MétaCan
Menu
Retour à la cohorte
Enregistrement W4416392314 · doi:10.1186/s43591-025-00149-2

Correction to: Risk-based management framework for microplastics in aquatic ecosystems

2025· article· en· W4416392314 sur OpenAlexaff
Alvine C. Mehinto, Scott Coffin, Albert A. Koelmans, Susanne M. Brander, Martin Wagner, Leah M. Thornton Hampton, G.A. Burton, Ezra Miller, Todd Gouin, Stephen B. Weisberg, Chelsea M. Rochman

Notice bibliographique

RevueMicroplastics and Nanoplastics · 2025
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueMicroplastics and Plastic Pollution
Établissements canadiensUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésVolume (thermodynamics)MicroplasticsParticle (ecology)Confidence intervalMathematical modelProcess (computing)CylinderCalibration

Résumé

récupéré en direct d'OpenAlex

The authors of this study discovered two mathematical errors in the alignment of toxicity data to the ecologically relevant metrics (ERMs), volume and surface area. The mathematical process was accurately described in the supplemental information of the original publication. The errors were only present in the source code for the Toxicity of Microplastics Explorer (ToMEx) used to perform the calculations [4]. In addition, the corrected analysis also excludes data from a study used in the previous analysis due to failure to meet the predefined technical red criteria for inclusion of control data [1]. The exclusion of this study has a minor impact on final threshold values and confidence intervals relative to mathematical errors. Estimation of particle volume correction. In the original publication, particle volume was incorrectly calculated for fragments, and the generic equation for the volume of a cylinder was used to estimate the volume of fibers, assuming a diameter of 15 μm - unless the length was otherwise reported (Kooi et al., 2019). The corrected analysis now applies the following equation to estimate particle volume for all morphologies where a, b, and c are equivalent to one-half times the particle length, width, and height:. The application of this equation is accurately described in the supplementary information in the original Mehinto et al., [3] manuscript (equation S8). If the width is unknown, the average length to width ratio for the selected environmental compartment is used to estimate width [2]. If height is unknown, the height to width ratio was assumed to be 0.67 [2]. Estimation of particle surface area correction. Particle surface area was incorrectly calculated for all morphologies. Specifically, particle length (a), width (b), and height (c) were not multiplied by one-half before the application of the surface area equation, which is accurately described in supplementary information of the original Mehinto et al., [3] manuscript (equation S9): (Formula presented.) Estimation of maximum ingestible size. A unit conversion was being misapplied when estimating the maximum ingestible particle length according to the allometric equation provided in Jâms, et al. 2020. (Nature). Specifically, instead of the body length (reported in cm) being multiplied by 10 in the model (i.e., maximum ingestible size [mm] = 10^(0.9341 * log10(body length [cm] * 10) − 1.1200)); the order of operations was incorrect: (i.e., maximum ingestible size [mm] = 10^(0.9341 * log10(body length [cm]) − 1.1200) * 10). Effect on calculated threshold values. Corrections to the threshold values for food dilution resulted in changes no more than 9 particles or 2 mg per liter at most (Table 1). The largest change in threshold values was for Threshold #4, Source Control. All the corrected threshold values were also well within the original confidence intervals, which remain wide. Comparison of threshold values for food dilution, where data are aligned according to particle volume, before and after corrections were made Threshold particles/L (95% CI) mg/L (95% CI) Previous Corrected Previous Corrected 0.3 a 0.2 a 0.05 a 0.04 a 3 (0.3–66) 2 (0.2–123) 0.4 (0.05–11.05) 0.4 (0.04–20.04) 5 (0.4–219) 3 (0.3–261) 0.9 (0.07–36.07) 0.6 (0.05–43.05) 34 (3–859) 23 (19 − 1,150) 6 (0.4–141) 4 (0.3–188) a Threshold 1 is the lower 95% CI of the HC5 calculated for Threshold 2, therefore confidence intervals cannot be reported for this threshold Corrections to the threshold values for tissue translocation had a greater impact than food dilution (Table 2). Values for Thresholds 1 and 2 were roughly the same as previously published values. Threshold 1 increased by 23 particles per liter or 4 mg per liter. Threshold 2 increased by 65 particles per liter or 11 mg per liter. Threshold 3 values decreased by 169 particles per liter or 27 mg per liter (~ 19% decrease). Threshold 4 values also decreased, though more substantially by 1,770 particles per liter or 292 mg per liter (~ 40% decrease). However, all corrected values fell within the previously published confidence intervals. Most confidence intervals narrowed following the correction, though they remained wide. Comparison of threshold values for tissue translocation, where data are aligned according to particle surface area, before and after corrections were made Threshold particles/L (95% CI) mg/L (95% CI) Previous Corrected Previous Corrected 60 a 83 a 10 a 14 a 312 (57 − 4,680) 377 (83 − 5,960) 51 (10–770) 62 (14–981) 890 (118 − 19,000) 721 (188-6,950) 146 (19 − 3,120) 119 (31 − 1,140) 4,110 (493 − 69,100) 2,340 (598 − 20,900) 676 (81 − 11,400) 384 (98 − 3,440) a Threshold 1 is the lower 95% CI of the HC5 calculated for Threshold 2, therefore confidence intervals cannot be reported for this threshold Though there were errors in the data analysis for calculating thresholds, the explanations provided in the supplemental information of the original publication remain correct and consistent with the proposed analytical process. While these corrections change the originally reported threshold values, confidence intervals remain wide, and the conclusions are the same. The management framework and analytical process for threshold derivation remain the same. The underlying data, with the exception of the one study excluded here, remain the same. Thus, the expert assessment assigning high confidence in the management framework and analytical process but low confidence in the thresholds themselves remains applicable.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,760
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,004
Tête enseignante GPT0,216
Écart entre enseignants0,211 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2025
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueMicroplastics and NanoplasticsMême sujetMicroplastics and Plastic PollutionTravaux en français237 207