MétaCan
Menu
Back to cohort
Record W4380980054 · doi:10.55849/jidc.v2i1.106

Analysis of Radio Broadcast

2022· article· en· W4380980054 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal International Dakwah and Communication · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Finance and Communication
Canadian institutionsConcordia University
Fundersnot available
KeywordsBroadcasting (networking)Radio broadcastingEntertainmentRadio programComputer scienceBroadcast engineeringMultimediaAdvertisingPublic broadcastingGraphicsTelecommunicationsComputer networkBusinessComputer graphics (images)Political science

Abstract

fetched live from OpenAlex

Radio is a public media that conveys the content of its message in the form of information, entertainment, news, and education by audio. In broadcasting, the Radio should have a program that suits the tastes of listeners, has excellent programs, and broadcasters who have their own privileges in communicating with their listeners, as is the case with this Fuad FM radio with some of its program programs that adjust the tastes of its listeners, besides that it does not forget to make its flagship show programs. Therefore, the purpose of this study is to analyze radio broadcast programs in general. The motto used is a qualitative research method. The results obtained from this study show an in-depth analysis of the ins and outs of radio broadcasting, starting from the programs, strategies for creating programs, factors, and others. So, a broadcast program is everything that a broadcasting station displays in the form of sound, image, or sound and image or in the form of graphics, and characters, whether interactive or not, that can be received through a broadcast receiving device to meet the needs of its audience.

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.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.807
Threshold uncertainty score0.737

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.020
GPT teacher head0.321
Teacher spread0.302 · 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