Preliminary project design for insect production: part 1 – overall mass and energy/heat balances
Bibliographic record
Abstract
Preliminary project design (PPD) is an initial stage in project development that makes it possible for an entopreneur to gain insight into the feasibility and potential profitability of setting up an insect production facility. In this paper a simple, spreadsheet-based model is presented to facilitate the first step of PPD by estimating the overall mass and energy balances for a proposed project. The model calculates outputs on the basis of scientific data and estimated values for operating parameters for the system that is proposed. With the model it is easy to use a trial-and-error approach to investigate the effect of different parameter values on system operation. Thus, the entopreneur can enter values for parameters such as feed composition, temperature of the cooling air, etc. and see the effect on system productivity, conversion efficiency, energy requirements, etc. immediately. This facilitates the overall procedure of reaching final decisions about the organism, the feed, the processing approach, the scale of operation, etc. Normally, this is an iterative procedure that is based on ‘trial-and-error’, the two aspects being referred to here as the ‘twin components of an iterative knowledge engine’. Thus, the outputs from the model will depend very much on the scientific data supplied and the values of the input parameters while, at the same time, use of the model will highlight what additional scientific data is needed and what alternate parameter values might prove profitable. Overall, the model allows the user to explore a large possibility space for both process constitution and operation much more quickly and easily than by experimental means alone. As such, it is a tool that can aid the entopreneur in thinking about a project and considering various alternatives, as well as in making decisions before a major commitment is made to any particular option. It is stressed here that PPD is only a preliminary stage in project development and that the investigation of overall process mass and energy balances is only the first step thereof. It is also stressed that results from modelling are invariably subject to empirical verification as well as ‘common-sense filtering’. The model presented is general and thus not oriented to the production of any species in particular.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.008 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".