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Record W2917444330 · doi:10.3133/wdrid032

Water resources data, Idaho, 2003; Volume 2. Surface water records for Upper Columbia River basin and Great Basin below King Hill

2004· report· en· W2917444330 on OpenAlexaboutno aff
T.S. Brennan, Andreas Lehmann, I. O'Dell

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicWater Quality and Resources Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHydrology (agriculture)Water yearGroundwaterSurface waterWater qualityStage (stratigraphy)STREAMSEnvironmental scienceGeological surveyStructural basinWater resourcesDrainage basinGeologyGeographyEnvironmental engineeringGeomorphologyEcology

Abstract

fetched live from OpenAlex

Water resources data for the 2003 water year for Idaho consists of records of stage, discharge, and water quality of streams; stage, contents, and water quality of lakes and reservoirs; discharge of irrigation diversions; and water levels and water quality of groundwater. The three volumes of this report contain discharge records for 208 stream-gaging stations and 14 irrigation diversions; stage only records for 6 stream-gaging stations; stage only for 6 lakes and reservoirs; contents only for 13 lakes and reservoirs; water-quality for 50 stream-gaging stations and partial record sites, 3 lakes sites, and 398 groundwater wells; and water levels for 427 observation network wells and 900 special project wells. Additional water data were collected at various sites not involved in the systematic data collection program and are published as miscellaneous measurements. Volumes 1 & 2 contain the surface-water and surface-water-quality records. Volume 3 contains the ground-water and ground-water-quality records. These data represent that part of the National Water Data System operated by the U.S. Geological Survey and cooperating State and Federal agencies in Idaho, adjacent States, and Canada.

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)0.003
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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.882
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.056
GPT teacher head0.255
Teacher spread0.199 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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
Published2004
Admission routes1
Has abstractyes

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