MétaCan
Menu
Back to cohort
Record W2479659381 · doi:10.1107/s2059798316010706

<i>TakeTwo</i>: an indexing algorithm suited to still images with known crystal parameters

2016· article· en· W2479659381 on OpenAlexafffund
Helen M. Ginn, Philip Roedig, Anling Kuo, Gwyndaf Evans, Nicholas K. Sauter, Oliver P. Ernst, Alke Meents, Henrike M. Müller‐Werkmeister, R. J. Dwayne Miller, David I. Stuart

Bibliographic record

VenueActa Crystallographica Section D Structural Biology · 2016
Typearticle
Languageen
FieldMaterials Science
TopicEnzyme Structure and Function
Canadian institutionsCanada Research ChairsUniversity of TorontoUniversity of New Brunswick
FundersBiotechnology and Biological Sciences Research CouncilOffice of ScienceNational Institutes of HealthEuropean CommissionSLAC National Accelerator LaboratoryWellcome TrustNational Institute of General Medical SciencesMedical Research CouncilCanadian Institute for Advanced ResearchU.S. Department of Energy
KeywordsSearch engine indexingOrthorhombic crystal systemSpace (punctuation)CurvatureImage (mathematics)SynchrotronAlgorithmComputer scienceCrystallographyDiffractionMathematicsOpticsPhysicsArtificial intelligenceGeometryChemistry

Abstract

fetched live from OpenAlex

The indexing methods currently used for serial femtosecond crystallography were originally developed for experiments in which crystals are rotated in the X-ray beam, providing significant three-dimensional information. On the other hand, shots from both X-ray free-electron lasers and serial synchrotron crystallography experiments are still images, in which the few three-dimensional data available arise only from the curvature of the Ewald sphere. Traditional synchrotron crystallography methods are thus less well suited to still image data processing. Here, a new indexing method is presented with the aim of maximizing information use from a still image given the known unit-cell dimensions and space group. Efficacy for cubic, hexagonal and orthorhombic space groups is shown, and for those showing some evidence of diffraction the indexing rate ranged from 90% (hexagonal space group) to 151% (cubic space group). Here, the indexing rate refers to the number of lattices indexed per image.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.021
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.004
Science and technology studies0.0020.001
Scholarly communication0.0030.004
Open science0.0050.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0210.015

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 head0.010
GPT teacher head0.237
Teacher spread0.227 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations46
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueActa Crystallographica Section D Structural BiologySame topicEnzyme Structure and FunctionFrench-language works237,207