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Record W4285406944 · doi:10.53730/ijhs.v6ns5.9385

Hydrogen isotope

2022· article· en· W4285406944 on OpenAlexaff
Ritu Mishra, Ekampreet Kaur, Domingos Vita, Prachi Avinash, Bikramjit Singh, Ajit Singh, Jaskaran Singh

Bibliographic record

VenueInternational Journal of Health Sciences · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsForensic scienceGeolocationIsotope analysisOfficerData scienceComputer scienceEcologyArchaeologyGeographyBiologyWorld Wide Web

Abstract

fetched live from OpenAlex

Stable isotope analysis is a valuable tool in forensic investigation. Recently, isotopic investigation is in great trend, Forensic discipline is making use of multi-purpose isotopic profiles along with isotopic landscapes or isoscapes from body tissues. These isotopes help in predicting the geographical location or origin of the unidentified body. Isotope analysis is a commendable and powerful tool for geolocation and can provide investigative leads to the investigating officer as well as forensic experts. This review article basically focuses on the hydrogen isotopes and their applications in forensic science. Being a bio-element, it is ubiquitous and has immense biological and chemical significance. We have discussed the role of hydrogen isotopes in different disciplines of forensic science such as forensic biology, wildlife forensics, forensic anthropology, forensic chemistry and toxicology etc. and the newer advancements that are employed in this discipline for making the analysis more accurate and robust. This field is still in its growing stage and hence, with more advancements, it will provide a great aid in forensic investigation.

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 categoriesScience and technology studies, Insufficient 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: none
Teacher disagreement score0.891
Threshold uncertainty score0.999

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 studies0.0010.005
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.063
GPT teacher head0.346
Teacher spread0.283 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations1
Published2022
Admission routes1
Has abstractyes

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