pubmlp

Multimodal publication classifier with LLM and deep learning. Fuses transformer embeddings from Hugging Face with tabular features through a multilayer perceptron (MLP) on PyTorch for human-in-the-loop screening. Screen by matched rules, by semantic similarity through sentence-transformers, by the classifier with active learning, or by a language model as a second rater. Read exports in every format bibliometrix accepts, extract page-anchored evidence with pdfplumber, and report stopping criteria and automation use for PRISMA.

Installation

pip install pubmlp

With optional dependencies:

pip install "pubmlp[screening]"  # regex and semantic screening, stratified sampling
pip install "pubmlp[fulltext]"   # PDF reading with page-anchored evidence
pip install "pubmlp[benchmark]"  # public benchmark datasets

From GitHub:

pip install git+https://github.com/mshin77/pubmlp.git

Getting Started

See Quick Start and Screening Workflow for tutorials.

Citation

Shin, M. (2026). pubmlp: Multimodal publication classifier with LLM and deep learning (Python package version 0.6.1) [Computer software]. https://github.com/mshin77/pubmlp

Reference

Shin, M., & McKenna, J. (2026). Exploring the research landscape on single-case design methodology using technology through text mining and large language models. Journal of Behavioral Education. https://doi.org/10.1007/s10864-026-09630-1

Metadata

Release files for pubmlp 0.6.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pubmlp 0.6.2
File	Size	Uploaded
pubmlp-0.6.2.tar.gz	62.2 kB	Sep 13, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for pubmlp 0.6.2
File	Interpreter	ABI	Platform	Reset
pubmlp-0.6.2-py3-none-any.whl 69.0 kB Sep 13, 2026	Python 3	none	any	Details

Total release size: 131.2 kB

Release files / pubmlp-0.6.2.tar.gz

Download URL	pubmlp-0.6.2.tar.gz
Size	62.2 kB
Tags	Source
SHA-256 checksum How to use checksums	`fb88baeb6951db41f0925c44937b298d1a76a41ce503a0cd4dea43f6193eb636`
BLAKE2b-256 checksum How to use checksums	`cf108c36916a227c845f5f7e610446df8767bd9681d6da95c5cc985584410137`
Upload date	Sep 13, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.13.9`

Release files / pubmlp-0.6.2-py3-none-any.whl

Download URL	pubmlp-0.6.2-py3-none-any.whl
Size	69.0 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`5e8e86849cb313708c67e3f71d488beb01d8d55c3e2bf6989c2028f1ef194359`
BLAKE2b-256 checksum How to use checksums	`3fbe46dedcd9cb7e5652f1748bfeaf367256afa0aed4b72693cb9d5a15476931`
Upload date	Sep 13, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.13.9`