A new version of AAKF (Reduced Tensor Matrix Elements) adapted to spectroscopic notation
Bibliographic record
Abstract
Abstract Title of program: REDUCED TENSOR MATRIX ELEMENTS 2 Catalogue number: AAKP Program obtainable from: CPC Program Library, Queen's University of Belfast N. Ireland (see application form in this issue) Computer: Installation: IBM 360/75 University of Waterloo, Waterloo, Ont. Canada Operating system: OS/360 HASP II Programming languages used: FORTRAN IV High speed store required: 102 K bytes No. of bits per byte: 8 Overlay structure: None Other peripherals used: Card reader, line printer No. of ca... Title of program: REDUCED TENSOR MATRIX ELEMENTS 2 Catalogue Id: AAKP_v1_0 Nature of problem This program is a revision of Robb's TENSOR program which enables one to calculate... CORRECTION SUMMARY: Vol:Year:Page 13:1977:231 "000A CORRECTION 12/04/77" "A new version of AAKF (reduced tensor matrix elements) adapted to spectroscopic notation. (C.P.C. 9(1975)370)." C.F. Fischer; K.M.S. Saxena ADAPTATION SUMMARY: Vol:Year:Page 13:1977:289 "0001 ADAPT TENSOR 2 FOR PRODUCT" "Adaptation of the new version of the reduced tensor matrix elements (AAKP) program: inclusion of the evaluation of matrix elements of tensor products." K.M.S. Saxena ADAPTATION SUMMARY: Vol:Year:Page 16:1978:57 "0002ADAPT TENSOR 2 TO CHECK DATA" "Adaptation of the new version of the reduced matrix elements (AAKP) program; inclusion of the checking of the input data." K.M.S. Saxena Note: adaptation instructions are contained in source code Note: correction instructions are contained in source code Versions of this program held in the CPC repository in Mendeley Data AAKP_v1_0; REDUCED TENSOR MATRIX ELEMENTS 2; 10.1016/0010-4655(75)90017-X This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018)
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.308 | 0.229 |
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".