and uncertainty, check model assumptions, investigate influential observations, compare models, and produce statistical tables for reporting.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Interpreting regression coefficients and confidence intervals
• Forecasting time series with prediction intervals
• Checking model assumptions and influential observations

Analyze research data with suitable statistical tests, regression, correlation, or Bayesian methods. Check assumptions, estimate effect sizes and uncertainty, plan sample sizes, and prepare figures, tables, and reports following APA academic reporting conventions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing statistical tests for research data
• Checking analysis assumptions and alternative methods
• Estimating sample sizes before collecting data

Forecast sales, sensor readings, and other single-variable time series with Google's TimesFM, without training a custom model. Accept CSV files, DataFrames, or arrays and obtain forecast values with prediction intervals that express uncertainty.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Forecast monthly sales from a CSV file
• Forecast demand across multiple stores
• Plot sensor forecasts with prediction intervals

Create scientific plots for manuscripts with consistent layouts, accessible colors, and error bars showing uncertainty. Use matplotlib, seaborn, or plotly to prepare multi-panel figures and export files with publication-specific sizes and resolution.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Prepare figures for journal submission
• Arrange multiple plots with consistent styling
• Improve color and grayscale readability

Turn analytical findings into reports and presentations that explain what the numbers mean and what to do next. Structure the narrative, choose clear visual comparisons, highlight key findings, and communicate uncertainty to audiences without technical expertise.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Present key findings to executives
• Build quarterly business review reports
• Explain analytical results to nontechnical audiences