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Record W2103680992 · doi:10.1107/s0907444911055296

Crystallography on a chip

2012· article· en· W2103680992 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

VenueActa Crystallographica Section D Biological Crystallography · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced X-ray Imaging Techniques
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaMax-Planck-GesellschaftPaul Scherrer InstitutUniversity of Toronto
KeywordsFemtosecondReciprocal latticeDiffractionChipMaterials scienceProtein crystallizationOpticsLaserRadiationCrystal (programming language)OptoelectronicsNanotechnologyResolution (logic)CrystallographyComputer scienceChemistryPhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

A new chip-based crystal-mounting approach for rapid room-temperature data collection from numerous crystals is described. This work was motivated by the recent development of X-ray free-electron lasers. These novel sources deliver very intense femtosecond X-ray pulses that promise to yield high-resolution diffraction data of nanocrystals before their destruction by radiation damage. Thus, the concept of `diffraction before destruction' requires rapid replenishment of the sample for each exposure. The chip promotes the self-assembly of an array of protein crystals on a surface. Rough features on the surface cause the crystals to adopt random orientations, allowing efficient sampling of reciprocal space.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.689
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.020
GPT teacher head0.261
Teacher spread0.241 · 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