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Record W2042098027 · doi:10.1081/amp-100104297

HOLE QUALITY IN DEEP HOLE DRILLING

2001· article· en· W2042098027 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueMaterials and Manufacturing Processes · 2001
Typearticle
Languageen
FieldEngineering
TopicTunneling and Rock Mechanics
Canadian institutionsnot available
FundersJordan University of Science and Technology
KeywordsMaterials scienceDeep hole drillingDrillingQuality (philosophy)MetallurgyMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract Deep hole drilling represents the most economical method of hole producing with length-to-diameter ratios ≥5. The objective of this study was to ascertain the effect of machining parameters on hole quality produced by the deep hole machining process and to develop a better understanding of the effect of these process parameters on the hole quality. Such an understanding can provide insight into the quality control problems of the holes when the process parameters are adjusted to obtain certain characteristics. This study deals with the experimental results obtained during boring trepanning association (BTA) drilling on medium carbon steel (AISI 1060). The surface roughness, out-of-roundness, and hole size are influenced by cutting speed and feed rate of the deep hole drilling. 5.0 ACKNOWLEDGMENTS The author gratefully acknowledges the use of the laboratory facilities at Jordan University of Science and Technology, Irbid, Jordan, and Concordia University, Montreal, Canada.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.472
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.015
GPT teacher head0.233
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