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
Currently available rapid diagnostic tests (RDTs) for malaria show large variation in sensitivity and specificity, and there are concerns about their stability under field conditions. To improve current RDTs, monoclonal antibodies (mAbs) for novel malaria antigens have been developed and screened for their possible use in new diagnostic tests. Three antigens, glutamate rich protein (GLURP), dihydrofolate reductase-thymidylate synthase (DHFR-TS) and heme detoxification protein (HDP), were selected based on literature searches. Recombinant antigens were produced and used to immunize mice. Antibody-producing cell lines were subsequently selected and the resulting antibodies were screened for specificity against Plasmodium falciparum and Plasmodium vivax. The most optimal antibody couples were selected based on antibody affinity (expressed as dissociation constants, KD) and detection limit of crude antigen extract from P. falciparum 3D7 culture. The highest affinity antibodies have KD values of 0.10 nM ± 0.014 (D5) and 0.068 ± 0.015 nM (D6) for DHFR-TS mAbs, 0.10 ± 0.022 nM (H16) and 0.21 ± 0.022 nM (H18) for HDP mAbs and 0.11 ± 0.028 nM (G23) and 0.33 ± 0.093 nM (G22) for GLURP mAbs. The newly developed antibodies performed at least as well as commercially available histidine rich protein antibodies (KD of 0.16 ± 0.13 nM for PTL3 and 1.0 ± 0.049 nM for C1-13), making them promising reagents for further test development.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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