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Record W2001719143 · doi:10.1080/1065657x.2014.896759

Modification and Industrial Applicability of a Temperature Probe Capable of Tracking Compost Temperature on a Random Particle Level

2014· article· en· W2001719143 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

VenueCompost Science & Utilization · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicComposting and Vermicomposting Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCompostTracking (education)Particle (ecology)Environmental scienceAerationThermistorMaterials scienceAnalytical Chemistry (journal)Waste managementChemistryEngineeringElectrical engineeringChromatographyEcology

Abstract

fetched live from OpenAlex

ABSTRACTIt is generally accepted that exposure of all compost particles to temperatures ≥55°C for at least three consecutive days is a sufficient criterion for a compost to be considered hygienic. Nonetheless, there are no known studies confirming that routine composting operations consistently provide the conditions to meet this criterion. The objectives of this study were: (i) to develop a self-contained temperature probe capable of mimicking random particle behavior in compost and recording the temperature it is exposed to, while withstanding adverse operating conditions; (ii) to validate the probe's physical characteristics in a field-scale operation; and (iii) to assess the recovery of probes from a full-scale compost operation. Two field trials found the probes do behave like random particles and that the aluminum case adequately protected the probe's circuitry and cryovial. Another two trials were conducted to analyze probe recovery. Temperature probes were randomly introduced into a freshly built aerated static pile. In the first trial, 80 m3 of material was screened in one day and the probe recovery efficiency was 100%. In the second trial, screening of 440 m3 of material was completed in three days and 79% of the probes were recovered. The inability to achieve a recovery rate of at least 90% could be due to the high moisture content (≥50%) of the material being screened, the high fraction of oversized material, and, most importantly, the heavy reliance on visually locating the probes in the screen overs.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.156
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.126
GPT teacher head0.296
Teacher spread0.170 · 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