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Record W2170724380 · doi:10.1017/s0266462309090357

The history of the <i>International Journal of Technology Assessment in Health Care</i>

2009· article· en· W2170724380 on OpenAlexaff
Egon Jonsson, Stanley Reiser

Bibliographic record

VenueInternational Journal of Technology Assessment in Health Care · 2009
Typearticle
Languageen
FieldMedicine
TopicAdvances in Oncology and Radiotherapy
Canadian institutionsInstitute of Health EconomicsUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsDilemmaHealth technologyMedicineEngineering ethicsBiomedical technologyHealth carePolitical scienceEngineeringLawPhilosophy

Abstract

fetched live from OpenAlex

The 1970s and early 1980s was the period in which high technology medicine became dominant. It had begun in the late 1950s with the introduction of effective artificial respiratory technology. This gave physicians, patients, and families the hope that the threats to fundamental life processes such as breathing could be countered by technology, and the dilemma of both meeting its costs and the ethical challenges of how to remove it when its use no longer produced benefits.

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)0.020
metaresearch head score (Gemma)0.044
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.982
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.044
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.009
Science and technology studies0.0030.017
Scholarly communication0.0180.009
Open science0.0010.003
Research integrity0.0060.012
Insufficient payload (model declined to judge)0.0080.002

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 head0.010
GPT teacher head0.422
Teacher spread0.412 · 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.

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

Citations6
Published2009
Admission routes1
Has abstractyes

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Same venueInternational Journal of Technology Assessment in Health CareSame topicAdvances in Oncology and RadiotherapyFrench-language works237,207