AUTOMATIC ASSIGNMENT AND INTERNAL ROTATION WITH PGOPHER
Bibliographic record
Abstract
This talk describes recent updates to the \\textsc{pgopher} program\\footnote{C. M. Western, J Quant. Spec. Radiat Trans., 186 221 (2017)} (http://pgopher.chm.bris.ac.uk), including new tools for computer assisted assignment of spectra and simulate spectra involving internal rotation. The new tools for assignment are described in a recent paper\\footnote{C. M. Western and B. E. Billinghurst, Phys. Chem. Chem. Phys., 21 13986 (2019)} and include (I) a method of trying multiple assignments automatically based on the \\textsc{autofit} algorithm of the group of Brooks Pate\\footnote{N. A. Seifert, I. A. Finneran, C. Perez, D. P. Zaleski, J. L. Neill, A. L. Steber, R. D. Suenram, A. Lesarri, S. T. Shipman, B. H. Pate, J Mol. Spectrosc. 312, 13, (2015)}, and (II) a new form of presenting assignments, a nearest lines plot. These latter plots allow possible sets of assignments to be accepted (or rejected) quickly, and also allow the rapid extension of initial assignments to an entire branch or band. Both these tools have been applied to the analysis of high resolution IR spectra, allowing the rapid assignment of ~10,000 lines for a band, even in the presence of strong overlapping transitions. These tools are now being supplemented with tools for handling internal rotation in \\textsc{pgopher}, including a general way of handling the special permutation inversion symmetry that is typically required for such molecules, and calculating levels affected by internal rotation, either by adding empirical terms to a standard asymmetric top Hamiltonian, or a more elaborate approach based on including multiple torsional states. Progress on the development of these tools will be presented, with applications to spectra taken on the far IR beamline of the Canadian light source\\footnote{The Canadian Light Source, is supported by the Canada Foundation for Innovation, Natural Sciences and Engineering Research Council of Canada, the University of Saskatchewan, the Government of Saskatchewan, Western Economic Diversification Canada, the National Research Council Canada, and the Canadian Institutes of Health Research.}.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.043 | 0.023 |
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".