Combinatorial Pattern Matching: 11th Annual Symposium. CPM 2000, Montreal, Canada, June 21-23, 2000, Proceedings
Bibliographic record
Abstract
Invited Lectures.- Identifying and Filtering Near-Duplicate Documents.- Machine Learning for Efficient Natural-Language Processing.- Browsing around a Digital Library: Today and Tomorrow.- Summer School Lectures.- Algorithmic Aspects of Speech Recognition: A Synopsis.- Some Results on Flexible-Pattern Discovery.- Contributed Papers.- Explaining and Controlling Ambiguity in Dynamic Programming.- A Dynamic Edit Distance Table.- Parametric Multiple Sequence Alignment and Phylogeny Construction.- Tsukuba BB: A Branch and Bound Algorithm for Local Multiple Sequence Alignment.- A Polynomial Time Approximation Scheme for the Closest Substring Problem.- Approximation Algorithms for Hamming Clustering Problems.- Approximating the Maximum Isomorphic Agreement Subtree Is Hard.- A Faster and Unifying Algorithm for Comparing Trees.- Incomplete Directed Perfect Phylogeny.- The Longest Common Subsequence Problem for Arc-Annotated Sequences.- Boyer-Moore String Matching over Ziv-Lempel Compressed Text.- A Boyer-Moore Type Algorithm for Compressed Pattern Matching.- Approximate String Matching over Ziv-Lempel Compressed Text.- Improving Static Compression Schemes by Alphabet Extension.- Genome Rearrangement by Reversals and Insertions/Deletions of Contiguous Segments.- A Lower Bound for the Breakpoint Phylogeny Problem.- Structural Properties and Tractability Results for Linear Synteny.- Shift Error Detection in Standardized Exams.- An Upper Bound for Number of Contacts in the HP-Model on the Face-Centered-Cubic Lattice (FCC).- The Combinatorial Partitioning Method.- Compact Suffix Array.- Linear Bidirectional On-Line Construction of Affix Trees.- Using Suffix Trees for Gapped Motif Discovery.- Indexing Text with Approximate q-Grams.- Simple Optimal String Matching Algorithm.- Exact and Efficient Computation of the Expected Number of Missing and Common Words in Random Texts.- Periods and Quasiperiods Characterization.- Finding Maximal Quasiperiodicities in Strings.- On the Complexity of Determining the Period of a String.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.075 | 0.040 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".