reported results for its second fiscal quarter ended April 3, 2010.
Bibliographic record
Abstract
o Non-GAAP operating margin of 13.6%; GAAP operating margin of 4.8% o Relative to Q2 guidance, currency was unfavorable to revenue by $3.1 million and favorable to non-GAAP expenses by $1.6 million and to GAAP expenses by $1.9 million • Q3 Guidance: Revenue of $235 to $245 million and non-GAAP EPS of $0.14 to $0.20 o GAAP EPS of $0.02 to $0.07 o Assumes $1.36 USD / EURO, down from $1.46 assumption in previous guidance, a $7 million negative impact to revenue in Q3 • FY 2010 Targets: Maintaining revenue target of $1,015 million and non-GAAP EPS of $1.00 o GAAP EPS of $0.50 o Increasing license revenue growth target to 35 % to 40 % year-over-year growth, up from previous target of 30 % growth o Non-GAAP operating margin of 16%; GAAP operating margin of 7.5% o Assumes $1.36 USD / EURO, down from $1.46 assumption in previous guidance, a $14 million negative impact to revenue in H2’10 The Q2 non-GAAP results exclude $12.3 million of stock-based compensation expense, $8.9 million of acquisitionrelated
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 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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.124 | 0.100 |
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".