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Record W2884552071 · doi:10.1002/pts.2385

The influence of stretch wrap containment force on load bridging in unit loads

2018· article· en· W2884552071 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePackaging Technology and Science · 2018
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsToronto Metropolitan University
FundersU.S. Forest ServiceU.S. Department of Agriculture
KeywordsPalletStiffnessBridging (networking)Deflection (physics)Structural engineeringUnit loadEngineeringMechanical engineeringComputer sciencePhysics

Abstract

fetched live from OpenAlex

The term “load bridging” describes a phenomenon in which the physical interaction between various packaging components acts as a series of discrete loads in a given unit load and adds stiffness to the shipping pallet/load combination. Current pallet design practices often ignore the aspect of load bridging and assume that the pallet payload is flexible and uniformly distributed over the pallet surface. This can influence the load‐carrying capacity of the pallet. The study reported in this paper investigated the relationship between the stretch wrap containment force and load bridging in unit loads and the resulting unit‐load deflection. The experimental results of this study indicate that an increase in the stretch wrap containment force can improve the unit‐load deflection by as much as 81%. The influence of the stretch wrap containment force on pallet deflection is greatest for small packages and pallets with low stiffness. These experimental results provide useful information for realizing more efficient and sustainable unit‐load designs.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.431

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.009
GPT teacher head0.246
Teacher spread0.238 · 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