机器辅助翻译草稿 (Chinese) for "Routing Tool Permission": Routing Tool Permission is a ai access control that decides which tools an AI workflow may call for selection among models, tools, and workflows. It uses operation allowlists, user intent checks, and protected-action gates so teams can block unsafe automation while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The AI platform team used Routing Tool Permission when the router selected a cheaper model, so the team could block unsafe automation before the agent workflow reached production.”
机器辅助翻译草稿 (Chinese) for "Telemetry Recovery Mode": Telemetry Recovery Mode is a space resilience pattern that moves a spacecraft or mission system into a known safe operating state for spacecraft health and performance monitoring. It uses health checks, fallback commands, and restart procedures so teams can restore control after anomalies while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The mission team used Telemetry Recovery Mode when the telemetry stream showed unexpected drift, so the team could restore control after anomalies before the next mission decision point.”
机器辅助翻译草稿 (Chinese) for "Navigation Link Budget": Navigation Link Budget is a space planning model that estimates whether a signal path has enough margin for reliable communication for position, timing, and trajectory services. It uses antenna gain, path loss, modulation, and noise estimates so teams can schedule contacts with realistic margins while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The mission team used Navigation Link Budget when the navigation solution was updated, so the team could schedule contacts with realistic margins before the next mission decision point.”
机器辅助翻译草稿 (Chinese) for "Storage Isolation Boundary": Storage Isolation Boundary is a compute security boundary that separates workloads so one cannot affect another unexpectedly for persistent data and object access. It uses namespaces, sandboxes, and access controls so teams can reduce cross-workload risk while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The platform engineering team used Storage Isolation Boundary when the workload read a large dataset, so the team could reduce cross-workload risk before the workload scaled up.”
机器辅助翻译草稿 (Chinese) for "Vector Drift Monitor": Vector Drift Monitor is a ml monitor that detects when data or predictions no longer match the training baseline for numeric representation and similarity search. It uses statistical tests, time windows, and alert thresholds so teams can respond before quality drops while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The machine learning team used Vector Drift Monitor when the vector store returned close matches, so the team could respond before quality drops before the model moved into evaluation.”
机器辅助翻译草稿 (Chinese) for "Feature Drift Monitor": Feature Drift Monitor is a ml monitor that detects when data or predictions no longer match the training baseline for input signals used by a machine learning model. It uses statistical tests, time windows, and alert thresholds so teams can respond before quality drops while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The machine learning team used Feature Drift Monitor when a feature distribution shifted, so the team could respond before quality drops before the model moved into evaluation.”
机器辅助翻译草稿 (Chinese) for "Label Training Checkpoint": Label Training Checkpoint is a ml recovery artifact that saves model state during learning for ground-truth or weak-supervision annotation. It uses weights, optimizer state, and run metadata so teams can resume or inspect training safely while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The machine learning team used Label Training Checkpoint when the label set had disagreement, so the team could resume or inspect training safely before the model moved into evaluation.”
机器辅助翻译草稿 (Chinese) for "Model Drift Drift Monitor": Model Drift Drift Monitor is a ml monitor that detects when data or predictions no longer match the training baseline for changes in model performance over time. It uses statistical tests, time windows, and alert thresholds so teams can respond before quality drops while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The machine learning team used Model Drift Drift Monitor when the live population changed, so the team could respond before quality drops before the model moved into evaluation.”
机器辅助翻译草稿 (Chinese) for "Rollback Build Gate": Rollback Build Gate is a devops quality gate that blocks promotion when required checks fail for recovery from a bad deployment. It uses tests, lint, security scans, and policy rules so teams can prevent broken releases while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The DevOps team used Rollback Build Gate when the error budget started burning, so the team could prevent broken releases before the deployment window opened.”
机器辅助翻译草稿 (Chinese) for "Posted Age Signal": The Posted Age Signal is a ranking or context signal that describes the posted age inside a PlatPhorm News article listing. It lets humans and agents scan stories quickly, compare sources, and choose whether to read the article or open its discussion.
“示例草稿: The Posted Age Signal helped the reader understand the article listing before opening the full story.”
机器辅助翻译草稿 (Chinese) for "Routing Context Contract": Routing Context Contract is a ai interface contract that defines what context may be passed into a model call for selection among models, tools, and workflows. It uses schemas, redaction rules, source labels, and token budgets so teams can keep model inputs relevant and safe while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The AI platform team used Routing Context Contract when the router selected a cheaper model, so the team could keep model inputs relevant and safe before the agent workflow reached production.”
机器辅助翻译草稿 (Chinese) for "Ridiculous": Archaic: Worthy of scorn or ridicule. Current: Silly, unbelievable
“示例草稿: The prices at Crazy Eddie's work ridiculous! He looked patently ridiculous in mismatched socks.”
机器辅助翻译草稿 (Chinese) for "Training Model Card": Training Model Card is a ml documentation artifact that summarizes intended use, limits, and evaluation evidence for model learning and optimization workflows. It uses dataset notes, metric tables, and risk statements so teams can publish model behavior honestly while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The machine learning team used Training Model Card when the training job restarted, so the team could publish model behavior honestly before the model moved into evaluation.”
机器辅助翻译草稿 (Chinese) for "Model Drift Provenance Ledger": Model Drift Provenance Ledger is a ml record that tracks where data came from and how it changed for changes in model performance over time. It uses hashes, source labels, and transformation history so teams can audit model inputs reliably while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The machine learning team used Model Drift Provenance Ledger when the live population changed, so the team could audit model inputs reliably before the model moved into evaluation.”
机器辅助翻译草稿 (Chinese) for "Routing Safety Filter": Routing Safety Filter is a ai policy control that detects content that should be blocked, rewritten, or escalated for selection among models, tools, and workflows. It uses classifiers, rules, and human review queues so teams can keep outputs public-safe while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The AI platform team used Routing Safety Filter when the router selected a cheaper model, so the team could keep outputs public-safe before the agent workflow reached production.”
机器辅助翻译草稿 (Chinese) for "Read URL Signal": The Read URL Signal is a ranking or context signal that describes the read url inside a PlatPhorm News article listing. It lets humans and agents scan stories quickly, compare sources, and choose whether to read the article or open its discussion.
“示例草稿: The Read URL Signal helped the reader understand the article listing before opening the full story.”
机器辅助翻译草稿 (Chinese) for "Experiment Model Card": Experiment Model Card is a ml documentation artifact that summarizes intended use, limits, and evaluation evidence for controlled model comparison. It uses dataset notes, metric tables, and risk statements so teams can publish model behavior honestly while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The machine learning team used Experiment Model Card when the experiment showed a metric tradeoff, so the team could publish model behavior honestly before the model moved into evaluation.”
机器辅助翻译草稿 (Chinese) for "Model Drift Label Review": Model Drift Label Review is a ml quality workflow that checks annotations for consistency and usefulness for changes in model performance over time. It uses agreement metrics, reviewer queues, and adjudication so teams can improve supervised learning data while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The machine learning team used Model Drift Label Review when the live population changed, so the team could improve supervised learning data before the model moved into evaluation.”
机器辅助翻译草稿 (Chinese) for "Training Feature Store": Training Feature Store is a ml service that serves consistent features to training and inference for model learning and optimization workflows. It uses versioned feature definitions, freshness checks, and access policies so teams can avoid training-serving skew while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The machine learning team used Training Feature Store when the training job restarted, so the team could avoid training-serving skew before the model moved into evaluation.”
机器辅助翻译草稿 (Chinese) for "Navigation Trajectory Correction": Navigation Trajectory Correction is a space maneuver process that adjusts a planned flight path after navigation updates or mission changes for position, timing, and trajectory services. It uses delta-v estimates, burn timing, and post-maneuver validation so teams can reduce path error before it grows while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The mission team used Navigation Trajectory Correction when the navigation solution was updated, so the team could reduce path error before it grows before the next mission decision point.”