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Record W2810409273 · doi:10.1002/adma.201870196

Photoreceptors: Artificial Rod and Cone Photoreceptors with Human‐Like Spectral Sensitivities (Adv. Mater. 27/2018)

2018· article· en· W2810409273 on OpenAlexaff
Heehong Yang, Tai Hwan Ha, Hyun Seo Park, Seung Ja Oh, Yong‐Sang Ryu, Young-Ho Cho, Hyo‐Suk Kim, Juyeong Oh, Dong Kyu Lee, Chulki Kim, Taikjin Lee, Minah Seo, Jaebin Choi, Young Min Jhon, Deok Ha Woo, Seok Lee, Seok Hwan Kim, Hyuk‐Jae Lee, Seong Chan Jun, Hyun Seok Song, Tai Hyun Park, Jae Hun Kim

Bibliographic record

VenueAdvanced Materials · 2018
Typearticle
Languageen
FieldMedicine
TopicOcular and Laser Science Research
Canadian institutionsBiotechnology Research Institute
Fundersnot available
KeywordsMaterials scienceLight-emitting diodeArtificial lightCone (formal languages)BiomaterialGrapheneBiophysicsOptoelectronicsNanotechnologyOpticsBiologyPhysicsComputer science

Abstract

fetched live from OpenAlex

In article number 1706764, Hyun Seok Song, Tai Hyun Park, Jae Hun Kim, and co-workers report an artificial nano-biomaterial based on human-like photoreceptor proteins and graphene hybrid structures that allows outstanding spectral sensitivities. In experiments with light-emitting diodes (LEDs), these artificial photoreceptors provide color distinguishability similar to that of human photoreceptor cells. This approach can be applied to study physiological, biophysical, and biochemical processes of photoreceptors.

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)0.000
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.297
Teacher spread0.278 · 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
Published2018
Admission routes1
Has abstractyes

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