Panel A: Comparative analysis of splicing site sequences in exon 32, 33, Δ33 and 34 flanking exon-intron junctions as well as prediction of impact of SNP32 (c
Bibliographic record
Abstract
Copyright information:Taken from "Mutation analysis and characterization of ATR sequence variants in breast cancer cases from high-risk French Canadian breast/ovarian cancer families"BMC Cancer 2006;6():230-230.Published online 29 Sep 2006PMCID:PMC1599749.5739-4del9+T) on exon 34 acceptor site. Panel B: Comparative analysis of splicing site sequences in exon 41, insΔInt41 and exon 42 flanking exon-intron junctions as well as prediction of impact of SNP37 (c.7041+8G/A) on exon 41 donor site. Splice Site Prediction Program using Neural Network (SSPNN) score values are indicated in parenthesis below each sequence. Exonic nucleotides are represented by uppercase letters while intronic sequences are represented by lowercase letters. m = c or a, r = a or g, y = t or c and n = any nucleotide. N.A. = value not available. Consensus sequences of acceptor and donor sites were described by Burge et al. 1999 [84].
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.069 | 0.013 |
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".