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Record W2799475877 · doi:10.1139/tcsme-2017-1030

ANCIENT CHINESE MAZE LOCKS

2017· article· en· W2799475877 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicHistorical Astronomy and Related Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLock (firearm)KeyholeHead (geology)Computer scienceKey (lock)Insert (composites)EngineeringMechanical engineeringGeologyOperating system

Abstract

fetched live from OpenAlex

There are many types of ancient Chinese locks that were designed using thin pieces of barbed springs in the locks. The geometric relativity and the elasticity effect between the key and the barbed springs were the main mechanisms for locking and opening. For some special locks, it is very difficult to insert the key-head into the keyhole. In the operation, the key-head must contact the keyhole in the right position and the right orientation in order to enter the keyhole. Discovering how to insert the key-head is similar to steering a maze, so such locks are named “maze locks” or “fixed-orientation locks”. This paper introduces the structures of maze locks, which were widely used in ancient China. The historical development of ancient Chinese locks is briefly introduced first. Then, the basic characteristics of the barbed-springs lock are presented. Finally, three examples are provided to illustrate the opening processes of maze locks.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.945
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.203
Teacher spread0.197 · 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