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Record W7052821344

Tech And Cannabis Industry

2023· other· en· W7052821344 on OpenAlexaboutno aff

Bibliographic record

VenueBulletin of Miscellaneous Information (Royal Gardens Kew) · 2023
Typeother
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsCompetitor analysisAuditAutomotive industryVariety (cybernetics)Government (linguistics)Financial AuditCash flowDelegationFinancial services
DOInot available

Abstract

fetched live from OpenAlex

With hosts Wolfgang Klein and Jack Hardill. Guests:?Richard Davis, President Investor and Strategy Unity Technologies I sit at the intersection of essentially every part of Unity, I am a trusted advisor up and down the organization by providing a 360-degree view of how our ecosystem of investors, competitors and customers think and respond. Skills: Strategic Planning - Leadership - Management - Mergers & Acquisitions (M&A) - Forecasting - Investor Relations - Planning Budgeting & Forecasting - Cash Flow Forecasting - Pre-IPO - Financial Structuring - Business Development - Financial Markets - Accounting - Financial Analysis - Capital Structure - CFOs - Board Development - Public SpeakingMatt Bottomley joined Canaccord Genuity in 2015 and is now an analyst covering the cannabis industry (both in Canada and internationally). Previously, Matt worked as a financial consultant in commercial litigations, preparing business valuations and damage quantification reports with an emphasis on the Canadian pharmaceutical industry. Matt also spent five years in the audit and assurance group at PricewaterhouseCoopers, covering a variety of industries including manufacturing, real estate, automotive and healthcare. Matt is a Chartered Professional Accountant and Chartered Business Valuator and has an Honours Bachelor of Commerce from McMaster University.

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 categoriesInsufficient 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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.031
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0370.006

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 head0.004
GPT teacher head0.171
Teacher spread0.167 · 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
Published2023
Admission routes1
Has abstractyes

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