MétaCan
Menu
Back to cohort
Record W1999309669 · doi:10.1211/jpp.59.2.0010

Characterization of the bulk properties of pharmaceutical solids using nonlinear optics - a review

2007· review· en· W1999309669 on OpenAlexaff
Chris Lee, Clare J. Strachan, P. J. Manson, Thomas Rades

Bibliographic record

VenueJournal of Pharmacy and Pharmacology · 2007
Typereview
Languageen
FieldMaterials Science
TopicNonlinear Optical Materials Research
Canadian institutionsDiscovery Centre
Fundersnot available
KeywordsCharacterization (materials science)Nonlinear opticsNonlinear opticalNonlinear systemMaterials scienceNanotechnologyOpticsPhysics

Abstract

fetched live from OpenAlex

With the development of stable, compact and reliable pulsed laser sources the field of characterizing materials through their nonlinear optical response has bloomed. Second harmonic generation by non-centrosymmetric crystal structures has provided a new spectroscopic tool of potentially great utility in the pharmaceutical field. The nonlinear optical response of various materials provides a very sensitive technique for the characterization of pharmaceutically interesting bulk compounds and dispersions, and determining their concentrations. This work has potential application for in-line monitoring and quality control of pharmaceutical manufacturing. In this article we have presented an extensive review of the spectroscopic techniques that make use of the nonlinear optical response of solid media. Also, we have presented the results of our own work in this field.

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)0.001
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.215
GPT teacher head0.476
Teacher spread0.260 · 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

Citations9
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Pharmacy and PharmacologySame topicNonlinear Optical Materials ResearchFrench-language works237,207