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Record W6931724461 · doi:10.5282/rcc/9272

“The battle of geological experts”: Water Flow and Tunneling within a Welsh Mountain

2021· article· en· W6931724461 on OpenAlexaff

Bibliographic record

VenueUniversitätsbibliothek der LMU · 2021
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDrainageWelshBattleCarboniferousDitchFlood mythWater flowLead (geology)

Abstract

fetched live from OpenAlex

In the nineteenth and early twentieth centuries, Halkyn Mountain in north-east Wales was one of the most important lead mining areas in Britain. Mining had a dramatic effect on the landscape and created distinct communities. As lead miners probed deeper to reach new veins, water levels rose in shafts and passages. Empowered by Acts of Parliament, mine owners and syndicates embarked on drainage schemes and extensive tunneling, which enabled the flow of water away from the mines and access to the ore. Above ground, there were local anxieties over the spread of mine shafts and the impact of drainage tunnels on local water supplies. Tunnel expansion was subject to Parliamentary hearings and geologists appeared as expert witnesses to discuss the nature of carboniferous limestone and underground water flow.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.986
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.020
Scholarly communication0.0050.004
Open science0.0010.004
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.014
GPT teacher head0.232
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

Classification

machine, unvalidated

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

Study designQualitative
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
Published2021
Admission routes1
Has abstractyes

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