Bibliographic record
Abstract
More than 250 industry leaders involved in Arctic E&P gathered for the 2018 Arctic Technology Conference recently in Houston. Supported by the Offshore Technology Conference’s network of scientific and professional societies, the conference provided a platform for collaboration among colleagues, vendors, and academia to reveal innovations, solutions, ideas, and emerging technologies for both onshore and offshore activities in the Arctic basins. The conference presented a highly specialized program that included more than 70 technical presentations, six panel discussions, and four topical breakfasts and luncheons. The Distinguished Achievement Award ceremony recognized the major technological, humanitarian, environmental, and leadership contributions of an individual and an organization. Due to his contributions and accomplishments in the industry, Kenneth Bird was awarded the Distinguished Achievement Award for Individuals. As a petroleum geologist, Bird led assessment teams to produce a series of scientifically sound, methodologically rigorous, and policy-neutral products widely accepted in Alaska and the global Arctic regions. Since the 1980s, Bird has been at the forefront of resource-assessment projects that have been executed by the US Geological Survey. The National Research Council (NRC) of Canada was presented the Distinguished Achievement Award for their involvement in the development of Arctic tools and technologies. For more than 60 years, NRC Canada has provided regulatory, operational, and engineering design support to clients. There is a Future in the Arctic The current economic and business environment is challenging to conduct safe and environmentally friendly hydrocarbon exploration and development in the Arctic. However, the Arctic continues to be a region of close observation to use relevant technology, respecting local requirements, and be ready for a time when we see a step up and acceleration of activity. In spite of a reduction of E&P activity in the Arctic, this conference continues to attract interest for several reasons: It is by far the premier event focused on the Arctic, not just E&P but also mining, shipping, logistics, environment, and, most importantly, the local people and communities. It is a platform for the passionate community to meet, network, and present quality technical papers. The 2018 event attracted 103 abstracts, which translated to 70 presentations split into 12 technical sessions. Six panel discussions, and four topical breakfasts and luncheons focused on current themes with specific regional focus from the Chukchi (US), through Beaufort, (Canada), through Barents (Finland and Norway) seas. Exhibiting companies showcased their latest products and innovations to specialized decision makers focused on finding unique solutions for successful operations in this area. This was the sixth OTC Arctic Technology Conference to be held. For more information, visit www.otcnet.org/arctic.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.315 | 0.207 |
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".