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Record W1854056485 · doi:10.1109/istcs.1993.253458

The mortgage problem

2002· article· en· W1854056485 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicOptimization and Search Problems
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCompetitive analysisLine (geometry)Interest rateSequence (biology)Database transactionEconomicsComputer scienceUpper and lower boundsMathematical economicsActuarial scienceMonetary economicsMathematicsChemistryDatabaseMathematical analysis

Abstract

fetched live from OpenAlex

Mortgage refinancing is a complex real-life problem involving a sequence of decisions, each of which requires a trade-off between the transaction cost associated with refinancing and the benefit of obtaining a lower interest rate. The authors present a simplified mathematical model of this problem. Within this model, they seek to determine the best possible competitive ratio achievable by an on-line mortgage refinancing policy. The main results are the following: under the assumption that the initial mortgage is obtained with an interest rate M and that future interest rates cannot decrease below m>or=0, they show a lower bound r= Omega (/sup 1nM///sub (m+1)lnlnM/) on the competitive ratio of any mortgage refinancing policy. Then they give an on-line policy that is optimal in some special cases, including the cases m=0 and M<(1+/sup 2///sub m+1/)(m+2). For other values of m, M the on-line policy is proven to be r/sup 2/-competitive.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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)0.000
metaresearch head score (Gemma)0.000
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: Methods · Consensus signal: Methods
Teacher disagreement score0.835
Threshold uncertainty score0.624

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 science0.0010.000
Research integrity0.0000.000
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 head0.028
GPT teacher head0.229
Teacher spread0.201 · 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

Quick stats

Citations10
Published2002
Admission routes1
Has abstractyes

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