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Low-Cost Solar Powered Automated Multi-Tasking Agricultural Robot to improve the Growth and Yield of the Plants

2023· article· en· W4383748109 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicControl and Dynamics of Mobile Robots
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsRobotAgricultureDiggingAgricultural machineryWork (physics)Agricultural engineeringAgrarian societyTask (project management)Plan (archaeology)Solar poweredEngineeringComputer scienceGeographyArtificial intelligenceSystems engineeringMechanical engineering

Abstract

fetched live from OpenAlex

Many Asian countries, like India, have agrarian economies, and the great majority of their rural populations depend on horticulture for employment. Pointed toward expanding the efficiency and This robot is meant to perform the work in question while minimising it the essential capabilities expected to be done in ranches. We intend to make a performing various tasks farming robot which will zero in on necessary work of ranch. A mechanical arm will use an accurate depth and equal spacing between the seeds to plant the seeds. A water syphon will be installed at the base of the robot and according to the prerequisite water will be sprinkled. This task expects to plan a rural robot, which assists individuals with enduring where it performs activities like digging of soil (ploughing ), planting of seeds, splashing water and cutting the plants. In past ventures the methods utilized were confounded as well as costly.[1]

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.772
Threshold uncertainty score0.267

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 studies0.0000.000
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 head0.007
GPT teacher head0.199
Teacher spread0.192 · 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

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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