Bibliographic record
Abstract
A abzymes 341 ACeDB 30,269 Acnuc 276 active sites, prediction of 317f adenomatous polyposis, familial -81,86 adenomatous polyposis coli gene (APC) 81 adenoviral transfer 85 adult polycystic kidney disease (APKD) 68 AFLP see amplified fragment length polymorphism agarose gel simulation 344 AGRICOLA 267 agrifood, and genomics 127ff -ESTs and microarrays 131f -genome sequencing 130 Agvobacterium-mediated transformation 135 algorithmic interpretation 106 alignment, consensus methods 295 -ESTsequences 290 -global-287 -Hidden Markov Model 291 -local-287f -multiple-291 -Needleman and Wunsch method 287 -pairwise -287,289f -score 287 -Smith and Waterman method 287 alignment methods 286ff alpha 1 -antitrypsin deficiency (alphalAD) Alzheimer disease 54,68,71,10S amino acids, residue properties 319 amino acid weight matrices 113 Aminoacyl-tRNA synthetase Database 371 amplicon generation 197 amplified fragment length polymorphism (AFLP) AmpliTaq FSTM 179 aneuploidy 75 Angelman syndrome (AS) 73f annotated databases 270 annotation, of the human genome DNA sequence 70 150 49ff -cataloguing the genes 51ff anonymization, of DNA samples 387 anticipation 69 APCgene 83 apolipoprotein E 68 Arabidopsis Genome Initiative 26 Arabidopsis Information Resource (TAIR) 269 Arabidopsis thaliana 129ff -functional assignments 27 functional genomics 28 geneticmap 25 genome project 24ff -mitochondria1 genome 27 plant-specific functions 28 -plastid genome 27 -postgenome era 27f -repetitive elements 27 -transposable elements 27 Archaeuglubus fulgidus, electron micrograph 16 flap endonucleases 19 -genes 18 -genome project 16ff -IS elements 18 -paralogous gene families 18 -postgenome era 19 -repeats 18 -sulfate metabolism 19 sulfate reduction 16 array format 335 arraying.glass microscope slides 192 artificial intelligence 311 Asilomar Conference 9 ASN.l 369 architectural model 367 assembly coverage 344 assembly engine 334 assembly software 197 Atlas 276 atom-and-bonds representation 368 ATP sulfurylase 192 automated DNA sequencing 398f
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.783 | 0.734 |
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".