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Record W2054684894 · doi:10.2308/jeta-51114

Some Clarification to the Evolution of the Electronic Spreadsheet

2014· article· en· W2054684894 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Emerging Technologies in Accounting · 2014
Typearticle
Languageen
FieldComputer Science
TopicSpreadsheets and End-User Computing
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFortranComputer scienceElectronic computerCorporationPersonal computerProgramming languageOperations researchVolume (thermodynamics)Computer programSoftware engineeringOperating systemFinanceMathematicsBusiness

Abstract

fetched live from OpenAlex

ABSTRACT As early as 1961 Mattessich suggested (in an article in The Accounting Review) to use budget simulation in form of a computerized spreadsheet. This was followed up by him in a mathematical model, outlined in his book Accounting and Analytical Methods (Mattessich 1964a) with a corresponding computer program (in FORTRAN IV on mainframe computers), including illustrations in a companion volume (Simulation of the Firm through a Budget Computer Program, Mattessich 1964b). Five years later (in 1969) Rene Pardo and Remy Landau co-presented “LANPAR” (LANguage for Programming Arrays at Random) at Random Corporation. This electronic spreadsheet type was also used on mainframe computers for budgeting at Bell Canada, AT&T, Bell operating companies, and General Motors. In 1978, Dan Bricklin and Robert Frankston introduced VisiCalc, the first commercialized spreadsheet program for personal desktop (Apple) computers. This program became the trailblazer for future developments of electronic spreadsheets.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score0.529

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0030.001
Research integrity0.0000.001
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 head0.237
Teacher spread0.229 · 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