MétaCan
Menu
Back to cohort
Record W7128698002 · doi:10.26071/a57715a9-cacd-4437

CTD Data for the 2022 COR2212 Cruise in the Saint-Lawrence Estuary

2025· dataset· fr· W7128698002 on OpenAlex
Jean‐Carlos Montero‐Serrano, Florian Jacques, Richard Saint-Louis, Camille Bernier, Khouloud Baccara, Christian Boutot, Sylvain Blondeau, Audrey Limoges, Natalie Pisciotto, Alexandre Normandeau

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

VenueOGSL repository · 2025
Typedataset
Languagefr
Field
Topic
Canadian institutionsUniversité LavalGeological Survey of CanadaUniversité du Québec à Rimouski
Fundersnot available
KeywordsCTDEstuaryTurbidityTerrigenous sedimentWater columnSedimentPlankton

Abstract

fetched live from OpenAlex

The objective of mission COR2212 (id: 2022_26) is to monitor natural risks during sediment remobilization and impacts on primary production dynamics in the St. Lawrence Estuary. As part of this mission, vertical CTD (conductivity, temperature, depth) profiles were taken in several areas between Forestville and Pointes-des-Monts (St-Lawrence Estuary). The CTD was also equipped with sensors to measure dissolved oxygen, fluorescence (chl-a), and water clarity in the water column. In addition, surface sediment samples and sediment cores were taken (mainly using a box corer) to determine the sources of the main terrigenous inputs into the estuary, to determine the concentrations of major and trace elements in surface sediments, to document the recurrence of turbidity currents over the last millennium, and to map the distribution of A. catenella in sediments. In addition, samples were taken using a plankton net to determine the abundance and spatial variability of harmful algae (A. catenella). This dataset is part of the EDMS-ISMER-QO collection

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)0.006
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.044
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0170.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.001

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 head0.038
GPT teacher head0.312
Teacher spread0.274 · 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

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueOGSL repositoryFrench-language works237,207