MétaCan
Menu
Back to cohort
Record W1994475966 · doi:10.1080/00219266.2010.9656220

Teaching the microbial growth curve concept using microalgal cultures and flow cytometry

2010· article· en· W1994475966 on OpenAlexaff
Nathalie L. Forget, Claude Belzile, Pierre Rioux, Christian Nozais

Bibliographic record

VenueJournal of Biological Education · 2010
Typearticle
Languageen
FieldEnergy
TopicAlgal biology and biofuel production
Canadian institutionsUniversité du Québec à Rimouski
Fundersnot available
KeywordsFlow cytometryBiologyBiological systemIsochrysis galbanaHemocytometerMicroorganismBacterial growthMicrobial ecologyBacteriaBotanyAlgaeFood scienceBiochemistryMolecular biology

Abstract

fetched live from OpenAlex

Abstract The microbial growth curve is widely studied within microbiology classes and bacteria are usually the microbial model used. Here, we describe a novel laboratory protocol involving flow cytometry to assess the growth dynamics of the unicellular microalgae Isochrysis galbana. The algal model represents an appropriate alternative to bacteria because its slower growth rate allows a better visualization of the growth phases, which makes the logistic of the laboratory sessions easier. Flow cytometry is a technique commonly used for cell enumeration in ecology, microbiology, and medical sciences because of its accuracy and speed. In this experiment, microbial growth was observed under two light conditions and cell abundance was monitored using a flow cytometer and a haemocytometer. The chlorophyll a fluorescence of each cell was also measured by the flow cytometer and was used as an index of cellular content of photosynthetic pigments. Students were asked to compare the results obtained with the two techniques and to explain the effect of light conditions on the growth curve shape and dynamics. Keywords: microbiologymicrobial growth curveflow cytometryIsochrysis galbanacell counting techniques

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)0.001
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.591
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
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 head0.017
GPT teacher head0.294
Teacher spread0.277 · 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

Citations12
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Biological EducationSame topicAlgal biology and biofuel productionFrench-language works237,207