MétaCan
Menu
Back to cohort
Record W2100063867 · doi:10.1002/bit.21543

A predictive nutritional model for plant cells and hairy roots

2007· article· en· W2100063867 on OpenAlex
M. Cloutier, Edith Bouchard-Marchand, Pascal Perrier

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

VenueBiotechnology and Bioengineering · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant nutrient uptake and metabolism
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsCatharanthus roseusDaucus carotaSuspension cultureCell cultureKineticsIntracellularBotanyBiologyPlant cellBiochemistryChemistry

Abstract

fetched live from OpenAlex

A structured nutritional model is proposed to describe growth and nutritional behavior of Eschscholtzia californica suspension cells and Catharanthus roseus and Daucus carota hairy roots in in vitro culture. The model describes the cells specific growth rate from concentration of intracellular nutrients such as inorganic phosphate (Pi), nitrogen sources (NO(3) (-) and NH(4) (+)) and sugars. Two-level Michaelis-Menten kinetics are used to describe Pi and NO(3) (-) uptake and simple Michaelis-Menten kinetics for description of sugars uptake. Model parameters for each cell line were calibrated using data from batch cultures. The predictive capacity of the model was tested using data from medium exchange hairy root cultures. The model describes growth and nutritional behavior for the cell and hairy root lines. A sensitivity analysis was performed to identify critical model parameters and effect of initial conditions. The cell and hairy roots lines are also compared from their kinetic parameters. The kinetic model is efficient for describing and predicting growth and nutritional behaviors of suspension cells and hairy roots.

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 score0.367
Threshold uncertainty score0.185

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 head0.013
GPT teacher head0.189
Teacher spread0.175 · 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