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Record W6980657749

Collaborative design in electromagnetics

2007· dissertation· en· W6980657749 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2007
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicPlant nutrient uptake and metabolism
Canadian institutionsnot available
Fundersnot available
KeywordsRepresentation (politics)Set (abstract data type)Construct (python library)SoftwareArchitectureElectromagneticsSoftware architecturePersonalizationReference architecture
DOInot available

Abstract

fetched live from OpenAlex

L'auteur a accordé une licence non exclusive permettant à la Bibliothèque et Archives Canada de reproduire, publier, archiver, sauvegarder, conserver, transmettre au public par télécommunication ou par l'Internet, prêter, distribuer et vendre des thèses partout dans le monde, à des fins commerciales ou autres, sur support microforme, papier, électronique et/ou autres formats.L'auteur conserve la propriété du droit d'auteur et des droits moraux qui protège cette thèse.Ni la thèse ni des extraits substantiels de celle-ci ne doivent être imprimés ou autrement reproduits sans son autorisation.Conformément à la loi canadienne sur la protection de la vie privée, quelques formulaires secondaires ont été enlevés de cette thèse.Bien que ces formulaires aient inclus dans la pagination, il n'y aura aucun contenu manquant.120 The fourth control cycle occurs at time Il min, when ANSYS completes.It returns a value for the force on the plunger.The task manager evalutes the execution conditions for all four KSs.ANSYS has 0 of 1 conditions satisfied, MagNet has 0 of 2 (previously 0 of 2), SPICE has 1 of 1 (previously 1 of 1), and ThermNet has 1 of 1 (previously 1 of 1).No KS saw an increase in its number of satisfied conditions, so the task manager sets act(ANSYS, MagNet), act(ANSYS, SPICE), act(ANSYS, ThermNet) all to o. SPICE and ThermNet both satisfy aU their execution conditions; furthermore, there are no other running KSs that they could benefit from waiting for, so both are dispatched immediately.The system state is summarized in table 4-6.ACKNOWLEDGEMENTS l want to express my appreciation to my supervisor, D.A. Lowther, for his many enlightening discussions, as weU as for his useful comments on the preliminary version of this thesis.His advice, patience, and sense of humor over the past years have been invaluable.l am also thankful to Infolytica for providing us with the licenses for MagNet and ThermNet, and for their feedback.l would like to thank my past and present friends in CADLAB with whom l shared the good time and the stresses during our studies.l thank them aU for the great working environment that we had, which made our lives more enjoyable.Finally, this thesis could

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0050.004
Open science0.0020.005
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0330.005

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 head0.017
GPT teacher head0.237
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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
Published2007
Admission routes1
Has abstractyes

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