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Record W2773796740 · doi:10.5539/jgg.v9n4p37

Topographic Analysis of Landing Areas of Apollo Moon Missions

2017· article· en· W2773796740 on OpenAlexvenueno aff
Pyrrhon Amathes, Paul Christodoulides

Bibliographic record

VenueJournal of Geography and Geology · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpace exploration and regulation
Canadian institutionsnot available
FundersNational Aeronautics and Space Administration
KeywordsMoon landingApolloElevation (ballistics)Human spaceflightLongitudeLunar orbitAstrobiologyLatitudeAeronauticsGeologyRemote sensingGeographySpace explorationMeteorologyGeodesySpacecraftEngineeringAerospace engineeringAstronomyPhysics

Abstract

fetched live from OpenAlex

The Apollo program was NASA’s (National Aeronautics and Space Administration) human spaceflight program, accomplishing landing of the first humans on the Moon from 1969 to 1972. Ever since there have been scientific and public questions about its legitimacy and claims that the associated Moon landings were staged by NASA and/or other organizations. In this paper we examine a number of the Apollo mission images through (i) a comparison with simulated views of Google Earth (Moon) and (ii) a photographic analysis of some of their features using Photoshop®. The functionality of latitude, longitude, elevation and elevation profile of Google Earth is addressed by means of a comparison with other available programs possessing the same features like NASA’s Moon Trek and Alcyone Lunar Calculator. The topographic analysis through Google Moon simulations indicate that the landscapes in Apollo mission images used were inaccurate presentations of reality and there are incorrect elevations and serious land feature omissions. Moreover, the Photoshop® analysis shows conclusively that images were staged, manipulated or altered.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.168

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.273
Teacher spread0.261 · 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".

Quick stats

Citations1
Published2017
Admission routes1
Has abstractyes

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