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Record W2051506844 · doi:10.1063/1.3625392

Observations of Biological Specimens at Cryo-Temperatures with Soft X-ray Microscope at the SR Center of Ritsumeikan University

2011· article· en· W2051506844 on OpenAlexfundno aff
K. Takemoto, Mitsuhiro Kimura, Keisuke Usui, Takuji Ohigashi, Hiromasa Fujii, K. Nakanishi, H. Namba, Hiroshi Kihara, Ian McNulty, Catherine Eyberger, Barry Lai

Bibliographic record

VenueAIP conference proceedings · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced X-ray Imaging Techniques
Canadian institutionsnot available
FundersRitsumeikan UniversityKansai UniversityMinistry of Education, Culture, Sports, Science and TechnologyKansai Medical UniversityRyerson University
KeywordsMicroscopeMaterials scienceOptical microscopeSample (material)Cryogenic temperatureResolution (logic)CryogenicsCenter (category theory)OpticsTemperature controlScanning electron microscopeComposite materialPhysicsMechanical engineeringEngineeringChemistryCrystallographyComputer science

Abstract

fetched live from OpenAlex

We have developed and installed a cryogenic sample chamber system to the soft x‐ray microscope BL‐12 at SR Center of Ritsumeikan University. The temperature of the specimens can be regulated continuously from 273 K up to 173 K. The cryogenic images of biospecimens have been taken. However, the resolution of the image was lower than that of the microscope. Therefore, the control method of LN2 and the sample chamber have been improved. The new chamber is compact, and LN2 flow is controlled with the LabVIEW program strictly. The compact chamber succeeded in high cooling efficiency, and the LN2 controlling system succeeded in high temperature stability.

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)0.000
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.042
GPT teacher head0.240
Teacher spread0.198 · 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
GenreEmpirical

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

Citations1
Published2011
Admission routes1
Has abstractyes

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