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Record W3136080276 · doi:10.1039/d0qm01099e

Advances in biomedical applications of self-healing hydrogels

2021· article· en· W3136080276 on OpenAlexaff
Hassan Rammal, Amin GhavamiNejad, Ahmet Erdem, Rene Mbeleck, Mohammad Reza Nematollahi, Sibel Emi̇r Di̇ltemi̇z, Halima Alem, Mohammad Ali Darabi, Yavuz Nuri Ertaş, Edward J. Caterson, Nureddin Ashammakhi

Bibliographic record

VenueMaterials Chemistry Frontiers · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHydrogels: synthesis, properties, applications
Canadian institutionsUniversity of WinnipegUniversity of ManitobaUniversity of TorontoToronto Public Health
FundersNational Institutes of HealthAmerican Heart Association
KeywordsSelf-healing hydrogelsSelf-healingMaterials scienceNanotechnologyBiomedical engineeringMedicinePolymer chemistry

Abstract

fetched live from OpenAlex

In this paper, various self-healing hydrogels are discussed including their healing mechanisms and details of their current biomedical applications.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.231
Teacher spread0.225 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations92
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueMaterials Chemistry FrontiersSame topicHydrogels: synthesis, properties, applicationsFrench-language works237,207