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.
Bibliographic record
Abstract
The workflow's name has been changed from <code>nf-iav-illumina</code> to <code>nf-flu</code> and the official repo for <code>nf-flu</code> will be CFIA-NCFAD/nf-flu going forward. Version 3 is a major release adding a Nanopore influenza sequence analysis subworkflow using IRMA for initial assembly and BLAST against NCBI Influenza DB sequences and optionally, user-specified sequences to identify the top reference sequence for each segment for each sample. A standard read mapping/variant calling analysis is performed: for each sample, Nanopore reads are mapped separately against each gene segment reference sequence using Minimap2; variant calling of read alignments is performed using Clair3; depth-masked consensus sequence is generated using Bcftools. Consensus sequences are BLAST searched against NCBI Influenza (and user-specified sequences) to generate a BLAST summary report and H/N subtyping report. MultiQC is used to summarize results into an interactive HTML report. NOTE: Read mapping/variant calling analysis has not been ported to the Illumina sequence analysis subworkflow. 3.1.0 changes Added back <code>bin/fastq_dir_to_samplesheet.py</code> for Illumina <code>--input</code> samplesheet creation from Illumina FASTQ reads directory Fixed issue #12. Nanopore sample sheet can specify a mix of single FASTQ files and/or directories containing FASTQ files. Different reads with the same sample name will be merged prior to analysis. FASTQs can be GZIP compressed and have the extensions: <code>.fastq</code>, <code>.fq</code>, <code>.fastq.gz</code>, <code>.fq.gz</code>. Updated CI tests to test for this flexible sample sheet handling. Switched to GitHub YAML form for bug report template from Markdown template. CI tests now output <code>results/pipeline_info/</code> and <code>.nextflow.log</code> as artifacts for easier debugging of issues.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.050 | 0.017 |
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 it