Bibliographic record
Abstract
It is possible that non-Australasian readers of this journal do not know of an Australian referendum that will take place on the 14th October, shortly after this issue of the journal is published. Such readers may not be aware of its significance and the vigorous debate it has generated in Australia. More details can be found at this official government website https://voice.gov.au. In a thoughtful, well structured and passionate editorial, Glenn Harrison discusses the background to the referendum, its contemporary relevance and importance, and why the Australasian College for Emergency Medicine is proud to support The Voice to Parliament. Artificial Intelligence is a development with uncertain long term future consequences for humanity. Will it ultimately be beneficial, malign or somewhere in between? We publish two papers of relevance to readers of this journal. In one, the authors investigated the freely available version of ChatGPT to find out if it can produce a quality conference abstract using a fictitious but accurately calculated data table as applied by a non-medically trained person. In the second paper, the authors investigated the performance of three prevalent Large Language Models (LLMs - OpenAI's GPT series, Google's Bard, and Microsoft's Bing Chat) on a practice Australasian College for Emergency Medicine (ACEM) primary examination. All LLMs achieved a passing score, with scores with GPT 4.0 outperforming the average candidate. An interesting retrospective cohort study from Adelaide identifies the individual clinical features and risk factors most strongly associated with the diagnosis of transient neurological symptoms with a cerebrovascular cause (TIA or stroke), as compared to common TIA mimics (including retinal ischaemia, migraine and seizure). The authors conclude that for 218/1273 patients diagnosed with stroke, the three features with the highest positive likelihood ratio were the presence of DWI positive lesion on MRI, extracranial carotid atherosclerosis and a history of peripheral vascular disease. For TIA, the three features with the highest positive likelihood ratio were extracranial carotid atherosclerosis, presence of atrial fibrillation and pre-existing anticoagulant therapy. For stroke and TIA, the respective features with the lowest negative likelihood ratios were limb weakness and hypertension. Emergency intubation in children is an infrequent procedure both in the pre-hospital and hospital setting. A collaborative study between a state-wide ambulance service and a tertiary children's hospital in Victoria describes the characteristics of pre-hospital paediatric intubations by Intensive Care Paramedics. Paramedics attended 2674 cases aged 0 to 18 years over the 12-month study period who received basic or advanced airway management. A total of 78 cases required advanced airway management. Sixty-eight patients (87.5%) were intubated successfully on the first attempt, first pass success was lowest in children <1 year of age. The most common indications for pre-hospital intubation were closed head injury and cardiac arrest. It was not possible to report complication rates due to incomplete documentation. Excessive pathology testing is associated with ED congestion, increased healthcare costs and adverse patient health outcomes. A team from Melbourne report on the frequency, yield and influence of pathology tests amongst patients presenting to the ED with atraumatic recurrent seizures. They discovered that most patients presenting to the ED with atraumatic recurrent seizures underwent pathology tests. Abnormalities were frequently detected but were uncommonly associated with change in management. Abnormal pathology tests results rarely led to acute changes in patient management. We recently published a paper from New Zealand about a management pathway for patients presenting with atrial fibrillation. It provoked a letter from Ian Stiell in Canada. We publish his letter and the response from the original authors. It makes interesting reading about significant differences in practice between countries, even for a condition as common and well studied as atrial fibrillation. A group from Queensland report the results of a survey that explored clinicians' knowledge, attitude and adherence to the first Australian national peripheral intravenous catheter Clinical Care Standard. Following on from the above, the focus in this issue is on quality improvement. It is a complex topic but the basics of it are simple. One of its most challenging aspects is changing long-standing processes and practices to make permanent improvements. Old habits die hard.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.072 | 0.007 |
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; both teacher heads agree on what is shown here.
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".