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Animating Ground Water Levels with Excel

2003· article· en· W2057223890 on OpenAlex

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

VenueGround Water · 2003
Typearticle
Languageen
FieldDecision Sciences
TopicMultidisciplinary Science and Engineering Research
Canadian institutionsEnvironment and Climate Change CanadaFuture Earth
Fundersnot available
KeywordsMacroComputer scienceComputer graphics (images)Microsoft excelGraphicsAnimationMs excelVisualizationTable (database)SoftwareData visualizationFrame (networking)Engineering drawingDatabaseOperating systemProgramming languageSoftware engineeringData miningEngineeringTelecommunications

Abstract

fetched live from OpenAlex

This note describes the use of Microsoft Excel macros (programs written in Excel's internal language, Visual Basic for Applications) to create simple onscreen animations of transient ground water data within Excel. Compared to many specialized visualization software packages, the use of Excel macros is much cheaper, much simpler, and can rapidly be learned. The Excel macro can also be used to create individual GIF files for each animation frame. This series of frames can then be used to create an AVI video file using any of a number of graphics packages, such as Corel PhotoPaint. The technique is demonstrated through a macro that animates changes in the elevation of a water table along a transect over several years.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.375
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.003

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 head0.167
GPT teacher head0.378
Teacher spread0.211 · 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