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Human factors design for the BMIT biomedical beamlines

2013· article· en· W2149793447 on OpenAlexaffabout
Craig D. Miller, Tomasz W. Wysokiński, George Belev, Dean Chapman

Bibliographic record

VenueJournal of Physics Conference Series · 2013
Typearticle
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsBeamlineUsabilityInstrumentation (computer programming)Computer scienceSystems engineeringMedical physicsEngineeringHuman–computer interactionMedicineOperating system

Abstract

fetched live from OpenAlex

Operation of a biomedical beamline poses a unique set of operational and instrumentation challenges for a synchrotron facility. From proper handling and care of live animals and animal tissues, to a user community drawn primarily from the medical and veterinary realms, the work of a biomedical beamline is unique when compared to other beamlines. At the Biomedical Imaging and Therapy (BMIT) beamlines at Canadian Light Source (CLS), operation of the beamlines is geared towards our user community of medical personnel, in addition to basic science researchers. Human factors considerations have been incorporated wherever possible on BMIT, including in the design of software and hardware, as well as ease-of-use features of beamline control stations and experiment hutches. Feedback from users continues to drive usability improvements to beamline operations.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.877
Threshold uncertainty score0.237

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.041
GPT teacher head0.248
Teacher spread0.207 · 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 teacher head, 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

Citations2
Published2013
Admission routes2
Has abstractyes

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