MétaCan
Menu
← Back to cohort

The Medley Interlisp Project: Reviving a Historical Software System

2025· article· W7127468921 on OpenAlexaff
Eleanor Young, Larry Masinter, Herb Jellinek, Eric Kaltman, Abhik Hasnain

Bibliographic record

Venuenot available
Typearticle
Language
FieldComputer Science
TopicSoftware Engineering Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBlueprintSoftwareSoftware systemUSableSoftware development

Abstract

fetched live from OpenAlex

The Medley Interlisp project is an endeavor in software recovery, preservation, and development. It aims to render Medley Interlisp, the final release of Interlisp, usable on modern operating systems and hardware environments, and to selectively add modern capabilities to Medley while conserving its value as a historically groundbreaking system. This paper describes the Medley Interlisp project’s past and ongoing operations, decisionmaking, and the unique issues encountered in the process of restoring a historic software system to modern computing environments. The Medley Interlisp project’s five years of hardships, successes, and discoveries regarding the unique issues of software recovery will help to create a blueprint from which similar longterm historical software recovery projects may benefit. Index Terms-software recovery, Interlisp, early programming, programming languages and software, non-profit organization.

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)0.006
metaresearch head score (Gemma)0.014
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.005
Scholarly communication0.0050.008
Open science0.0020.006
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0090.002

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 head0.020
GPT teacher head0.279
Teacher spread0.259 · 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
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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same topicSoftware Engineering Research→French-language works237,207→