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Characteristic of popular culinary place in Kelurahan Tamalanrea Indah based on Universitas Hassanudin student’s Mental Maps

2020· article· en· W3088405434 on OpenAlexaff
Nurul Maharani, Hartanto Setiadi, N Rizqihandari

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicArchitectural and Urban Studies
Canadian institutionsToronto Metropolitan University
FundersDirektorat Riset dan Pengabdian Masyarakat
KeywordsMental mappingResidenceMental imageSpace (punctuation)PsychologyCitizen journalismCartographyGeographySocial psychologySociologyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Abstract Mental maps concept emerged in discussions among experts since the 1960s where the concept was combined using participatory in exploring the visualization of the city and spatial preferences. This study discusses the characteristics of popular eating places based on an evaluation of spatial products in the discussion of space. For comparison purposes, it takes participants who need to fill in the required form about the characteristics of the eating place based on their favorite places to eat and analyze the printed map and mental map. Universitas Hassanudin students are selected as research participants. They chose to map three of their favorite eating places in Tamalanrea Indah Village as a basis to determine their popular eating places while revealing their mental maps. In total, there are 10 participants which produced 18 names of favorite eating places. Ten respondents who were willing to fill in the map, and evaluate the mental maps, is compared. From the data obtained, the three most popular places to eat in Tamalanrea Indah Village that were successfully validated were Bokatana, Waroeng Dian and Warung Alhamdulillah. In general, the mental map produced is based on the variable length of stay and length of study at the Universitas Hassanudin which affects the accuracy of the mental maps, while for popular eating places students are selected based on the distance from the faculty to compare the distance of the residence.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score0.753

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.023
GPT teacher head0.194
Teacher spread0.171 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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