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Record W4392116736 · doi:10.15173/m.v1i40.3250

Dr. David Lysecki

2022· article· en· W4392116736 on OpenAlexvenueaboutno aff
Dalraj Dhillon, Eric Zhang, J. Wang, Matthew Lynn

Bibliographic record

VenueThe Meducator · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicMedical History and Research
Canadian institutionsnot available
Fundersnot available
KeywordsPeer reviewMedicinePolitical scienceLaw

Abstract

fetched live from OpenAlex

Pediatric palliative care is often an overlooked field of medicine. As terminally ill children make up a small proportion of patients in Canada, a less robust network of resources is available to deliver end-of-life care for these patients. To gain a better insight into this field, we sat down with Dr. David Lysecki, a pediatric palliative care physician at McMaster Children’s Hospital. He is also the founder and head of the Quality of Life & Advanced Care program at McMaster Children’s Hospital and the Division of Pediatric Palliative Medicine in the McMaster University Department of Pediatrics.

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)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.055
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0550.027

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 head0.082
GPT teacher head0.289
Teacher spread0.207 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2022
Admission routes2
Has abstractyes

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