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Record W1931733199 · doi:10.3233/bme-141240

Comparative study of the biodegradability of porous silicon films in simulated body fluid

2015· letter· en· W1931733199 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBio-Medical Materials and Engineering · 2015
Typeletter
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsMemorial University of Newfoundland
FundersMemorial University of Newfoundland
KeywordsMicroporous materialDissolutionSiliconSimulated body fluidMaterials sciencePorous siliconMesoporous materialPorosityChemical engineeringComposite materialChemistryOrganic chemistryMetallurgyScanning electron microscopeCatalysis

Abstract

fetched live from OpenAlex

The biodegradability of oxidized microporous, mesoporous and macroporous silicon films in a simulated body fluid with ion concentrations similar to those found in human blood plasma were studied using gravimetry. Film dissolution rates were determined by periodically weighing the samples after removal from the fluid. The dissolution rates for microporous silicon were found to be higher than those for mesoporous silicon of comparable porosity. The dissolution rate of macroporous silicon was much lower than that for either microporous or mesoporous silicon. This is attributed to the fact that its specific surface area is much lower than that of microporous and mesoporous silicon. Using an equation adapted from [Surf. Sci. Lett. 306 (1994), L550-L554], the dissolution rate of porous silicon in simulated body fluid can be estimated if the film thickness and specific surface area are known.

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 categoriesMeta-epidemiology (narrow)
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 score0.089
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.017
GPT teacher head0.233
Teacher spread0.216 · 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