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Record W2311756675 · doi:10.14288/1.0052159

Variants of the Consecutive-Ones Property motivated by the reconstruction of ancestral species

2012· article· en· W2311756675 on OpenAlexaff
Murray Patterson

Bibliographic record

VenuecIRcle (University of British Columbia) · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenome Rearrangement Algorithms
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsProperty (philosophy)Evolutionary biologyGenealogyBiologyComputer scienceArtificial intelligenceHistoryEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

The polynomial-time decidable Consecutive-Ones Property (C1P) of binary matrices, formally introduced in 1965 by Fulkerson and Gross, has since found applications in many areas. In this thesis, we propose and study several variants of this property that are motivated by the reconstruction of ancestral species. We first propose the Gapped C1P, or the (k,delta)-C1P: a binary matrix M has the (k,delta)-C1P for integers k and delta if the columns of M can be permuted such that each row contains at most k blocks of 1's and no two neighboring blocks of 1's are separated by a gap of more than delta 0's. The C1P is equivalent to the (1,0)-C1P. We show that for every bounded and unbounded k ≥ 2, delta ≥ 1, (k,delta)≠ (2,1), deciding the (k,delta)-C1P is NP-complete [Golberg et al., 1995]. We also provide an algorithm for a relevant case of the (2,1)-C1P. We then study the (k,delta)-C1P with a bound d on the maximum number of 1's in any row (the maximum degree) of M. We show that the (d,k,delta)-C1P is polynomial-time decidable when all three parameters are fixed constants. Since fixing d also fixes k (k ≤ d), the only case left to consider is the (d,k,infinity)-C1P (when delta is unbounded). We show that for every d > k ≥ 2, deciding the (d,k,infinity)-C1P is NP-complete. We also study the C1P with Multiplicity (mC1P), introduced by Wittler and Stoye [2010]: a binary matrix M on columns S = {1,..,n} has the mC1P for multiplicity vector m:S→ ℕ if there is a sequence sigma on S such that (i) sigma contains each s ∈ S at most m(s) times, and (ii) for each row r of M, the set of columns that have entry 1 in r form at least one subsequence of sigma. We show that deciding the mC1P, and two restricted variants thereof, are NP-complete, for M having maximum degree 3 (6 for one of the variants), and for m(s) ≤ 2 for all s ∈ S. We also give a tractability result for the mC1P that is motivated by handling telomeres in the reconstruction of ancestral species. Finally, we study the Generalized Cladistic Character Compatibility (GCCC) Problem, a generalization of the Perfect Phylogeny Problem [Semple and Steel, 2003] introduced by Benham et al. [1995]. We use the structure of the PQ-tree [Booth and Leuker, 1976] associated with the C1P to give algorithms for several cases of the GCCC Problem.

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)0.003
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.007
Open science0.0030.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.166
Teacher spread0.155 · 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 designTheoretical or conceptual
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

Citations2
Published2012
Admission routes1
Has abstractyes

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