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Record W1612100356

Using the Geology of Your Neighbourhood and City for Geoscience Outreach

2009· article· en· W1612100356 on OpenAlexaffvenueabout
W.A.D. Edwards

Bibliographic record

VenueGeoscience Canada · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsAlberta Energy
Fundersnot available
KeywordsHumanitiesArtCartographyGeography
DOInot available

Abstract

fetched live from OpenAlex

Most Canadians live, work and attend school in urban areas. Your neighbour-hood has wonders such as snow-bank stratigraphy, sidewalk sedimentology, and building stone. Urban fieldtrips require little money and little time to run and they can inspire participants. An inner-city school teacher confirmed my belief in urban fieldtrips when she said, “I’ve never been able to take my students anywhere but we can now take a city bus downtown and see the world. Thank You!” So open your eyes to the grand world of geology around you. Take others on a neighbourhood trip; you will inspire, motivate and educate them. SOMMAIRE La majorite des Canadiens vivent, travaillent et etudient en milieu urbain. Votre voisinage meme offre des occasions d’emerveillement comme des exemples de stratigraphie de bancs de neige, de sedimentologie des trottoirs, et de pierres de construction. Les excursions urbaines sont peu couteuses, prennent peu de temps et peu-vent s’averer stimulantes pour leurs participants. Une enseignante d’une ecole en milieu urbain a confirme mes idees sur les excursions urbaines lorsqu’elle a declare, « Je n’avais jamais pu sortir mes eleves, mais maintenant, nous pouvons prendre l’autobus et voir le monde, grâce a vous. » Soyez donc a l’affut de l’univers geologique qui pointe dans votre milieu. Amener les gens de votre entourage en excursion; vous les aurez interesses, motives et eduques.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score0.768

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.246
Teacher spread0.225 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2009
Admission routes3
Has abstractyes

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