Pivot Strategy of a Seed-Stage Venture Company: Analysis of Zoo Service Business by Bayesian Network
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
KAI Inc. is a seed-stage company established in November 2019 with a focus on improving animals' quality of life. Initially, they developed feeding devices and systems, animal play equipment, and exercise promotion systems. However, the COVID-19 pandemic led to the closure of zoos, prompting KAI Inc. to pivot. They decided to create an "Online Zoo" concept, which emerged from an accelerator program they participated in. Through collaboration with Shirotori Zoo in Kagawa Prefecture, they conducted a survey in April 2021 to gather feedback from potential users. The study involved constructing a causality model and conducting Bayesian network analysis to understand user preferences, desired animals to see, and acceptable viewing prices. The findings helped clarify the target audience, preferred animals, and pricing, serving as the foundation for developing a business plan.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.013 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it