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Record W2323847171 · doi:10.3724/sp.j.1042.2013.01071

Review of Measuring Imagery

2013· article· en· W2323847171 on OpenAlexaff
Xiao Ma, Yu Zhang

Bibliographic record

VenueAdvances in Psychological Science · 2013
Typearticle
Languageen
FieldEngineering
TopicInfrared Target Detection Methodologies
Canadian institutionsQuest University Canada
Fundersnot available
KeywordsRemote sensingGeographyComputer science

Abstract

fetched live from OpenAlex

摘要: 表象测量在训练领域广泛应用, 也是训练成败的关键环节。表象测量方法可分为口头报告纸笔法、实验操作法, 以及神经科学技术共三种方法。其中纸笔报告法以量表测量为主, 包括Betts量表、视觉表象清晰度量表及其修订版和运动表象清晰度量表及其修订版; 实验操作法以心理旋转为基本范式; 神经科学技术主要以经颅磁刺激和功能磁共振成像为主, 测量多种表象过程中不同脑区兴奋性。三者各有优劣, 均有待提高和改进。

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)0.043
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.043
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0080.008
Science and technology studies0.0010.004
Scholarly communication0.0040.006
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.002

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 head0.052
GPT teacher head0.379
Teacher spread0.328 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2013
Admission routes1
Has abstractyes

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