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Record W7027892469

Dum Dums - S02 E16 Project: Under Gardiner

2016· other· en· W7027892469 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBulletin of Miscellaneous Information (Royal Gardens Kew) · 2016
Typeother
Languageen
FieldComputer Science
TopicMetaheuristic Optimization Algorithms Research
Canadian institutionsnot available
Fundersnot available
KeywordsDowntownSpace (punctuation)Public spaceSelection (genetic algorithm)
DOInot available

Abstract

fetched live from OpenAlex

Dum Dums is joined by one of the driving members behind Project: Under Gardiner , an initiative dedicated to revolutionizing the under used public space below the raised expressway, turning it into a multi-use space that will connect the waterfront to the downtown core. Guest: Chris McKinnon ( Manager, Digital & Social Media, Waterfront Toronto) Hosts: Donny Kehoe & Hannan Younis Special Guest Host: Garrett Jamieson Producer: Alex Maveal Listen live every Wednesday night at 7pm ET on: www.radioregent.com --OR-- on the TuneIn app and at tunein.com/radio/Radio-Regent-s31265/ facebook.com/dumdumspodcast @DumDumsRadio www.radioregent.com

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), 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 score0.357
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.4010.044

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 head0.011
GPT teacher head0.227
Teacher spread0.216 · 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