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Record W7033083889

Podcast - No pets, provincial meets federal, smart carts and the Grey Cup

2019· other· en· W7033083889 on OpenAlexaboutno aff

Bibliographic record

VenueInternet Archive (Internet Archive) · 2019
Typeother
Languageen
FieldArts and Humanities
TopicDiverse Musicological Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPrime ministerParliamentGeorge (robot)Administration (probate law)Newspaper
DOInot available

Abstract

fetched live from OpenAlex

Hamilton City Hall might have to say goodbye to Mayor Eisenberger's dog Dash, after a debate by the city's audit, finance and administration committee lead to most of the eight councillors speaking out against the idea of a dog-friendly workplace. Instead, they voted 6-2 to ask staff to prepare a blanket \"no-pets policy\" for municipal facilities.Guest: Brad Clark, Ward 9 Councillor for the City of Hamilton.The Prime Minister of Canada and the Premier of Ontario are set to meet today. Doug Ford has positioned himself as a peacemaker of sorts, looking bring a sense of unity to Canadian politics. Prime Minister Trudeau shares these goals but, given the history between the two - and Trudeau's comments about Ford, on the campaign trail - what can we expect from today's meeting?Guest: Richard Brennan, retired journalist with the Toronto Star. Covered Queen's Park and Parliament Hill.Tired of using the self-checkout at grocery stores? Don't feel like talking to another human? Just don't have time for the lines? Then the new high-tech shopping carts being tested at one Sobeys in Oakville might be just what you want! The smart carts can scan their items on the spot, track their total bill and accept payment.Guest: Mathieu Lacoursiere, Sobeys Vice-President, Retail Support.One of the Ticats fans that has trekked out to Calgary is our very own Bill Kelly (hence Rick being your host.) We checked in with Bill. Guest: Bill Kelly, host of The Bill Kelly Show,

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.183
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.004
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0250.008

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 head0.031
GPT teacher head0.213
Teacher spread0.182 · 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; both teacher heads agree on what is shown here.

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
Published2019
Admission routes1
Has abstractyes

Explore more

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