Performance of an Analytical, Dual Infrared-Beam, Stored-Product Insect Monitoring System
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.
Bibliographic record
Abstract
A system is described for automated monitoring of pest insects in stored grain. It provides quantitative data indicative of the species of detected insects and is self-calibrating to maintain reliable operation over time across adverse environmental and biological conditions. The system uses electronic grain probes, each with a dual infrared-beam sensor head providing orthogonal views of falling insects. Sensor analog signals are analyzed by an embedded microprocessor, and extracted waveform parameters are transmitted back to a central computer. Filtering algorithms recognize and eliminate false detections due to extraneous (nonfalling) insect activities and provide an indication of species based on body size. Laboratory test data provide species identification templates and an analysis of Montana field test data acquired in aerated and nonaerated bins demonstrates the effectiveness of the filtering algorithms. The described system technology has been licensed by OPIsystems, Inc., Calgary, Alberta, Canada, and is commercially available as Insector.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it