Comment by amber_raza | Hacker News Reader

Comment by amber_raza | Hacker News Reader

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Thanks for the feedback—this is helpful.

1. Re: Clerk/uBlock: You were spot on. The default Clerk domain often gets flagged by strict blocklists. I just updated the DNS records to serve auth from a first-party subdomain (clerk.getevidex.com) to resolve this. It should be working now.

2. Re: Freshness & 'Rubbish': You are absolutely right that standard of care doesn't (and shouldn't) change overnight based on one new paper.

However, the decision to ditch the Vector DB for Live Search wasn't about pushing 'experimental treatments'—it was about Safety and Engineering constraints:

Retractions & Safety Alerts: A stale vector index is a safety risk. If a major paper is retracted or a drug gets a black-box warning today, a live API call to PubMed/EuropePMC reflects that immediately. A vector store is only as good as its last re-index.

The 'Long Tail': Vectorizing the entire PubMed corpus (35M+ citations) is expensive and hard to keep in sync. By using the search APIs directly, we get the full breadth of the database (including older, obscure case reports for rare diseases) without maintaining a massive, potentially stale index.

The goal isn't to be 'bleeding edge'—it's to be 'currently accurate'.

a good system (like openevidence) indexes every paper released and semantic search can incredible helpful since the the search api of all those providers are extremely limited in terms of quality.

now you get why those system are not cheap. keeping indexes fresh, maintaining high quality at large scale and being extremely precise is challenging. by having distributed indexes you are at the mercy of the api providers and i can tell you from previous experience that it won't be 'currently accurate'.

for transparency: i am building a search api, so i am biased. but i also build medical retrieval systems for some time.

Appreciate the transparency and the insight from a fellow builder.

You are spot on that maintaining a fresh, high-quality index at scale is the 'hard problem' (and why tools like OpenEvidence are expensive).

However, I found that for clinical queries, Vector/Semantic Search often suffers from 'Semantic Drift'—fuzzily matching concepts that sound similar but are medically distinct.

My architectural bet is on Hybrid RAG:

Trust the MeSH: I rely on PubMed's strict Boolean/MeSH search for the retrieval because for specific drug names or gene variants, exact keyword matching beats vector cosine similarity.

LLM as the Reranker: Since API search relevance can indeed be noisy, I fetch a wider net (top ~30-50 abstracts) and use the LLM's context window to 'rerank' and filter them before synthesis.

It's definitely a trade-off (latency vs. index freshness), but for a bootstrapped tool, leveraging the NLM's billions of dollars in indexing infrastructure feels like the right lever to pull vs. trying to out-index them.

This sounds like a cookie cutter ChatGPT reply.

Haha, ouch. I promise it’s just me—I just spent 20 minutes rewriting that comment because I didn't want to sound like an idiot explaining search to a search engineer. I'll take it as a sign to dial back the formatting next time.

That emdash in your reply is so in-your-face "—".

Now it is loading. You are still in violation of GDPR rules by including a SVG file with the google logo from the clerk.com domain and a css file from tailwindcss.com - both are tracking users. There is no privacy policy on your page. The privacy policy should include a list of companies you share my visitor data with and what kind of data is shared, and how I can deny sharing that data.

Fair point on the Privacy Policy link. That definitely slipped through the cracks in the launch rush. I just pushed a fix to add it to the footer now.

Re: the trackers: The SVG is just the icon inside the Clerk login button, but you're right that loading Tailwind via CDN isn't ideal for strict GDPR IP-masking. I'll look into self-hosting the assets to clean that up.

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