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Record W4386816348 · doi:10.23977/jemm.2023.080310

Design of an Automatic Packaging Machine for Syringes

2023· article· en· W4386816348 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Engineering Mechanics and Machinery · 2023
Typearticle
Languageen
FieldEngineering
TopicEmbedded Systems and FPGA Applications
Canadian institutionsnot available
Fundersnot available
KeywordsSyringeMechanical engineeringEngineeringEngineering drawingComputer science

Abstract

fetched live from OpenAlex

The 5ml syringe automatic packaging machine designed in this paper is mainly composed of mechanical structure and control system. The machine is based on the traditional vertical packaging machine, syringe automatic packaging machine can complete the syringe from the clutter of syringes to achieve a single sequential packaging, can achieve the whole process from feeding, film forming, and then the bag heat sealing, shear. The feeding is achieved by vibrating discs, the heat sealing device is controlled by a cylinder heat sealing jig to seal the plastic film longitudinally and horizontally, and the serrated blade is used to cut, the whole machine is compact and easy to install and manipulate. The packaging machine is highly automated, the user only needs to put the syringe into the vibrating plate, through the machine's servo control, can achieve a key start, but also through the adjustment of the software parameters to achieve control of the syringe packaging speed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.896
Threshold uncertainty score0.437

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.232
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it