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Record W614399814

Business Plan for Peloton: A Software Product Firm Focused on the Credit Union Industry in the United States

2012· article· en· W614399814 on OpenAlexaboutno aff
Daniel Flippance

Bibliographic record

VenueSummit (Simon Fraser University) · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinTech, Crowdfunding, Digital Finance
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessProduct (mathematics)Plan (archaeology)Credit unionSoftwareCommerceMarketingIndustrial organizationFinanceComputer science
DOInot available

Abstract

fetched live from OpenAlex

This business plan proposes a new software firm, Peloton Software Inc., the product of which will meet an evident need of credit unions with 30-200 employees based in the United States. The hosted software product, based on Microsoft SharePoint, will improve top-down communication and horizontal collaboration. The firm will be composed of a development office in Vancouver, BC and a sales office in Los Angeles, CA, and will sell to credit unions and their credit union service organizations in California, Texas and Michigan. The two founders have a combined 30 years experience in the software and credit union industries. Daniel Flippance is an experienced software architect and Bob Smith is a highly motivated manager and salesman. The firm will be a boot-strapped start-up, using rapid development cycles with excellent customer feedback to develop the exact product customers need.

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)0.000
metaresearch head score (Gemma)0.001
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: Other
Teacher disagreement score0.074
Threshold uncertainty score0.247

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0740.016

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 head0.032
GPT teacher head0.210
Teacher spread0.178 · 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 routes1
Has abstractyes

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