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Inactivation of bacteria and yeasts on agar surfaces with high power Nd: YAG laser light

2008· article· en· W2171996218 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.

Bibliographic record

VenueLetters in Applied Microbiology · 2008
Typearticle
Languageen
FieldMedicine
TopicLaser Applications in Dentistry and Medicine
Canadian institutionsInstitute of Infection and Immunity
FundersUniversity of Glasgow
KeywordsNutrient agarAgarBacteriaAgar plateSerratia marcescensLaserPower densityFood scienceBiologyOpticsEscherichia coliBiochemistry

Abstract

fetched live from OpenAlex

Near infrared light from a high-powered, 1064 nm, Neodymium:Yttrium Aluminium Garnet (Nd:YAG) laser killed a variety of Gram-positive and Gram-negative bacteria and two yeasts, lawned on nutrient agar plates. A beam (cross-sectional area, 1.65 cm2) of laser light was delivered in 10 J, 8 ms pulses at 10 Hz, in a series of exposure times. For each microbial species, a dose/response curve was obtained of area of inactivation vs energy density (J cm-2). The energy density that gave an inactivation area (IA) equal to 50% of the beam area was designated the IA50-value and was plotted together with its 95% confidence limits. Average IA50-values were all within a threefold range and varied from 1768 J cm-2 for Serratia marcescens to 4489 J cm-2 for vegetative cells of Bacillus stearothermophilus. There were no systematic differences in sensitivity attributable to cell shape, size, pigmentation or Gram reaction. At the lowest energy densities where inactivation was achieved for the majority of organisms (around 2000 J cm-2), no effect was observed on the nutrient agar surface, but as the energy density was increased, a depression in the agar surface was formed, followed by localized melting of the agar.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.094
Threshold uncertainty score0.396

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 head0.006
GPT teacher head0.207
Teacher spread0.201 · 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