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Record W7036005975

Active shooters — how close are they?

2017· other· en· W7036005975 on OpenAlexaboutno aff

Bibliographic record

VenueVia Medica Journals · 2017
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicBotany, Ecology, and Taxonomy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTerrorismAction (physics)Action planPlan (archaeology)Service (business)
DOInot available

Abstract

fetched live from OpenAlex

Recent terrorist attacks in the United States, Canada and Western Europe have shown an increase in the incidence of “Active Shooters” [1]. These ruthless and desperate assassins usually attack urban and poorly protected areas (lack of armed protection) that are densely populated [2]. Utilizing their strength, they realize that their plan is to maximize the number of casualties, without counting on the consequences of their actions. The basis of their action may be based on extremely radical views. Frequent outcomes for active shooters include suicide during an attack (90%) or the resolution of the threat by the authorities [3]. In response to the ever-increasing number of assassinations and the risk of such incidents in one’s immediate surroundings, comprehensive education should be widely spread. Thus, it is important to promote appropriate behaviour, rules of reaction during an attack by an armed assailant, as well as cooperation with incoming service personnel. Such actions will not only help one prevent, but also allow one to prepare for such incidences.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.219
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.046
GPT teacher head0.263
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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