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Phage Display - A Promising Tool for the Recovery of Valuable Metals from Primary and Secondary Resources

2017· article· en· W2747458472 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

VenueDiffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomena · 2017
Typearticle
Languageen
FieldMaterials Science
TopicDiatoms and Algae Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPhage displayMaterials scienceNanotechnologyScrapBiochemical engineeringMetalLeaching (pedology)Combinatorial chemistryBiologyMetallurgyPeptideChemistryBiochemistryEngineering

Abstract

fetched live from OpenAlex

The development of effective and ecofriendly processes for the recovery of critical elements poses a challenge for scientists all over the world. A novel approach is the generation of highly specific peptides that bind with high affinity to individual elements of interest. The peptides are selected by phage surface display (PSD) technology. In this study, PSD technology has been applied in two different approaches. The focus of the first approach was the identification of peptides that bind specifically to special particles of interest that are part of electronic scrap aiming towards the development of new recycling processes. In the second approach, metal ion binding peptides were isolated via PSD to use them for the targeted removal and enrichment of these elements from complex leaching solutions or from industrial waters. To address the economic production of peptides, the development of a new expression system is also part of this study.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.597
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0030.004
Open science0.0040.009
Research integrity0.0000.001
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 head0.049
GPT teacher head0.328
Teacher spread0.278 · 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