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Record W7024937902

Tunnel Valley Genesis and Subglacial Dynamics in South-Central Ontario

2019· dissertation· en· W7024937902 on OpenAlexaboutno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2019
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
Fundersnot available
KeywordsGlacial periodQuaternaryContext (archaeology)PleistoceneInfillDrumlin
DOInot available

Abstract

fetched live from OpenAlex

Glacial sediments are found across formerly glaciated regions across the world and host a variety of important resources, ranging from groundwater to hydrocarbons, aggregate material, and mineral deposits. In southern Ontario, Canada, thick successions (up to 200 m) of Quaternary glacial sediments are truncated by large valleys (>30km long, 2 to >8.5 km wide, and up to 200m deep) that formed subglacially and have characteristic morphology and infill stratigraphy. These valleys are interpreted as (a new class of) tunnel valleys and strongly affect groundwater resources and flow systems at local and regional scales. The overall context of the valleys is evaluated through an introduction to the study area, objectives, and background information on subglacial systems and geologic history of south-central Ontario (Chapter 1). Interpretation of valley genesis in Simcoe County is provided through an integrated, multi-faceted approach, involving: description of the morphology and sediment infill succession within the valleys from surficial mapping, sedimentological logging of continuously-cored boreholes, and geophysical surveys (Chapter 2); delineation and characterization of seismic architecture from high-resolution lake-based sub-bottom profiles in one of the valleys (Chapter 3); detailed site-scale field description of the internal characteristics of the regional Late Wisconsin till sheet in various subglacial settings (Niagara Escarpment, uplands, lowlands; Chapter 4); comparison of the characteristics of the subglacial bed within the study area to adjacent regions in southern Ontario (Chapter 5); and a synthesis of the major findings from all the different components of this investigation and suggestions for future work to shed further light on several questions that arise from this study (Chapter 6). Together, key data from these studies of tunnel valleys and related deposits – a near-continuous till sheet on the surface of uplands and along the flanks and floors of the tunnel valleys, multi-stage drumlinization of the till sheet following development of the tunnel valleys, variations in internal facies and physical properties within the till sheet in different subglacial settings, localized distribution of coarse-grained tunnel valley in-fill sediments, and gradational upward transitions from tunnel valley in-fills to fossiliferous proglacial lacustrine sediments – indicate multiple phases of subglacial meltwater, and direct subglacial, erosion and deformation contributed to the development of the valleys over a protracted time period during the Late Wisconsin. Landform and sediment associations within the valleys in Simcoe County and surrounding parts of the bed of the former Laurentide ice sheet in south-central Ontario, are inconsistent with previous conceptualizations involving the presence of large (>1000 km2) subglacial lakes and the storage and discharge of regional-scale subglacial meltwater sheetfloods followed by ice stagnation. This study provides new data and insight to help refine reconstructions and better understand the evolution of past ice dynamics and subglacial processes, evaluate competing theories of regional landscape evolution, and provide new conceptual and (hydro)stratigraphic frameworks for future hydrogeological investigations related to groundwater exploration and use.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.189
Teacher spread0.177 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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