How to Resolve the Problem of Drago's Four Parameters in the Context of Molecular Interactions
Bibliographic record
Abstract
This study aims to provide a new thermodynamic method for determining the value of Drago's four interaction parameters, namely Ea, Eb, Ca, and Cb (kcal1/2 mol-1/2). The method is based on the following fundamental novelties: The values of the parameters Ea, Eb, Ca, and Cb are simultaneously determined for seven amphoteric substances. Thus, there are a total of 28 values to be determined, with each set consisting of seven substances. For the seven selected amphoteric substances, there are seven equations of the type: V∂2h / n = (Ea Eb + Ca Cb) Next, all possible 2-to-2 combinations of these seven substances are generated. For each 2-to-2 combination, one of the two is selected as a solute (2) and the other as a solvent (1), or vice versa. By measuring the mixing energy, ΔEmix (2.1), of these combinations, the 21 measurements available to extract the energy, ΔEint, of chemical bonds, according to the enclosed Buchmann paper: ΔEmix (2.1) = (Ea1 Eb2 + Ca1 Cb2) + (Ea2 Eb1 + Ca2 Cb1) Next, the seven equalities of the type V∂2h / nj = (Eaj Ebj + Caj Cbj) (kJ / mol) with j = 1,7 are put together with 21 equalities of the type ΔEint = (Eaj Ebj+1 + Caj Cbj+1) + (Eaj+1 Ebj + Caj+1 Cbj). This will generate a system comprising 28 equations for 28 unknown parameters. The resolution of this system will afford the 28 sought values of Drago's four parameters Ea, Eb, Ca, Cb for the seven selected substances.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".