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Technology Study of Polypropylene Hollow Fiber Membranes-Like Artificial Lung Made by the Melt-Spinning and Cold-Stretching Method

2011· article· en· W2012971398 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdvanced materials research · 2011
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsUniversity of Waterloo
FundersDivision of Materials ResearchTianjin Science and Technology Program
KeywordsSpinningMembraneMaterials scienceHollow fiber membranePolypropyleneAnnealing (glass)Melt spinningArtificial lungComposite materialFiberChemistry

Abstract

fetched live from OpenAlex

Artificial lung also called as oxygenator which performs a function of exchanging O2 and removing CO2 from blood. Due to its good performance at the exchange area, oxygenation, etc, hollow fiber membranes have become the main research direction of artificial lung. Polypropylene (pp) hollow fiber membranes made by the melt-spinning and cold-stretching methods (MSCS) in this study. Through the research on the membrane manufacture process and technology optimization to prepare suitable membrane for artificially lung. The performance of membrane was affected by the melt-draw ratio and spinning temperature, annealing temperature, and the proportional relations of cold stretch with hot stretch. The results of the study show that improve melt-draw ratio, select the appropriate annealing conditions and the reasonable ratio of hot stretch with cold stretch can effectively increase the air flux of pp hollow fiber membrane.

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)0.004
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.647

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.373
Teacher spread0.329 · 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