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Record W1667500860 · doi:10.1109/pes.2003.1270982

Deep lake water cooling

2004· article· en· W1667500860 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

Venue2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491) · 2004
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsFuelCell Energy (Canada)
Fundersnot available
KeywordsHypolimnionWater cooledEnvironmental scienceSpring (device)Layer (electronics)Deep waterDeep ocean waterHydrology (agriculture)Water coolingMeteorologyGeologyMaterials scienceEngineeringGeographyMechanical engineeringOceanographyEutrophication

Abstract

fetched live from OpenAlex

Deep lake water cooling is based on a very simple physical property of water: water is heaviest at a temperature of 4/spl deg/C, and is lighter at temperatures above and below this. As a result, any deep body of water will have a permanent layer of cold (4/spl deg/C) water at a depth of 83 meter, called the "hypolimnion", and this layer is renewed every spring and fall as the surface is warmed and cooled with the season: when the surface hits this critical 4/spl deg/C temperature, it sinks, and adds to the existing cold layer. This layer can provide a permanent renewable source of totally natural cooling. The deep lake water cooling project has it all: it makes business sense, it is environmentally responsible, and it will be reliable. Customer contracts are being negotiated right now and several new landmark buildings are expected to join Enwave's expanding cooling network over the next few months.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.135
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.227
Teacher spread0.218 · 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