Biocapteurs ampérométriques à cholinestérases pour la détermination des pesticides organophosphorés
Bibliographic record
Abstract
The purpose of this study is a comparative presentation of the different types of the amperometric biosensors based on cholinesterases for the determination of organophosphorous pesticides using the bibliographical information of the last 20 years. The study contains the presentation of the structure and properties of the cholinesterases, the main reactions implied in the functioning of the amperometric biosensors, their applications and factors influencing the detection or (and) the inhibition process. The detection limit of the mono- or bi-enzymatic amperometric biosensors are relatively higher than those corresponding with the immunobiosensors or with gas and liquid chromatography, which are still considered as the reference methods. As shown, for many other amperometric biosensors, the MichaelisMenten's kinetic treatment used for reactions catalyzed by free enzymes can be extended to describe the response of amperometric biosensors based on immobilized cholinesterases. The positive compromise between advantages and drawbacks, as well as the "soft" experimental conditions, point to the amperometric monoenzymatic bioelectrode, as an attractive analytical tool for the detection of organophosphorous pesticides.Key words: amperometric biosensor, acetylcholinesterase, organophosphorous pesticides, kinetic, inhibition.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".