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Enregistrement W6947768451 · doi:10.48336/sbsz-sx02

Application of the POLARIS methodology to historic ice-class ship operations in freshwater lake ice

2024· article· en· W6947768451 sur OpenAlexaffabout

Notice bibliographique

RevueMemorial University Research Repository (Memorial University) · 2024
Typearticle
Langueen
DomaineComputer Science
ThématiqueResearch Data Management Practices
Établissements canadiensMemorial University of Newfoundland
Organismes subventionnairesnon disponible
Mots-clésSea iceContext (archaeology)Drift iceIce formationSampling (signal processing)Arctic ice pack

Résumé

récupéré en direct d'OpenAlex

The primary objective of this work is to examine ship operations in freshwater versus sea ice in the context of evaluating appropriate regulatory guidelines, through analysis of historic data for the North American (Laurentian) Great Lakes region, a heavily trafficked freshwater waterway that is crucial for the functioning of Canada’s industrial heartland. The first goal of this analysis was to characterize expected ice conditions that could be found within the region through aggregating and sampling data from Canadian Ice Service ice charts over the 10-year study period, which includes the ice seasons from 2010 to 2019. This was followed by an analysis of ship traffic in the region during the same period through the use of historical archived AIS data. Lastly, the POLARIS methodology, an internationally accepted means of guiding ship operators in specific sea ice conditions, was applied to the historic ship operations described by the available AIS data to provide a comparison of historic operator decisions in lake ice to existing guidelines for operations in sea ice of similar thickness and concentration. The characterization of the regional ice conditions during the studied period was intended to provide additional context for the ship traffic analysis for comparison against typical local ice conditions along shipping routes. As existing reviewed literature previously indicated, this analysis clearly affirmed that there is significant year-to-year variability in the potential severity and duration of a given ice season in the Great Lakes. Results obtained from the analysis of historic ship traffic in the region and the application of the POLARIS methodology to this data provided valuable insights into the nature of current ship operations in ice in the Great Lakes. Overall, the trends observed suggest that current practices are well aligned with POLARIS guidelines for sea ice (89% of ice operations are in positive RIO values) and that risk mitigating measures currently used in the Great Lakes (such as icebreaker support and speed reductions when transiting through ice) are compatible with the approaches recommended in POLARIS. However, it is recommended that a more detailed analysis of the correlation between historical ship operations and icebreaking activity in specific regions be conducted to provide a better understanding of the degree to which ships operate in managed ice conditions. Further exploration of the POLARIS guidelines in the context of adapting mitigating measures into operational guidance for freshwater ice is also recommended, given the known differences in material properties of sea ice versus freshwater ice. Since it is not evident how such differences in ice types would translate into differences between the current POLARIS method and a modified “Freshwater POLARIS”, additional research is needed to assess the impact of differences in ice properties in terms of potential for ship damage and appropriate speed limits, as well as assessing the need for possible modification of Risk Index Values for lake ice types. In summary, the results of this work do suggest that the development of specifically tailored POLARIS-like guidelines presents a promising approach to aid ship operations in lake ice conditions similar to that found within the Laurentian Great Lakes during the studied 10-year period. The potential to codify current best-practices for shipping operations in the Great Lakes into such a modified method would help ensure consistency in the assessment of operational capabilities and limitations for different classes of vessels operating in lake ice. This in turn would provide greater clarity regarding expected mitigating measures and would help support effective decision-making relating to ship operations in ice.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,033
Score d'incertitude au seuil0,065

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0050,005
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,103
Tête enseignante GPT0,335
Écart entre enseignants0,232 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
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

Citations0
Publié2024
Routes d'admission2
Résumé présentoui

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