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Record W1924543959 · doi:10.1139/cjp-2013-0545

Exploring the infrared-sensing properties of polymorphous silicon-germanium (pm-Si<sub><i>x</i></sub>Ge<sub><i>y</i></sub>:H) thin films

2014· article· en· W1924543959 on OpenAlexvenueno aff
Mario Moreno, Alfonso Torres, Cesar Calleja, Roberto Ambrosio, Pedro Rosales, A. Kosarev, Ricardo Jiménez

Bibliographic record

VenueCanadian Journal of Physics · 2014
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsnot available
FundersConsejo Nacional de Ciencia y Tecnología
KeywordsGermaniumInfraredResponsivitySiliconPhysicsTemperature coefficientThin filmOptoelectronicsAnalytical Chemistry (journal)OpticsPhotodetector

Abstract

fetched live from OpenAlex

In this work we have performed an exploratory study of the infrared (IR) sensing properties of polymorphous silicon–germanium (pm-Si x Ge y :H) thin films. Our objective was to study the characteristics that are important parameters for infrared detection, as activation energy (E a ), thermal coefficient of resistance (TCR), room temperature conductivity (σ RT ), and responsivity to IR radiation. After characterization, our results demonstrated that pm-SiGe:H films have advantages over a-Si:H,B, pm-Si:H, and pm-Ge:H, because of the possibility to tailor its properties as σ RT , E a , and TCR, and moreover, the possibility to adjust those values for specific applications.

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 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 categoriesMeta-epidemiology (narrow)
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 score0.046
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.025
GPT teacher head0.168
Teacher spread0.143 · 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 teacher head, not a consensus.

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

Citations8
Published2014
Admission routes1
Has abstractyes

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