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Record W4416880172 · doi:10.37665/smpywte56368

Recalling the Lead-Free Manhattan Project

2014· article· W4416880172 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

VenueSMTA International · 2014
Typearticle
Language
FieldBusiness, Management and Accounting
TopicTransportation Systems and Infrastructure
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsGovernment (linguistics)CharterProduct (mathematics)AerospaceKnowledge baseTask (project management)Resource (disambiguation)Best practice

Abstract

fetched live from OpenAlex

ABSTRACT In April and August 0f 2009, seventeen (17) industry subject-matter-experts were assembled in Philadelphia, PA and charged with executing two tasks: 1.) Benchmark the knowledge base of Pb-free technology and its associated impact on performance in aerospace and defense (A&D) products (Phase 1) and 2.) Develop a roadmap that would close the knowledge gaps providing solutions and/or mitigation strategies to confidently address all associated risks (Phase 2). This entire effort was named “The Lead- Free Manhattan Project” (LFMP). The results from both phases were reported in two separate documents with a combined page count of five hundred seventy-nine (579) pages. The page count is reported here not to impress the reader but to emphasize the fact that assessing the impact of any major material change on an industry has far-reaching effects in every aspect of product life cycle, i.e. concept, design, reliability, supply chain, assembly, test, and logistics. Subsequently, as the cost to execute the project was, understandably high and in response to several industry and government inquiries, a special task team, sponsored by the IPC Pb-free Electronics Risk Mitigation (PERM) Council, was stood up in 2012 with a charter to identify priority research areas to help close the knowledge gaps regarding impact and risks associated with the implementation of Pbfree materials in high-performance, i.e. A&D, electronics. The priorities were based on the output of the LFMP. The white paper was released in February 2014. An applicationbased strategy was employed and, as a result, five platform categories were identified in assessing priorities. Those platforms were avionics, ground-based systems, missiles, space systems, and submarine-sea systems. A panel of platform subject-matter-experts, from within the PERM Council, was stood up and their subsequent review of performance and service conditions disclosed that the following four areas should be given attention based on their significant influence and control by service and environmental conditions (in addition to supply chain practices which are beyond the scope of this paper): Tin whisker failure modes Tin whisker risk mitigation Complex systems logistics Pb-free interconnections (e.g. solder joints) including reliability models, effects and assembly qualification Despite this prioritization, some preliminary effort would be required to re-plan the tasks as these were part of an integrated planning approach used in the original LFMP. Subsequently, the impact of performing these as stand-alone tasks would need to be assessed. This paper will briefly re-visit the “mission” of the Lead- Free Manhattan Project and provide some detail on the generation of this prioritized list.

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 categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.810
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.016
GPT teacher head0.234
Teacher spread0.219 · 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