Bibliographic record
Abstract
Contents: Foreword Part 1 Characteristics of Complex Decision Making: Decisions about 'what' and decisions about 'how', Erik Hollnagel Corruption and recovery of sensemaking during navigation, Gary Klein Time and design in decision making environments, GA ran Pettersson Risk and decision making, Damien J. Williams Extreme risk-taking and decision making, Bruno Sicard, Elisabeth Jouve, and Olivier Blin. Part 2 Areas of Application: Human requirements in automated weapons systems, Jennifer McGovern Narkevicius and Peggy Heffner Automation and decision making, Jan Noyes The flightdeck of the future: field studies in datalink and freeflight, Gemma Cox, Sarah Sharples, Alex Stedmon, John Wilson and Tracey Milne The flightdeck of the future: perceived urgency of speech and text, Alex Stedmon, Sarah Sharples, Edward Nicholson, Gemma Cox and John Wilson Operator interface research testbed for supervisory control of multiple unmanned aerial vehicles (UAVs), Gloria Calhoun, Mark Draper and Heath Ruff Virtual environments for military decision making, John Kostaras and Georgias Detsis ROLF 2010: A Swedish command post of the future, Berndt Brehmer. Part 3 Complex Decision Making in Civil Applications: Human information processing aspects of effective emergency incident management decision making, Jim McLennan, Mary Omodei, Alina Holgate and Alexander Wearing Decision making by operational incident commanders in a nuclear emergency response organisation: decision strategy selection, Margaret Crichton, Peter McGeorge and Rhona Flin Presentation of verbal material: the impact of modality on situation awareness and performance on the flightdeck, Alastair Nicholls, Tracey Milne, Eric Farmer and Anne Melia Air traffic controller strategies in holding scenarios, Lynn Springall How roles change when disaster strikes: lessons learnt from the manufacturing domain, Carys Siemieniuch and Murray Sinclair. Part 4 Complex Decision Making in Military Applications: A history lesson on the use of technology to support military decision making and command and control, Robert Bolia, Michael Vidulich, Todd Nelson and Malcolm Cook The intuitive vs. analytic approach to real world problem solving: misperception of dynamics in military operations, BjA,rn Tallak Bakken, Stig Johannessen, Dag SA,berg and Morten Ruud Critical thinking in tactical decision games-training, Karel van den Bosch and Anne Helsdingen. Part 5 Teams and Complex Decision Making: Why training team decision making is not as easy as you think: guiding principles and needs, Eduardo Salas, Joseph Guthrie and Shawn Burke The migration of authority in tactical decision making, Sidney Dekker, and Nalini Suparamaniam The analysis of team decision making architectures, Richard Breton and Robert Rousseau Surgical team self-review: enhancing organisational learning in the Royal Cornwall Hospital Trust, Simon Henderson, Matt Mills, Adrian Hobbs, Alan Bleakley, James Boyden and Linda Walsh. Part 6 Assessment and Measurement: A method for need analysis before decision making based on ecological psychology, Thierry Morineau Operational net assessment: a Canadian human factors analysis, Philip Farrell Psycho-physiological measures of situation awareness, Han Tin French, Elizabeth Clarke, Diane Pomeroy, Melanie Seymour and C.Richard Clark Signal detection theory and the assessment of situation awareness, Barry McGuinness Psycho-physiological measurements of mental activity, stress reactions and situation awareness in the maritime full mission simulator, Thomas Koester Measures of attention and cognitive effort in tactical decision making, Sandra Marshall Crew mental workload for the vetronics technology testbed vehicle, Christopher Smyth Full spectrum analysis: practical operational research in the face of the human variable, Graham Mathieson Effective taxonomies in organisational safety, Brendan Wallace and Alastair Ross Using signal detection theory to measure situation awareness: the technique, the tool (QUASAa ), the test, the way forward, Graham Edgar and Helen Edgar. Part 7 A Final Comment: Intelligence, uncertainty, interpretations and prediction failure, Malcolm Cook, Corinne Adams and Carol Angus Index.
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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.030 | 0.004 |
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".