Why Verified Lists Outperform Scraped Targets in 2026
Your customized message can be found under. A rejection e-mail looks like this: All demands will be sent out to at least one publisher e-mail address for approval.
This generally implies that sales reps who currently work with particular accounts have the chance to authorize demands from them. The other receivers of the request emails must show up to you in the 'To:' line of the e-mail. This also indicates that it is possible that somebody else will have dealt with a demand before you get to it.
As you compose, Automobile Linker silently underlines the words that match your other notes and uses a oneclick wikilink ranked by a confidence score (not a blind text match), so you get to select the beneficial links and not the noise. This software was vibe-coded. Auto Linker constantly suggests and never links on its own.
A lot of "car link" tools do a match: a word either equates to a note title or it doesn't - Car Linker rather computes a for every candidate and just reveals the ones that clear a threshold you control. That rating blends numerous signals: how closely the text matches a note's title (exact, stemmed, or a close typo).
No difficult stopword list; it's graded, and selftunes to your vault by means of IDF. AND reads in a different way from and; ALLCAPS/ TitleCase get an increase, lowercase function words a charge.
Why Verified Lists Outperform Scraped Targets in 2026
Steps 58 just push ball game up or down a note is removed just at the steps marked. the text is split into tokens (keeping intraword bits like the dot in 802.1 q), keeping in mind where phrase vs anchor separators fall. periods inside [[ links]], #tags, inline 'code' and "'fenced blocks are excluded up front.
a spannote you've rejected (pernote or vaultwide), or the note you're presently editing, is dropped before scoring. how textually complete the match is: entire title = 1.0; a subphrase or single word = the share of the title's details (IDF) it covers; a digitbase 0.85; a typo (1 edits length).
an only AND/ Database gets a boost and a lowercase common word a charge; neutral for multiword periods. adds PageRank (hub notes), semantic similarity (if the model is on) and your accept history (if any), then renormalizes everything to a single 01 confidence. candidates that don't clear the bar are dropped.
survivors are highlighted with an approve/reject tooltip: an underline indicates text decided it, a one means meaning was the deciding lift. Simply put, a note leaves when it shares no word (3 ), sits in a skipped/rejected/self area (2, 4), scores too low (9 ), or loses to an overlapping much better match (10 ).
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tune the balance yourself; bring back defaults anytime. manages 802.1 Q, Topic: Subtopic, client-server, and pathlike titles by means of configurable separator rules. an adjoining run of a title's words matches the entire note (typing method 3 - CAD suggests Payment method 3 - CAD), scored by how much of the title it covers.
, including a distinct word standing in for the entire (kruger DunningKruger). link [[ Dinosaurraptor]] as soon as and raptor can recommend Dinosaur afterwards, given a confident score. dismiss an idea pernote or vaultwide; manage and restore them in settings. the target note, authorize (), or reject () inline. Ctrl/Cmd + inserts a bare [[ Keep in mind]] (no display alias); Shift + authorizes every repeat of that tip in the note simultaneously.
The index, scores, reject list, learned aliases, and the optional embedding cache all remain on your device no telemetry, no external API. The network event in the whole plugin is the optional, one-time download of the embedding design when you turn the semantic tier on (it carries no note information, and can be prevented totally by pointing at a model you already have).
When you enable it you choose: the default multilingual design (Xenova/paraphrase-multilingual-MiniLM-L12-v2, 50 MB, as soon as), or point at a format design already on disk (airgapped/ your own). Usage to precompute every note's "meaning fingerprint" so meaningbased ranking is ready across the entire vault instantly. The semantic tier actual candidates it fine-tunes what the text match currently discovered.
