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Record W7022619627

Practicums

2004· other· de· W7022619627 on OpenAlexaboutno aff

Bibliographic record

VenueTSpace (University of Toronto) · 2004
Typeother
Languagede
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsnot available
Fundersnot available
KeywordsOrgan transplantationMultidisciplinary approachTransplantationProcess (computing)Health careNeeds assessmentWork (physics)
DOInot available

Abstract

fetched live from OpenAlex

A user needs analysis is a process whereby needs are identified and priorities among them established.The user needs analysis is required in order to evaluate the library's reference services, database training opportunities, and collection development decisions.The project would involve initial research into the process of needs assessment and analysis, particularly in a library setting.The development of a needs assessment questionnaire (online/electronic and mailout).The administration of said questionnaire to members of UHN's Multi Organ Transplant Program.Identification of needs and an analysis of the results, including recommendations for targetted library services for this user group. About the Multi Organ Transplant Program:As the largest transplant program in Canada, the Multi Organ Transplant Program provides a broad spectrum of services currently encompassing heart, lung, liver, kidney and pancreas transplantation as well as highly successful living donor transplant programs.Transplant patients from all organ groups benefit from our team of multidisciplinary health care professionals, most of whom specialize in the field of transplantation, and work exclusively within the Multi Organ Transplant Program.In addition to medicine and nursing, the program currently includes professionals from the following allied health professions: psychiatry, social work, nutrition,

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.744
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.6820.010

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 head0.020
GPT teacher head0.246
Teacher spread0.226 · 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; both teacher heads agree on what is shown here.

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
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueTSpace (University of Toronto)Same topicSurface Modification and SuperhydrophobicityFrench-language works237,207