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Record W104114705

Technology marketing plan for laboratory services to sustain a translational research centre

2006· dissertation· en· W104114705 on OpenAlexfundno aff
Chris H. Sterzinger

Bibliographic record

VenueSummit (Simon Fraser University) · 2006
Typedissertation
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsnot available
FundersSimon Fraser University
KeywordsMarketing planPlan (archaeology)Translational researchServices marketingEngineeringMarketingBusinessEngineering managementGeographyService (business)BiotechnologyBiologyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Translational laboratories provide leading edge life science research by utilizing the latest equipment and top technical talent. The high cost of maintaining this techno-structure creates a sustainability challenge. This study was completed for the iCAPTURE Centre at St. Paul’s Hospital. In 2005, the centre raised $ 282,000 in service revenues but needed to recover $ 755,000 for equipment upkeep costs. iCAPTURE requires a formalized market marketing plan to increase service revenues from biotechnology, pharmaceutical, and academic markets. External analysis of iCAPTURE’s industry and internal analysis were performed. Analytical frameworks were used to formulate a strategic marketing plan. Considering iCAPTURE’s limited marketing resources, short-term and long-term target market segments were identified. Recommendations were made for the implementation of short-term and long-term actions. The systematic framework resulted in rationalized planning designed to achieve cost recovery goals by using a differentiation focused niche strategy. This plan requires financial support and additional organizational infrastructure.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.225
Teacher spread0.217 · 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 designNot applicable
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
Published2006
Admission routes1
Has abstractyes

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