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Record W4386143126 · doi:10.1002/admi.202370072

Characterizing Mineral Ellipsoids in New Bone Formation at the Interface of Ti6Al4V Porous Implants (Adv. Mater. Interfaces 24/2023)

2023· article· en· W4386143126 on OpenAlexaff
Joseph Deering, Jianyu Chen, Dalia Mahmoud, Tengteng Tang, Yujing Lin, Qiyin Fang, Gregory R. Wohl, M.A. Elbestawi, Kathryn Grandfield

Bibliographic record

VenueAdvanced Materials Interfaces · 2023
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsBrockhouse Institute for Materials ResearchMcMaster University
Fundersnot available
KeywordsMaterials scienceBone canaliculusTitanium alloyPorosityTitaniumCortical boneBiomedical engineeringInterface (matter)Composite materialNanotechnologyContact angleAlloyMetallurgyAnatomyMedicine

Abstract

fetched live from OpenAlex

Polar 2D Polymer Crystals In article 2300333, Kathryn Grandfield and co-workers show osteocytes, the bone cells responsible for signaling bone growth and maintenance, together with their cell processes (canaliculi) connecting in the vicinity of a porous titanium dental implant interface. Captured by focused ion beam 3D imaging, the cells are segmented and analyzed to determine their orientation with respect to the newly forming bone.

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 score0.022
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.013
GPT teacher head0.260
Teacher spread0.247 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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