Bibliographic record
Abstract
Editor's column The 2-year downturn in oil prices has been a challenge for operators and service companies alike, but operators appear to have turned a corner, going by the most recent fourth-quarter earnings. For the larger service providers, it may take longer to gain solid financial footing, but the chief executives of these firms are sounding more optimistic. After months of cost cutting and reassessment of projects, earnings for the larger majors were positive. More stable oil prices and OPEC’s recent production agreement point to a brighter year in 2017. Total boasted a USD 548 million profit for the quarter, compared with a USD 1.6 billion loss in the fourth quarter of 2016. The company announced that it was ready to embark on new projects, possible acquisition, and increased production. BP eked out a USD 72 million profit compared with a USD 2.2 billion loss in the year-ago period. Shell also reported profits, although net revenue was down from the previous year’s quarter. Shell said it had “turned a corner” after paying down debt and absorbing BG. Chevron posted its second straight quarterly profit and sees production growth this year amid cautious spending and cost control. ExxonMobil, meanwhile, recorded its lowest earnings in 2 decades and took a huge writedown on the value of some of its upstream assets. Smaller operators, particularly those involved in shale plays in west Texas, New Mexico, and other promising areas, plan more aggressive upstream spending this year. While many larger international plays still seem risky, activity in places such as the Permian Basin is soaring. Service companies are also seeing a better year compared with the previous two, particularly for those involved in North American operations, but still face some challenges. Many service providers have begun renegotiating prices with clients, after slashing prices the past 2 years because of the steep fall in oil prices. “The direction [service companies] all need to go is that we need to recover some of the pricing concessions that we’ve given,” Schlumberger Chief Executive Officer Paal Kibsgaard told the Wall Street Journal during an earnings presentation.
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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".