Estimating Density Contrast From Global Geopotential Fields
Bibliographic record
Abstract
Fingerprinting mass spectrometric analysis at atmospheric conditions has been realized using an arc plasma-based dissociation (APD) device. Because of its high energy, high temperature, and unique chemical reactivity, the thermal plasma can induce dissociation of neutral molecules or ions produced by atmospheric ion sources. Both even/odd electron (fragment) ions would be generated to provide fingerprinting structural information and molecular weight of the compounds simultaneously. Meanwhile, elimination and aromatization were observed as special dissociation patterns in this device, which can be applied in the differentiation of isomers. The good compatibility with atmospheric ion sources is demonstrated by coupling the device with nanoelectrospray ionization (nano-ESI) and zero volt paper spray ionization (PSI), respectively. With erythromycin as the tuning standard, informative dissociation spectra of various compounds can be reproducible, making it possible to establish an arc plasma-based dissociation spectra database. This device allows fingerprinting mass spectrometric analysis, with no need for harsh vacuum conditions and is promising for making a breakthrough in making up the deficiency of atmospheric ionization techniques.
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.
How this classification was reachedexpand
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) | 0.000 | 0.000 |
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 teacher head, 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".