Supervisor Progress-Update Brief — bilingual script
导师进度汇报双语逐字稿
Follow-up meeting after the v1.0.0 hardening pass on 2026-05-11.
Walk-through order is unchanged: dataset → model → app → next steps.
Open this file on screen during the meeting; do not read word-for-word.
紧接 2026-05-11 v1.0.0 强化提交之后的进度汇报会议。
顺序一律不变：dataset → model → app → 下一步。
开会时屏幕上打开本文档，不要照念，当兜底用即可。
0. What you need to do — three time windows
0. 你要做的事 —— 三个时间窗口
0.1 Before the meeting (T-15 min) / 会前 15 分钟
| ☐ |
English |
中文 |
| ☐ |
Charge laptop ≥ 80 %; charger in bag. |
笔记本充满 ≥ 80%，充电器带上。 |
| ☐ |
cd ~/Projects/microclimate-x && git pull && git status — must print "working tree clean". |
拉最新代码，确认 working tree clean。 |
| ☐ |
make run in terminal A (leave it running). |
终端 A 起后端，不要关。 |
| ☐ |
curl -s http://localhost:8000/api/health | python3 -m json.tool in terminal B — verify "ml_loaded": true. |
终端 B 验证健康检查，ml_loaded 必须为 true。 |
| ☐ |
Open the 10 browser tabs in the order from docs/MEETING_CHEAT_SHEET.md §0 — app tab is last. |
按 cheat-sheet §0 顺序开 10 个标签页，app 标签放最后。 |
| ☐ |
This file (docs/progress_update_brief.md) open on a separate screen / phone. |
把本文档单独开在副屏或手机上。 |
| ☐ |
Phone on silent. Deep breath. |
手机静音，深呼吸。 |
0.2 During the meeting (≈ 8 minutes) / 会中 ≈ 8 分钟
| Block |
EN heading |
中文标题 |
Time |
| 1 |
Opening 30 s |
开场 30 秒 |
0:00 → 0:30 |
| 2 |
What changed since last meeting |
自上次会以来的进展 |
0:30 → 2:00 |
| 3 |
Live demo — dataset → model → app |
现场演示（顺序不变） |
2:00 → 5:00 |
| 4 |
Next steps for Chapter 5 |
Chapter 5 下一步 |
5:00 → 6:30 |
| 5 |
Asks + closing |
请示 + 收尾 |
6:30 → 8:00 |
0.3 After the meeting (T+24 h) / 会后 24 小时内
| ☐ |
English |
中文 |
| ☐ |
Write meeting minutes — capture every supervisor decision in docs/meeting_log_<date>.md. |
写会议纪要，把老师每条决定记到 docs/meeting_log_<日期>.md。 |
| ☐ |
Open one GitHub issue per agreed action item (label: chapter-5). |
每个 action item 在 GitHub 开一个 issue，打 chapter-5 标签。 |
| ☐ |
Email a 3-bullet summary back to the supervisor for written confirmation. |
给老师发 3 条要点的总结邮件，留书面确认。 |
| ☐ |
Update README.md §9 Roadmap — tick boxes that were signed off. |
更新 README.md 第 9 节 Roadmap，把通过的项打勾。 |
| ☐ |
Tag a new release if scope was confirmed (git tag v1.1.0-rc.1). |
如果范围确认了，打个新 tag (v1.1.0-rc.1)。 |
1. Opening 30 seconds / 开场 30 秒
| English (say this) |
中文（口头要点） |
| "Sir, thank you for your time. Following up on our last session, I've completed a production-grade hardening pass — version 1.0.0 — and the full pipeline is now reproducible end-to-end. May I walk you through what's new in the same order as before — dataset, then model, then app — and finish with my proposed plan for Chapter 5?" |
"老师感谢您抽时间。接着上次的内容，我做完了v1.0.0 工程化强化，整条流水线现在可以端到端复现。我按上次的顺序——dataset、model、app——给您过一遍新的进展，最后讲我对 Chapter 5 的下一步计划，可以吗？" |
Why this opening: it (a) restates the supervisor's preferred process order without him asking, (b) signals you've made forward progress not just polish, and (c) ends with an explicit ask for direction on Chapter 5 — which is what he wants to talk about.
为什么这样开场：(a) 不用他提就主动按他的流程顺序；(b) 强调是前进了而不是只在抛光；(c) 用对 Chapter 5 的请示收尾，这正是他想聊的话题。
2. What changed since the last meeting / 自上次会议以来的进展
~ 90 seconds. Stay on the GitHub repo tab — point to the commit history,
the green CI badge, the v1.0.0 release.
≈ 90 秒。停在 GitHub repo 标签页，指给老师看 commit 历史、CI 绿勾、v1.0.0 release。
| Area |
English |
中文 |
| Backend hardening |
"I added a request-ID middleware, a typed ErrorResponse contract so no bare HTML 500s leak, structured logging, and an enriched /api/health exposing uptime, cache stats, and the loaded ML feature schema." |
"后端我加了 request-ID 中间件、类型化错误协议 ErrorResponse（不再泄漏裸 HTML 500）、结构化日志、以及**升级版 /api/health**（暴露 uptime、缓存统计、ML 特征 schema）。" |
| ML pipeline |
"I shipped scripts/4_evaluate_model.py which produces six publication-quality figures plus a machine-readable evaluation_summary.json. I also wrote a HuggingFace-style MODEL_CARD.md covering intended use, training data, metrics, limitations, and ethical considerations." |
"ML 流水线加了 评估脚本 scripts/4_evaluate_model.py，自动出 6 张论文级别图 + 一份 evaluation_summary.json。还写了 HuggingFace 风格的 MODEL_CARD.md，覆盖用途、训练数据、指标、局限、伦理考量。" |
| Tests + CI |
"Total tests went from 19 to 70, backend coverage is 97 %. CI runs on Python 3.9 / 3.11 / 3.12 plus a Docker image-build smoke test." |
"测试数从 19 涨到 70，**后端覆盖率 97%**。CI 跑 Python 3.9/3.11/3.12 矩阵，外加 Docker 镜像构建烟测。" |
| Dev-ex |
"Multi-stage Dockerfile, docker-compose, Makefile single-word recipes, pre-commit hooks. The whole project is now docker compose up --build away from a clean machine." |
"多阶段 Dockerfile + compose + Makefile 单词命令 + pre-commit hooks。新机器一句 docker compose up --build 就能跑起来。" |
| Documentation |
"Three new docs — architecture.md, thresholds.md with citations for every Veto threshold, and pipeline_order.md which explicitly enforces the dataset → model → app order you asked for." |
"三份新文档——architecture.md、thresholds.md（每个 Veto 阈值都附学术引用）、以及 pipeline_order.md（显式按您要求的 dataset→model→app 顺序写死）。" |
Artefact to show: the GitHub commit history page; the green CI badge on the README; CHANGELOG.md v1.0.0 entry.
展示物：GitHub commit 历史页；README 上的 CI 绿勾；CHANGELOG.md 中 v1.0.0 那一段。
3. Live demo — dataset → model → app / 现场演示（顺序不变）
~ 3 minutes. Same order as the 5/11 dry-run script — no surprises for the supervisor.
≈ 3 分钟。跟 5/11 的脚本完全一样的顺序，老师不会被打乱节奏。
3.1 Dataset (Tab docs/dataset.md) — 30 s
| EN |
中文 |
"Same dataset as last time — ERA5 reanalysis, 5 Malaysian mountain sites, 175 315 hourly rows. The Y column is_rain_event is derived in one line and documented in §5. No change here, just confirming the foundation is unchanged." |
"数据集跟上次一样——ERA5 再分析、马来西亚 5 个山地点位、17.5 万行小时数据。Y 列 is_rain_event 一行代码构造，文档在 §5。这里没有变，只是确认地基没动。" |
3.2 Model (Tabs 01_roc_curve.png → 03_calibration_curve.png → 04_threshold_sweep.png → 05_feature_importance.png) — 90 s
| EN |
中文 |
"Same model as last time — Random Forest, time-based split, τ = 0.20. Test ROC AUC 0.871, PR AP 0.750, Brier 0.138, recall 93.4 %. What's new is the 6 figures plus the model card — every number you see here is reproducible from make evaluate." |
"模型跟上次一样——RF、时间序列切分、τ = 0.20。测试 AUC 0.871、PR AP 0.750、Brier 0.138、召回率 93.4%。新东西是 6 张图 + model card——上面任何一个数字都可以用 make evaluate 复现。" |
3.3 App (Tab http://localhost:8000/app/) — 60-90 s
| EN |
中文 |
| "Step 3, the app — opened last as agreed. Two demo scenarios. First, Genting Highlands — a slope at 1865 m inside the training distribution. The model gives a moderate rain probability; the rule engine picks up orographic lift; the four mini-gauges decompose the risk by hazard type." |
"第三步 app——按约定最后才开。两个 demo 场景。第一个云顶高原——1865 m 的山坡，在训练分布之内。模型给中等降雨概率，规则引擎检测到地形抬升，四个 mini-gauge 把风险按灾害类型拆解。" |
"Second, Mt Everest — completely out of distribution. The model alone would say 'safe'. The Veto cascade fires three independent overrides — hypoxia, frostbite, gale — and the composite is forced to Danger. There's a unit test for exactly this: test_mt_everest_veto_hypoxia." |
"第二个珠峰——完全分布外。光看模型会说"安全"，但 Veto 级联触发三个独立否决——缺氧、冻伤、大风——综合分被强制设为 Danger。专门有单元测试覆盖这个场景：test_mt_everest_veto_hypoxia。" |
4. Next steps for Chapter 5 / Chapter 5 下一步
~ 90 seconds. This is the section the supervisor will react to most.
Frame each item as a concrete deliverable + estimated time + dependency.
≈ 90 秒。老师反应最强烈的就是这一节。每一项都以"交付物 + 估时 + 依赖"形式呈现。
4.1 Proposed Chapter 5 work plan / Chapter 5 工作计划
| # |
Deliverable |
EN one-liner |
中文一句话 |
Estimate |
| 5.1 |
Comparative ablation |
"Train LogReg + XGBoost on the same features and report ROC / PR / F2 side-by-side with RF — answers 'why RF?' empirically." |
"在同一特征集上训 LogReg + XGBoost，对比 ROC / PR / F2，**用数据回答"为什么选 RF"**。" |
1 week |
| 5.2 |
Hindcast validation |
"Replay 2020-2024 NaDMA-documented Malaysian flood / landslide events and check whether the system would have raised Warning / Danger at the right time. Reports hit-rate, lead-time, false-alarm rate." |
"把 2020-2024 NaDMA 公开的马来西亚洪水/滑坡事件逐一回放，看系统能否在事发前给出 Warning/Danger。报告命中率、提前量、误报率。" |
2 weeks |
| 5.3 |
Threshold sensitivity |
"Sweep τ ∈ {0.10, 0.15, 0.20, 0.25, 0.30}, plot precision-recall trade-off, and justify the operating point with a cost-of-error analysis." |
"扫 τ ∈ {0.10, 0.15, 0.20, 0.25, 0.30}，画精度-召回权衡曲线，用误差代价分析为最终选点辩护。" |
3 days |
| 5.4 |
Component ablation |
"Compare three system variants — RF only / Rule only / Hybrid — on the held-out test set and on the OOD Mt Everest case. Quantifies the rule-engine contribution." |
"对比三个系统变体——纯 RF / 纯规则 / 混合——在测试集和 OOD 珠峰场景上的表现。量化规则引擎的贡献。" |
4 days |
| 5.5 |
Small user study (optional) |
"Recruit 5-8 mountain hikers, run a 4-week panel, log system advice vs. their field judgment. Reports inter-rater agreement (Cohen's κ)." |
"招募 5-8 名登山者，4 周面板研究，记录系统建议 vs 他们现场判断，报告 Cohen's κ 一致性。" |
4 weeks |
| 5.6 |
Thesis Chapter 5 draft |
"Pull §5.1-5.5 into a single 12-15 page evaluation chapter with all figures, tables, and discussion." |
"把 §5.1-5.5 整合成 12-15 页的评估章节，含全部图表和讨论。" |
1 week (after 5.1-5.4) |
4.2 Decision tree to ask the supervisor / 请示决策树
| Question to ask |
EN |
中文 |
| Q1 |
"Sir, of the five evaluation tracks above, which two should I prioritise for the next four weeks before we converge on the Chapter 5 outline?" |
"老师，上面 5 条评估方向，未来四周您建议我重点做哪两条，然后再收敛到 Chapter 5 大纲？" |
| Q2 |
"Do you want me to include the user study (5.5)? It is the longest item and depends on participant recruitment — I want your call before committing." |
"用户研究 (5.5) 您要不要做？这一条最长、依赖招募——想请您拍板再投入。" |
| Q3 |
"For the comparative ablation, do you want the comparison framed as 'why RF wins' (defending current choice) or 'what if XGBoost wins' (open exploration)? The framing affects how I report inconclusive results." |
"对比实验您希望框成"为什么 RF 胜出"（捍卫现有选择）还是"如果 XGBoost 更好怎么办"（开放探索）？两种 framing 对模棱两可结果的报告方式不同。" |
| Q4 |
"Should I treat the Mt Everest OOD test as a thesis-level contribution (a stand-alone subsection on safety) or just an appendix item?" |
"珠峰 OOD 测试算论文级别的贡献（单独一节讲安全性），还是放附录就够？" |
5. Asks + closing 60 seconds / 请示 + 收尾 60 秒
| EN (say this) |
中文（口头要点） |
| "Sir, to summarise: since the last meeting I've shipped v1.0.0 — production-grade hardening, 70 tests at 97 % coverage, six evaluation figures, a published model card, full Docker reproducibility. The pipeline order is unchanged from what you asked: dataset, model, app. For Chapter 5 I have five evaluation tracks scoped; I'd like your guidance on which two to prioritise for the next four weeks." |
"老师，总结：自上次会议以来交付了 v1.0.0——工程化强化、70 个测试 97% 覆盖率、6 张评估图、model card、Docker 全复现。流水线顺序按您要求没动：dataset、model、app。Chapter 5 我列了 5 条评估方向，接下来四周您建议我先做哪两条？" |
| "I'll send you a 3-bullet email summary by tomorrow morning so we have written agreement on the priorities. Thank you for your time." |
"明早之前给您发 3 条要点的邮件总结，留个书面确认。谢谢老师。" |
6. Q&A defensive lines / Q&A 兜底话术
Anticipated follow-up questions from this update specifically (not the
classics from the 5/11 brief — those are still live, just don't repeat
them here).
针对本次进度汇报可能出现的追问（5/11 那份的经典 Q1-Q7 仍然有效，
不重复罗列）。
Q-N1 — "Why are you spending time on tests and Docker instead of the thesis?"
Q-N1 ——为什么你在写测试和 Docker 上花时间，不写论文？
| EN |
中文 |
"Sir, the v1.0.0 hardening was a one-time investment to make every Chapter 5 number reproducible by the examiner with a single command. Without it, every evaluation result would be a black box — the examiner could not verify the AUC of 0.871 herself. With make evaluate reproducing all six figures byte-for-byte, the thesis claims become falsifiable. From this point on, all my time goes to evaluation and writing." |
"老师，v1.0.0 的强化是一次性投资——为了让评审老师用一行命令就能复现 Chapter 5 的每一个数字。没有它，AUC = 0.871 就是黑盒，评审无法独立验证。现在 make evaluate 能把 6 张图按字节复现，论文的每个 claim 都可证伪。从今天起所有时间都给评估和写作。" |
Q-N2 — "Why hasn't the model improved since last time?"
Q-N2 ——模型为什么自上次以后没提升？
| EN |
中文 |
| "Two reasons. First, the supervisor's instruction was to consolidate dataset and model before adding more capacity — which is what I did. Second, the bottleneck right now is not the model but the rule engine's coverage of OOD scenarios, which is a Chapter 5 contribution rather than a hyperparameter tweak. I'd rather report a defensible 0.871 with a calibrated rule engine than chase 0.88 with an unprincipled stack." |
"两个理由：(1) 您上次的指示是先把 dataset 和 model 巩固好再加复杂度——我严格照做了。(2) 当前瓶颈不是模型本身，而是规则引擎对 OOD 场景的覆盖——这是 Chapter 5 的研究贡献，不是调超参。我宁愿报一个可辩护的 0.871 加一个校准好的规则引擎，也不要不讲原理地堆栈到 0.88。" |
Q-N3 — "Show me one concrete weakness you have not yet fixed."
Q-N3 ——给我说一个你目前还没修的具体弱点。
| EN |
中文 |
"Honestly, Sir, the biggest one is cape_jkg — the ERA5 archive returns predominantly zero CAPE for these Malaysian coordinates, which is a known coverage gap. The Random Forest learns nothing from it (0 % importance). The rule engine still uses live Open-Meteo CAPE at inference time, so the production output is fine, but the training signal for thunderstorm risk is weaker than I'd like. I plan to address this in §5.4 ablation by quantifying how much it matters." |
"老实说，老师，最大的弱点是 cape_jkg——ERA5 在这些马来西亚坐标上的 CAPE 几乎全为零（已知覆盖缺口），RF 完全没学到东西（特征重要性 0%）。规则引擎在推理时用的是 Open-Meteo 实时 CAPE，所以生产输出没问题，但雷暴风险的训练信号比我希望的弱。计划在 §5.4 消融实验里量化它的影响。" |
Q-N4 — "When can I see the first draft of Chapter 5?"
Q-N4 ——Chapter 5 初稿什么时候能给我看？
| EN |
中文 |
| "If you sign off on tracks 5.1 + 5.2 + 5.4 today, the data collection finishes in 3 weeks, writing takes 1 week, so you'd have a draft in 4 weeks from today. If you also want 5.5 (user study), add 4 weeks. I'll lock the date the moment you confirm the scope." |
"如果今天您拍板 5.1 + 5.2 + 5.4 三条，3 周收数据 + 1 周写作 = 4 周后给您初稿。如果再加 5.5（用户研究），再加 4 周。您一确认范围，我立刻锁定交稿日。" |
7. Materials checklist before walking in / 开会前自检清单
☐ Laptop ≥ 80 % battery, charger in bag
☐ Terminal A: `make run` is running, do not close
☐ Terminal B: `curl /api/health` returned ml_loaded: true within last 5 min
☐ 10 browser tabs open in cheat-sheet §0 order — app tab is LAST
☐ This file open on a separate screen / phone, NOT to be read aloud
☐ docs/MEETING_CHEAT_SHEET.md open as a fall-back
☐ models/MODEL_CARD.md open in case any number is challenged
☐ figures/evaluation_summary.json downloadable on demand
☐ Phone on silent
☐ One deep breath. You shipped v1.0.0. You're prepared.
☐ 笔记本电池 ≥ 80%，充电器已带
☐ 终端 A：`make run` 跑着，不要关
☐ 终端 B：5 分钟内 `curl /api/health` 返回 ml_loaded: true
☐ 10 个浏览器标签页按 cheat-sheet §0 顺序开好——app 标签放最后
☐ 本文档开在副屏 / 手机，不要照念
☐ docs/MEETING_CHEAT_SHEET.md 开着兜底
☐ models/MODEL_CARD.md 开着，老师质疑任何数字立刻打开
☐ figures/evaluation_summary.json 随时可发
☐ 手机静音
☐ 深呼吸。v1.0.0 已经交付。你准备好了。
8. Cross-references / 相关文档索引
Generated 2026-05-13 for the MicroClimate-X progress-update meeting at UKM.
此页为 2026-05-13 UKM 毕业设计 MicroClimate-X 进度汇报准备文档。
