RRepoGEO

REPOGEO REPORT · LITE

naver/biobert-pretrained

Default branch master · commit b2be8384 · scanned 6/10/2026, 2:06:36 AM

GitHub: 705 stars · 91 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface naver/biobert-pretrained, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    biomedical-nlp, bert, pretrained-models, natural-language-processing, text-mining, biomedical-text-mining, named-entity-recognition, question-answering, relation-extraction
  • highlicense#2
    Add a LICENSE file and declare it in the README

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the repository root (e.g., Apache-2.0 or MIT). Then, add a line to the README, such as: 'This project is licensed under the [License Name] License - see the LICENSE file for details.'
  • mediumhomepage#3
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    Add the URL 'https://arxiv.org/abs/1901.08746' (or a more official project page if one exists) to the repository's About section as the homepage.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface naver/biobert-pretrained
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
BioBERT
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. BioBERT · recommended 2×
  2. PubMedBERT · recommended 2×
  3. ClinicalBERT · recommended 2×
  4. SciBERT · recommended 2×
  5. BioMegatron · recommended 2×
  • CATEGORY QUERY
    Looking for pre-trained language models suitable for biomedical text analysis and information extraction.
    you: not recommended
    AI recommended (in order):
    1. BioBERT
    2. PubMedBERT
    3. ClinicalBERT
    4. SciBERT
    5. BioMegatron
    6. GatorTron

    AI recommended 6 alternatives but never named naver/biobert-pretrained. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the top BERT-based models for biomedical named entity recognition and question answering?
    you: not recommended
    AI recommended (in order):
    1. BioBERT
    2. PubMedBERT
    3. ClinicalBERT
    4. BioMegatron
    5. SciBERT
    6. BioLinkBERT
    7. RoBERTa

    AI recommended 7 alternatives but never named naver/biobert-pretrained. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of naver/biobert-pretrained?
    pass
    AI named naver/biobert-pretrained explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts naver/biobert-pretrained in production, what risks or prerequisites should they evaluate first?
    pass
    AI named naver/biobert-pretrained explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo naver/biobert-pretrained solve, and who is the primary audience?
    pass
    AI named naver/biobert-pretrained explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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naver/biobert-pretrained — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite