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Turkey Lakes Watershed - Stream Water Flow

2020· dataset· en· W6907433333 on OpenAlexaffabout

Bibliographic record

VenueGEOSCAN · 2020
Typedataset
Languageen
Field
Topic
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsHydrology (agriculture)WeirSTREAMSWater yearWatershedStreamflowStage (stratigraphy)Flow (mathematics)Water level

Abstract

fetched live from OpenAlex

This dataset contains annual mean stream water flow/discharge data derived from daily means for headwater streams draining forested hillslopes measured at stream catchments C31, C32, C33, C34, C35, C37, C38, C39, C42, C46, C47, C49, and C50 in the Turkey Lakes Watershed, approximately 60 km northwest of Sault Ste. Marie, Ontario, Canada. This data set is recorded as annual mean flow by calendar year (January-December in litres per second), annual mean flow by water year (October to September in litres per second), and annual number of zero flow days by water year. Daily mean flows that were used to derive this data set were recorded from 1981-2012 by the Great Lakes Forestry Centre, and are reported for 1981-2011 due to some inaccuracies throughout the 2012 data. Hydrological gauging stations employ "flow-control" 120 degree V-notch weirs (catchments 31, 33, 34, 37, 39, 42, 46, and 47), 90 degree V-notch weirs (catchments 32, 35, and 49), and 60 degrees V-notch weirs (catchment 38) to facilitate monitoring of stream discharge. Water "stage" or depth within the structure (e.g. in the pool behind the weir notch) is automatically and continuously recorded by chart recorders (Leupold & Stevens A-71 SE Water Level Recorder) from 1981-2003. Capacitance rods (Trutrack WT-HR 1000) installed in stilling wells replaced the chart recorders over the period of 2002 to 2003 and were used until 2012. The capacitance rods logged data at 1 hour intervals for the majority of their use and then averaged to a daily rate. Manual stage measurements have been taken intermittently when synoptic water chemistry samples were taken throughout the years. Stage data are then converted to a continuous record of flow using the relationship between stage and discharge measurements.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.246
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.254

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 head0.014
GPT teacher head0.230
Teacher spread0.217 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2020
Admission routes2
Has abstractyes

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