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Deaths Due to Electrocution-A Retrospective Study

2019· article· en· W2968560482 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

VenueMedico-Legal Update · 2019
Typearticle
Languageen
FieldComputer Science
TopicInternet of Things and AI
Canadian institutionsnot available
Fundersnot available
KeywordsElectrocutionMedicineRetrospective cohort studyForensic engineeringMedical emergencyEmergency medicineEngineeringSurgery

Abstract

fetched live from OpenAlex

Retrospective analysis of deaths because of electric shock from the medico-legal death records our college i.e. J.N.M.C., A.M.U., Aligarh, Uttar Pradesh, India. Most of the deaths were of men having the age in between 11–50 years. All deaths were inadvertent and most part of them were during the time of monsoon as compared to the deaths in western countries where, baths, warmers or hair dryers were the source of electric shocks. The death rate reported because of electric shock was 0.34 per lakhs (100000) of the population in the present study as against the figures of 0.94 and 0.14 from Bulgaria and Canada respectively. A large portion of the deaths were either prompt or quick. It implies that individuals living at home did not have basic knowledge of dangers of electric shock. In this way mindfulness about utilization of good quality electric machines is the need of great importance.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.836
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.003

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 head0.004
GPT teacher head0.229
Teacher spread0.225 · 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