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Record W2160271224 · doi:10.12927/cjnl.2012.22958

LaRon Nelson – Canada's Rising Star in Global Health

2012· article· en· W2160271224 on OpenAlexvenueaboutno aff
Lynn Nagle

Bibliographic record

VenueNursing leadership · 2012
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsStar (game theory)SociologyPolitical scienceNursingPsychologyMedicinePhysics

Abstract

fetched live from OpenAlex

lEAdErSHIP ProFIlE laron Nelson,* rN, NP, Phd, is clinically trained in the primary care of families, with an emphasis on the care of adolescents.He has practised in various community-based settings, including a local public health STI clinic and correctional facility, and an adolescent health clinic.He was the first African-American man to receive a doctoral degree in nursing from the University of Rochester in May 2010.Dr. Nelson's program of research involves the development of integrated biomedical, behavioural and social/structural interventions for the prevention of HIV and other sexually transmissible infections among socially marginalized groups within African and African Diaspora communities.His current research focuses on understanding how autonomy, supportive counselling strategies, gender-equitable attitudes and the promotion of socio-culturally and developmentally relevant co-parenting can help reduce STI/HIV risk behaviours among non-married adolescent parents in Toronto, Ontario and New York, New York.laron Nelson -Canada's rising Star in Global Health * At the time of this interview, Dr. Nelson announced his imminent departure from the Lawrence S.

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)0.004
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 score0.349
Threshold uncertainty score0.702

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0070.003
Scholarly communication0.0070.003
Open science0.0010.003
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0260.007

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 head0.145
GPT teacher head0.357
Teacher spread0.211 · 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
Published2012
Admission routes2
Has abstractyes

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