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
A molecularly imprinted polymer (MIP) film using catechol as the template was designed for adsorption of a range of phenols from water. Four different isotherm models (Langmuir (LI), Freundlich (FI), Langmuir-Freundlich (L-FI), and Brunauer, Emmett, and Teller (BET)) were used to study the MIP adsorption of five phenolic compounds: phenol (Ph), 2-methylphenol (2-MP), 3-methylphenol (3-MP), 2-chlorophenol (2-CP), and 4-teroctylphenol (4-OP). Each model was evaluated for its fit with the experimental data, and key parameters, including a number of binding sites and binding site energies, were compared. Though the LI, L-FI, and BET models showed good agreement for estimation of the number of binding sites and affinity for most adsorbates, no single model was suitable for all. The LI and L-FI models gave the best fitting statistics for the Ph, 2-MP, 3-MP, and 2-CP. The recognition of 4-OP, which has much higher binding affinities than the smaller phenolic compounds not attributable to hydrophobicity alone, was explained only by the BET model, which indicates the formation of multilayers. The BET model failed only with phenol. MIPs also showed higher adsorption capacities and improved homogeneity over the analogous non-imprinted polymers.
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 | 0.001 |
| 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 | 0.002 |
| 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