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Record W6990662685

Dum Dums - S02 E14 Baby Pain

2016· other· en· W6990662685 on OpenAlexaboutno aff

Bibliographic record

VenueBulletin of Miscellaneous Information (Royal Gardens Kew) · 2016
Typeother
Languageen
FieldHealth Professions
TopicRomani and Gypsy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSick childAssociate editorPatient carePain relief
DOInot available

Abstract

fetched live from OpenAlex

Dum Dums is joined by an expert who runs the The Opportunities to Understand Childhood Hurt [OUCH] Lab at York University, where she studies what effects pain has on infants and babies, and how care givers can help mitigate that trauma in four easy steps. Guest: Dr. Rebecca Pillai Ridell - Associate Professor at York University's Department of Psychology, a Scientific Staff member at Sick Kids (Department of Psychiatry Research), and an Adjunct Associate Professor at the University of Toronto's Department of Psychiatry. 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.

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)0.001
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 score0.637
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 science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.7810.144

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 head0.013
GPT teacher head0.261
Teacher spread0.248 · 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
Published2016
Admission routes1
Has abstractyes

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