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Record W2083769116 · doi:10.1159/000371722

Beneficence and Nonmaleficence in Treating Neonatal Hypoxic-Ischemic Brain Injury

2015· review· en· W2083769116 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDevelopmental Neuroscience · 2015
Typereview
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsWinnipeg Regional Health Authority
Fundersnot available
KeywordsBeneficenceMedicineIntensive care medicinePsychological interventionNeuroprotectionSafeguardingNeonatal encephalopathyHypoxic Ischemic EncephalopathyEncephalopathyRandomized controlled trialNeurosciencePsychologyPsychiatryPathologyNursingPharmacologyAutonomy

Abstract

fetched live from OpenAlex

The successful clinical translation of therapeutic hypothermia offers the tantalizing possibility that further improvements in outcomes may be possible by combining cooling with other neuroprotective drugs. The challenge now is to select from a daunting range of potential treatments. The patient's best interest must be central to ethical decision making at all times. However, the beneficence or nonmaleficence of potential therapies is seldom clear for any individual patient at the time of testing new therapies. Clinical randomized controlled trials are generally acknowledged by the scientific community as the 'gold standard' for evaluating interventions in health care. Therefore, ethical trial design is of the utmost importance. This paper explores contrasting ethical perspectives on how to select new interventions to treat neonatal encephalopathy after perinatal hypoxia-ischemia.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.054
GPT teacher head0.333
Teacher spread0.278 · 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